2025-08-14T21:01:39.2580629Z Current runner version: '2.328.0'
2025-08-14T21:01:39.2586958Z Runner name: 'i-02d6cf458b1433fa4'
2025-08-14T21:01:39.2587737Z Runner group name: 'Default'
2025-08-14T21:01:39.2588720Z Machine name: 'ip-10-1-41-230'
2025-08-14T21:01:39.2591890Z ##[group]GITHUB_TOKEN Permissions
2025-08-14T21:01:39.2594269Z Contents: read
2025-08-14T21:01:39.2594925Z Metadata: read
2025-08-14T21:01:39.2595563Z ##[endgroup]
2025-08-14T21:01:39.2597862Z Secret source: Actions
2025-08-14T21:01:39.2598654Z Prepare workflow directory
2025-08-14T21:01:39.3167450Z Prepare all required actions
2025-08-14T21:01:39.3209920Z Getting action download info
2025-08-14T21:01:39.6028692Z Download action repository 'pytorch/test-infra@main' (SHA:83f58f391e939c10dcb8cb6d745e4cefa3b98a84)
2025-08-14T21:01:41.5102670Z Download action repository 'pytorch/pytorch@main' (SHA:eac2d9d695a32dd456050f45cac35134ec3809f4)
2025-08-14T21:01:55.0125653Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065)
2025-08-14T21:01:55.3340724Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722)
2025-08-14T21:01:55.5631811Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076)
2025-08-14T21:01:55.7369315Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a)
2025-08-14T21:01:56.0987384Z Getting action download info
2025-08-14T21:01:56.2215434Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955)
2025-08-14T21:01:56.4932343Z Getting action download info
2025-08-14T21:01:56.6138723Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e)
2025-08-14T21:01:56.8547206Z Getting action download info
2025-08-14T21:01:56.9584804Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482)
2025-08-14T21:01:57.1617841Z Getting action download info
2025-08-14T21:01:57.3012337Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (1fc683cf17c8c673044538d10266c00f92987be2)
2025-08-14T21:01:57.3016518Z ##[group] Inputs
2025-08-14T21:01:57.3016909Z   build-environment: linux-jammy-py3.13-clang12
2025-08-14T21:01:57.3020074Z   test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}
2025-08-14T21:01:57.3023588Z   docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:01:57.3024405Z   sync-tag: 
2025-08-14T21:01:57.3025241Z   timeout-minutes: 240
2025-08-14T21:01:57.3025498Z   use-gha: 
2025-08-14T21:01:57.3025733Z   dashboard-tag: 
2025-08-14T21:01:57.3025999Z   s3-bucket: gha-artifacts
2025-08-14T21:01:57.3026274Z   aws-role-to-assume: 
2025-08-14T21:01:57.3026847Z   disable-monitor: false
2025-08-14T21:01:57.3027443Z   monitor-log-interval: 5
2025-08-14T21:01:57.3027857Z   monitor-data-collect-interval: 1
2025-08-14T21:01:57.3043675Z ##[endgroup]
2025-08-14T21:01:57.3044101Z Complete job name: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:01:57.3523824Z A job started hook has been configured by the self-hosted runner administrator
2025-08-14T21:01:57.3627302Z ##[group]Run '/home/ec2-user/runner-scripts/before_job.sh'
2025-08-14T21:01:57.3636354Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:01:57.3637030Z ##[endgroup]
2025-08-14T21:01:58.5323817Z Runner Type: lf.linux.2xlarge
2025-08-14T21:01:58.5324315Z Instance Type: c5.2xlarge
2025-08-14T21:01:58.5324582Z AMI Name: unknown
2025-08-14T21:01:58.5351971Z AMI ID: ami-05ffe3c48a9991133
2025-08-14T21:02:04.1561568Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main
2025-08-14T21:02:04.1562063Z with:
2025-08-14T21:02:04.1562647Z   github-secret: ***
2025-08-14T21:02:04.1563382Z   instructions: All testing is done inside the container, to start an interactive session run:
  docker exec -it $(docker container ps --format '{{.ID}}') bash

2025-08-14T21:02:04.1564200Z   activate-with-label: false
2025-08-14T21:02:04.1564489Z   label: with-ssh
2025-08-14T21:02:04.1564746Z   remove-existing-keys: true
2025-08-14T21:02:04.1565025Z   fail-silently: true
2025-08-14T21:02:04.1565287Z env:
2025-08-14T21:02:04.1565513Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:02:04.1565777Z ##[endgroup]
2025-08-14T21:02:04.2721832Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info.
2025-08-14T21:02:04.2723124Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys
2025-08-14T21:02:04.2869414Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main
2025-08-14T21:02:04.2869883Z with:
2025-08-14T21:02:04.2870094Z   no-sudo: true
2025-08-14T21:02:04.2870344Z   submodules: recursive
2025-08-14T21:02:04.2870623Z   fetch-depth: 0
2025-08-14T21:02:04.2870851Z env:
2025-08-14T21:02:04.2871100Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:02:04.2871379Z ##[endgroup]
2025-08-14T21:02:04.2957613Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:02:04.2958623Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:02:04.2967782Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:02:04.2968175Z env:
2025-08-14T21:02:04.2968425Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:02:04.2968704Z ##[endgroup]
2025-08-14T21:02:04.3059067Z ##[group]Run # Use all available CPUs for fetching
2025-08-14T21:02:04.3059538Z # Use all available CPUs for fetching
2025-08-14T21:02:04.3059913Z cd "${GITHUB_WORKSPACE}"
2025-08-14T21:02:04.3060300Z git config --global fetch.parallel 0
2025-08-14T21:02:04.3060707Z git config --global submodule.fetchJobs 0
2025-08-14T21:02:04.3061080Z 
2025-08-14T21:02:04.3061443Z # Clean workspace. The default checkout action should also do this, but
2025-08-14T21:02:04.3061941Z # do it here as well just in case
2025-08-14T21:02:04.3062273Z if [[ -d .git ]]; then
2025-08-14T21:02:04.3062564Z   if [ -z "${NO_SUDO}" ]; then
2025-08-14T21:02:04.3062886Z     sudo git clean -ffdx
2025-08-14T21:02:04.3063179Z   else
2025-08-14T21:02:04.3063411Z     git clean -ffdx
2025-08-14T21:02:04.3063683Z   fi
2025-08-14T21:02:04.3063903Z fi
2025-08-14T21:02:04.3070359Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:02:04.3070765Z env:
2025-08-14T21:02:04.3071078Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:02:04.3071375Z   NO_SUDO: true
2025-08-14T21:02:04.3071681Z ##[endgroup]
2025-08-14T21:02:04.3195995Z ##[group]Run actions/checkout@v4
2025-08-14T21:02:04.3196314Z with:
2025-08-14T21:02:04.3196571Z   ref: 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:02:04.3197091Z   fetch-depth: 0
2025-08-14T21:02:04.3197329Z   submodules: recursive
2025-08-14T21:02:04.3197605Z   show-progress: false
2025-08-14T21:02:04.3197884Z   repository: pytorch/pytorch
2025-08-14T21:02:04.3198339Z   token: ***
2025-08-14T21:02:04.3198566Z   ssh-strict: true
2025-08-14T21:02:04.3198814Z   ssh-user: git
2025-08-14T21:02:04.3199070Z   persist-credentials: true
2025-08-14T21:02:04.3199342Z   clean: true
2025-08-14T21:02:04.3199610Z   sparse-checkout-cone-mode: true
2025-08-14T21:02:04.3199924Z   fetch-tags: false
2025-08-14T21:02:04.3227039Z   lfs: false
2025-08-14T21:02:04.3227330Z   set-safe-directory: true
2025-08-14T21:02:04.3227615Z env:
2025-08-14T21:02:04.3227844Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:02:04.3228116Z ##[endgroup]
2025-08-14T21:02:04.4324443Z Syncing repository: pytorch/pytorch
2025-08-14T21:02:04.4325845Z ##[group]Getting Git version info
2025-08-14T21:02:04.4326342Z Working directory is '/home/ec2-user/actions-runner/_work/pytorch/pytorch'
2025-08-14T21:02:04.4327065Z [command]/usr/bin/git version
2025-08-14T21:02:04.4327349Z git version 2.47.1
2025-08-14T21:02:04.4336854Z ##[endgroup]
2025-08-14T21:02:04.4349142Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/64bc8a16-fe07-410d-abe4-64e0589da47c/.gitconfig'
2025-08-14T21:02:04.4369495Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/64bc8a16-fe07-410d-abe4-64e0589da47c' before making global git config changes
2025-08-14T21:02:04.4371400Z Adding repository directory to the temporary git global config as a safe directory
2025-08-14T21:02:04.4375963Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-08-14T21:02:04.4411836Z Deleting the contents of '/home/ec2-user/actions-runner/_work/pytorch/pytorch'
2025-08-14T21:02:04.4415590Z ##[group]Initializing the repository
2025-08-14T21:02:04.4420500Z [command]/usr/bin/git init /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-08-14T21:02:04.4451825Z hint: Using 'master' as the name for the initial branch. This default branch name
2025-08-14T21:02:04.4452922Z hint: is subject to change. To configure the initial branch name to use in all
2025-08-14T21:02:04.4453912Z hint: of your new repositories, which will suppress this warning, call:
2025-08-14T21:02:04.4454687Z hint:
2025-08-14T21:02:04.4455188Z hint: 	git config --global init.defaultBranch <name>
2025-08-14T21:02:04.4455837Z hint:
2025-08-14T21:02:04.4456428Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and
2025-08-14T21:02:04.4457510Z hint: 'development'. The just-created branch can be renamed via this command:
2025-08-14T21:02:04.4458274Z hint:
2025-08-14T21:02:04.4458655Z hint: 	git branch -m <name>
2025-08-14T21:02:04.4459619Z Initialized empty Git repository in /home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/
2025-08-14T21:02:04.4465544Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch
2025-08-14T21:02:04.4492466Z ##[endgroup]
2025-08-14T21:02:04.4493273Z ##[group]Disabling automatic garbage collection
2025-08-14T21:02:04.4497461Z [command]/usr/bin/git config --local gc.auto 0
2025-08-14T21:02:04.4523908Z ##[endgroup]
2025-08-14T21:02:04.4524631Z ##[group]Setting up auth
2025-08-14T21:02:04.4531448Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-08-14T21:02:04.4559033Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :"
2025-08-14T21:02:04.4830832Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-08-14T21:02:04.4855107Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :"
2025-08-14T21:02:04.5111207Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-08-14T21:02:04.5155450Z ##[endgroup]
2025-08-14T21:02:04.5162777Z ##[group]Fetching the repository
2025-08-14T21:02:04.5164014Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/*
2025-08-14T21:02:59.8731065Z From https://github.com/pytorch/pytorch
2025-08-14T21:02:59.8731844Z  * [new branch]              2.6.0.dev20241004+          -> origin/2.6.0.dev20241004+
2025-08-14T21:02:59.8732898Z  * [new branch]              5addvllmbuild               -> origin/5addvllmbuild
2025-08-14T21:02:59.8733555Z  * [new branch]              AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest
2025-08-14T21:02:59.8734275Z  * [new branch]              HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes
2025-08-14T21:02:59.8735045Z  * [new branch]              JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops
2025-08-14T21:02:59.8735804Z  * [new branch]              PR-AOTInductorNoneBug       -> origin/PR-AOTInductorNoneBug
2025-08-14T21:02:59.8737630Z  * [new branch]              PR-AOTInductorNoneBugFix    -> origin/PR-AOTInductorNoneBugFix
2025-08-14T21:02:59.8738599Z  * [new branch]              PR-FixConfigsIssue          -> origin/PR-FixConfigsIssue
2025-08-14T21:02:59.8739872Z  * [new branch]              PR-NoneBugFix-viable        -> origin/PR-NoneBugFix-viable
2025-08-14T21:02:59.8741160Z  * [new branch]              PR-ResetToZero              -> origin/PR-ResetToZero
2025-08-14T21:02:59.8742953Z  * [new branch]              Update-Flash-Packaging      -> origin/Update-Flash-Packaging
2025-08-14T21:02:59.8743754Z  * [new branch]              add-missing-args-normalization -> origin/add-missing-args-normalization
2025-08-14T21:02:59.8744981Z  * [new branch]              add-user-guide-structure    -> origin/add-user-guide-structure
2025-08-14T21:02:59.8746183Z  * [new branch]              addVllmPin                  -> origin/addVllmPin
2025-08-14T21:02:59.8747645Z  * [new branch]              add_windows_testing_back    -> origin/add_windows_testing_back
2025-08-14T21:02:59.8749157Z  * [new branch]              addbuildvllm                -> origin/addbuildvllm
2025-08-14T21:02:59.8751126Z  * [new branch]              addmm-heuristic             -> origin/addmm-heuristic
2025-08-14T21:02:59.8752434Z  * [new branch]              addsimde                    -> origin/addsimde
2025-08-14T21:02:59.8753804Z  * [new branch]              addvllpinnedfile            -> origin/addvllpinnedfile
2025-08-14T21:02:59.8755512Z  * [new branch]              adi/acl_upgrade             -> origin/adi/acl_upgrade
2025-08-14T21:02:59.8756832Z  * [new branch]              adi/skip_slow_tests         -> origin/adi/skip_slow_tests
2025-08-14T21:02:59.8758043Z  * [new branch]              adi/test                    -> origin/adi/test
2025-08-14T21:02:59.8759396Z  * [new branch]              adi/test_bgemm              -> origin/adi/test_bgemm
2025-08-14T21:02:59.8760419Z  * [new branch]              adi/test_fusions            -> origin/adi/test_fusions
2025-08-14T21:02:59.8761705Z  * [new branch]              adi/test_onednn_v3.9        -> origin/adi/test_onednn_v3.9
2025-08-14T21:02:59.8762814Z  * [new branch]              adi/test_presve_change      -> origin/adi/test_presve_change
2025-08-14T21:02:59.8763966Z  * [new branch]              adi/test_timm               -> origin/adi/test_timm
2025-08-14T21:02:59.8765859Z  * [new branch]              adi/testpresve_change       -> origin/adi/testpresve_change
2025-08-14T21:02:59.8768162Z  * [new branch]              aditew01/test/vec_bf16      -> origin/aditew01/test/vec_bf16
2025-08-14T21:02:59.8769178Z  * [new branch]              ah-globalfeedback-hook      -> origin/ah-globalfeedback-hook
2025-08-14T21:02:59.8770690Z  * [new branch]              albanD-patch-1              -> origin/albanD-patch-1
2025-08-14T21:02:59.8771825Z  * [new branch]              alt-disable                 -> origin/alt-disable
2025-08-14T21:02:59.8773758Z  * [new branch]              angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files
2025-08-14T21:02:59.8774892Z  * [new branch]              angelayi/aoti_inductor_fx   -> origin/angelayi/aoti_inductor_fx
2025-08-14T21:02:59.8776212Z  * [new branch]              angelayi/assert_tensor_metadata_device -> origin/angelayi/assert_tensor_metadata_device
2025-08-14T21:02:59.8777231Z  * [new branch]              angelayi/benchmark          -> origin/angelayi/benchmark
2025-08-14T21:02:59.8778556Z  * [new branch]              angelayi/benchmark2         -> origin/angelayi/benchmark2
2025-08-14T21:02:59.8780407Z  * [new branch]              angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization
2025-08-14T21:02:59.8781688Z  * [new branch]              angelayi/cpp_loader         -> origin/angelayi/cpp_loader
2025-08-14T21:02:59.8783738Z  * [new branch]              angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph
2025-08-14T21:02:59.8784869Z  * [new branch]              angelayi/customop           -> origin/angelayi/customop
2025-08-14T21:02:59.8786267Z  * [new branch]              angelayi/del_lib            -> origin/angelayi/del_lib
2025-08-14T21:02:59.8787345Z  * [new branch]              angelayi/docs               -> origin/angelayi/docs
2025-08-14T21:02:59.8788769Z  * [new branch]              angelayi/docs2              -> origin/angelayi/docs2
2025-08-14T21:02:59.8790043Z  * [new branch]              angelayi/fix_pt2            -> origin/angelayi/fix_pt2
2025-08-14T21:02:59.8791687Z  * [new branch]              angelayi/logging.bak        -> origin/angelayi/logging.bak
2025-08-14T21:02:59.8792690Z  * [new branch]              angelayi/logging2           -> origin/angelayi/logging2
2025-08-14T21:02:59.8794038Z  * [new branch]              angelayi/no_so_weight       -> origin/angelayi/no_so_weight
2025-08-14T21:02:59.8795153Z  * [new branch]              angelayi/pytree             -> origin/angelayi/pytree
2025-08-14T21:02:59.8796537Z  * [new branch]              angelayi/save_error         -> origin/angelayi/save_error
2025-08-14T21:02:59.8797848Z  * [new branch]              angelayi/scan_layers        -> origin/angelayi/scan_layers
2025-08-14T21:02:59.8798992Z  * [new branch]              angelayi/symint_input       -> origin/angelayi/symint_input
2025-08-14T21:02:59.8800513Z  * [new branch]              angelayi/tensor_nn_module_meta -> origin/angelayi/tensor_nn_module_meta
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2025-08-14T21:03:00.5024261Z  * [new tag]                 ciflow/inductor-perf-test-nightly-rocm/160538 -> ciflow/inductor-perf-test-nightly-rocm/160538
2025-08-14T21:03:00.5025311Z  * [new tag]                 ciflow/inductor-perf-test-nightly-x86-zen/156599 -> ciflow/inductor-perf-test-nightly-x86-zen/156599
2025-08-14T21:03:00.5026217Z  * [new tag]                 ciflow/inductor-periodic/160406 -> ciflow/inductor-periodic/160406
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2025-08-14T21:03:00.5027588Z  * [new tag]                 ciflow/inductor-rocm/151845 -> ciflow/inductor-rocm/151845
2025-08-14T21:03:00.5028196Z  * [new tag]                 ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158
2025-08-14T21:03:00.5028812Z  * [new tag]                 ciflow/inductor-rocm/160073 -> ciflow/inductor-rocm/160073
2025-08-14T21:03:00.5029420Z  * [new tag]                 ciflow/inductor-rocm/160538 -> ciflow/inductor-rocm/160538
2025-08-14T21:03:00.5030011Z  * [new tag]                 ciflow/inductor/134881      -> ciflow/inductor/134881
2025-08-14T21:03:00.5030513Z  * [new tag]                 ciflow/inductor/137400      -> ciflow/inductor/137400
2025-08-14T21:03:00.5031143Z  * [new tag]                 ciflow/inductor/144516      -> ciflow/inductor/144516
2025-08-14T21:03:00.5031779Z  * [new tag]                 ciflow/inductor/146506      -> ciflow/inductor/146506
2025-08-14T21:03:00.5032312Z  * [new tag]                 ciflow/inductor/147360      -> ciflow/inductor/147360
2025-08-14T21:03:00.5032859Z  * [new tag]                 ciflow/inductor/147990      -> ciflow/inductor/147990
2025-08-14T21:03:00.5033420Z  * [new tag]                 ciflow/inductor/148180      -> ciflow/inductor/148180
2025-08-14T21:03:00.5033923Z  * [new tag]                 ciflow/inductor/148328      -> ciflow/inductor/148328
2025-08-14T21:03:00.5034477Z  * [new tag]                 ciflow/inductor/148484      -> ciflow/inductor/148484
2025-08-14T21:03:00.5034973Z  * [new tag]                 ciflow/inductor/148492      -> ciflow/inductor/148492
2025-08-14T21:03:00.5035536Z  * [new tag]                 ciflow/inductor/150302      -> ciflow/inductor/150302
2025-08-14T21:03:00.5036187Z  * [new tag]                 ciflow/inductor/151845      -> ciflow/inductor/151845
2025-08-14T21:03:00.5036673Z  * [new tag]                 ciflow/inductor/152198      -> ciflow/inductor/152198
2025-08-14T21:03:00.5037268Z  * [new tag]                 ciflow/inductor/152624      -> ciflow/inductor/152624
2025-08-14T21:03:00.5037838Z  * [new tag]                 ciflow/inductor/153966      -> ciflow/inductor/153966
2025-08-14T21:03:00.5038396Z  * [new tag]                 ciflow/inductor/154193      -> ciflow/inductor/154193
2025-08-14T21:03:00.5038887Z  * [new tag]                 ciflow/inductor/154650      -> ciflow/inductor/154650
2025-08-14T21:03:00.5039462Z  * [new tag]                 ciflow/inductor/154694      -> ciflow/inductor/154694
2025-08-14T21:03:00.5040027Z  * [new tag]                 ciflow/inductor/155072      -> ciflow/inductor/155072
2025-08-14T21:03:00.5040590Z  * [new tag]                 ciflow/inductor/155152      -> ciflow/inductor/155152
2025-08-14T21:03:00.5041139Z  * [new tag]                 ciflow/inductor/155153      -> ciflow/inductor/155153
2025-08-14T21:03:00.5041798Z  * [new tag]                 ciflow/inductor/155154      -> ciflow/inductor/155154
2025-08-14T21:03:00.5042497Z  * [new tag]                 ciflow/inductor/155501      -> ciflow/inductor/155501
2025-08-14T21:03:00.5043190Z  * [new tag]                 ciflow/inductor/155502      -> ciflow/inductor/155502
2025-08-14T21:03:00.5043872Z  * [new tag]                 ciflow/inductor/155503      -> ciflow/inductor/155503
2025-08-14T21:03:00.5044694Z  * [new tag]                 ciflow/inductor/155504      -> ciflow/inductor/155504
2025-08-14T21:03:00.5045478Z  * [new tag]                 ciflow/inductor/155557      -> ciflow/inductor/155557
2025-08-14T21:03:00.5046006Z  * [new tag]                 ciflow/inductor/155608      -> ciflow/inductor/155608
2025-08-14T21:03:00.5046709Z  * [new tag]                 ciflow/inductor/155923      -> ciflow/inductor/155923
2025-08-14T21:03:00.5047405Z  * [new tag]                 ciflow/inductor/155928      -> ciflow/inductor/155928
2025-08-14T21:03:00.5048203Z  * [new tag]                 ciflow/inductor/155958      -> ciflow/inductor/155958
2025-08-14T21:03:00.5049482Z  * [new tag]                 ciflow/inductor/156049      -> ciflow/inductor/156049
2025-08-14T21:03:00.5050393Z  * [new tag]                 ciflow/inductor/156851      -> ciflow/inductor/156851
2025-08-14T21:03:00.5051084Z  * [new tag]                 ciflow/inductor/156967      -> ciflow/inductor/156967
2025-08-14T21:03:00.5051711Z  * [new tag]                 ciflow/inductor/157148      -> ciflow/inductor/157148
2025-08-14T21:03:00.5052499Z  * [new tag]                 ciflow/inductor/157149      -> ciflow/inductor/157149
2025-08-14T21:03:00.5053217Z  * [new tag]                 ciflow/inductor/157152      -> ciflow/inductor/157152
2025-08-14T21:03:00.5054169Z  * [new tag]                 ciflow/inductor/157542      -> ciflow/inductor/157542
2025-08-14T21:03:00.5055157Z  * [new tag]                 ciflow/inductor/157572      -> ciflow/inductor/157572
2025-08-14T21:03:00.5056179Z  * [new tag]                 ciflow/inductor/157635      -> ciflow/inductor/157635
2025-08-14T21:03:00.5057121Z  * [new tag]                 ciflow/inductor/157685      -> ciflow/inductor/157685
2025-08-14T21:03:00.5058116Z  * [new tag]                 ciflow/inductor/157686      -> ciflow/inductor/157686
2025-08-14T21:03:00.5059076Z  * [new tag]                 ciflow/inductor/157689      -> ciflow/inductor/157689
2025-08-14T21:03:00.5060066Z  * [new tag]                 ciflow/inductor/157699      -> ciflow/inductor/157699
2025-08-14T21:03:00.5061016Z  * [new tag]                 ciflow/inductor/157743      -> ciflow/inductor/157743
2025-08-14T21:03:00.5062000Z  * [new tag]                 ciflow/inductor/157944      -> ciflow/inductor/157944
2025-08-14T21:03:00.5062995Z  * [new tag]                 ciflow/inductor/157971      -> ciflow/inductor/157971
2025-08-14T21:03:00.5063985Z  * [new tag]                 ciflow/inductor/157994      -> ciflow/inductor/157994
2025-08-14T21:03:00.5065102Z  * [new tag]                 ciflow/inductor/158061      -> ciflow/inductor/158061
2025-08-14T21:03:00.5066074Z  * [new tag]                 ciflow/inductor/158091      -> ciflow/inductor/158091
2025-08-14T21:03:00.5067051Z  * [new tag]                 ciflow/inductor/158097      -> ciflow/inductor/158097
2025-08-14T21:03:00.5068049Z  * [new tag]                 ciflow/inductor/158098      -> ciflow/inductor/158098
2025-08-14T21:03:00.5069012Z  * [new tag]                 ciflow/inductor/158104      -> ciflow/inductor/158104
2025-08-14T21:03:00.5069869Z  * [new tag]                 ciflow/inductor/158168      -> ciflow/inductor/158168
2025-08-14T21:03:00.5070874Z  * [new tag]                 ciflow/inductor/158250      -> ciflow/inductor/158250
2025-08-14T21:03:00.5071970Z  * [new tag]                 ciflow/inductor/158321      -> ciflow/inductor/158321
2025-08-14T21:03:00.5072945Z  * [new tag]                 ciflow/inductor/158609      -> ciflow/inductor/158609
2025-08-14T21:03:00.5073927Z  * [new tag]                 ciflow/inductor/158647      -> ciflow/inductor/158647
2025-08-14T21:03:00.5074822Z  * [new tag]                 ciflow/inductor/158914      -> ciflow/inductor/158914
2025-08-14T21:03:00.5075772Z  * [new tag]                 ciflow/inductor/158932      -> ciflow/inductor/158932
2025-08-14T21:03:00.5076769Z  * [new tag]                 ciflow/inductor/158987      -> ciflow/inductor/158987
2025-08-14T21:03:00.5077751Z  * [new tag]                 ciflow/inductor/159009      -> ciflow/inductor/159009
2025-08-14T21:03:00.5078867Z  * [new tag]                 ciflow/inductor/159010      -> ciflow/inductor/159010
2025-08-14T21:03:00.5079811Z  * [new tag]                 ciflow/inductor/159093      -> ciflow/inductor/159093
2025-08-14T21:03:00.5080780Z  * [new tag]                 ciflow/inductor/159158      -> ciflow/inductor/159158
2025-08-14T21:03:00.5081758Z  * [new tag]                 ciflow/inductor/159197      -> ciflow/inductor/159197
2025-08-14T21:03:00.5082759Z  * [new tag]                 ciflow/inductor/159274      -> ciflow/inductor/159274
2025-08-14T21:03:00.5083698Z  * [new tag]                 ciflow/inductor/159281      -> ciflow/inductor/159281
2025-08-14T21:03:00.5084684Z  * [new tag]                 ciflow/inductor/159329      -> ciflow/inductor/159329
2025-08-14T21:03:00.5085563Z  * [new tag]                 ciflow/inductor/159361      -> ciflow/inductor/159361
2025-08-14T21:03:00.5086494Z  * [new tag]                 ciflow/inductor/159365      -> ciflow/inductor/159365
2025-08-14T21:03:00.5087457Z  * [new tag]                 ciflow/inductor/159366      -> ciflow/inductor/159366
2025-08-14T21:03:00.5088440Z  * [new tag]                 ciflow/inductor/159367      -> ciflow/inductor/159367
2025-08-14T21:03:00.5089352Z  * [new tag]                 ciflow/inductor/159368      -> ciflow/inductor/159368
2025-08-14T21:03:00.5090318Z  * [new tag]                 ciflow/inductor/159473      -> ciflow/inductor/159473
2025-08-14T21:03:00.5091305Z  * [new tag]                 ciflow/inductor/159483      -> ciflow/inductor/159483
2025-08-14T21:03:00.5092263Z  * [new tag]                 ciflow/inductor/159508      -> ciflow/inductor/159508
2025-08-14T21:03:00.5093194Z  * [new tag]                 ciflow/inductor/159523      -> ciflow/inductor/159523
2025-08-14T21:03:00.5094121Z  * [new tag]                 ciflow/inductor/159530      -> ciflow/inductor/159530
2025-08-14T21:03:00.5095096Z  * [new tag]                 ciflow/inductor/159678      -> ciflow/inductor/159678
2025-08-14T21:03:00.5095770Z  * [new tag]                 ciflow/inductor/159691      -> ciflow/inductor/159691
2025-08-14T21:03:00.5096742Z  * [new tag]                 ciflow/inductor/159778      -> ciflow/inductor/159778
2025-08-14T21:03:00.5097693Z  * [new tag]                 ciflow/inductor/159786      -> ciflow/inductor/159786
2025-08-14T21:03:00.5098588Z  * [new tag]                 ciflow/inductor/159817      -> ciflow/inductor/159817
2025-08-14T21:03:00.5099679Z  * [new tag]                 ciflow/inductor/159842      -> ciflow/inductor/159842
2025-08-14T21:03:00.5100627Z  * [new tag]                 ciflow/inductor/159864      -> ciflow/inductor/159864
2025-08-14T21:03:00.5101592Z  * [new tag]                 ciflow/inductor/159865      -> ciflow/inductor/159865
2025-08-14T21:03:00.5102559Z  * [new tag]                 ciflow/inductor/159869      -> ciflow/inductor/159869
2025-08-14T21:03:00.5103511Z  * [new tag]                 ciflow/inductor/159875      -> ciflow/inductor/159875
2025-08-14T21:03:00.5104487Z  * [new tag]                 ciflow/inductor/159889      -> ciflow/inductor/159889
2025-08-14T21:03:00.5105475Z  * [new tag]                 ciflow/inductor/159902      -> ciflow/inductor/159902
2025-08-14T21:03:00.5106411Z  * [new tag]                 ciflow/inductor/159923      -> ciflow/inductor/159923
2025-08-14T21:03:00.5107382Z  * [new tag]                 ciflow/inductor/159944      -> ciflow/inductor/159944
2025-08-14T21:03:00.5108333Z  * [new tag]                 ciflow/inductor/160000      -> ciflow/inductor/160000
2025-08-14T21:03:00.5109452Z  * [new tag]                 ciflow/inductor/160004      -> ciflow/inductor/160004
2025-08-14T21:03:00.5110364Z  * [new tag]                 ciflow/inductor/160080      -> ciflow/inductor/160080
2025-08-14T21:03:00.5111299Z  * [new tag]                 ciflow/inductor/160108      -> ciflow/inductor/160108
2025-08-14T21:03:00.5112291Z  * [new tag]                 ciflow/inductor/160109      -> ciflow/inductor/160109
2025-08-14T21:03:00.5113265Z  * [new tag]                 ciflow/inductor/160111      -> ciflow/inductor/160111
2025-08-14T21:03:00.5114199Z  * [new tag]                 ciflow/inductor/160113      -> ciflow/inductor/160113
2025-08-14T21:03:00.5115162Z  * [new tag]                 ciflow/inductor/160127      -> ciflow/inductor/160127
2025-08-14T21:03:00.5116115Z  * [new tag]                 ciflow/inductor/160131      -> ciflow/inductor/160131
2025-08-14T21:03:00.5117067Z  * [new tag]                 ciflow/inductor/160132      -> ciflow/inductor/160132
2025-08-14T21:03:00.5118047Z  * [new tag]                 ciflow/inductor/160136      -> ciflow/inductor/160136
2025-08-14T21:03:00.5118995Z  * [new tag]                 ciflow/inductor/160138      -> ciflow/inductor/160138
2025-08-14T21:03:00.5119912Z  * [new tag]                 ciflow/inductor/160151      -> ciflow/inductor/160151
2025-08-14T21:03:00.5120752Z  * [new tag]                 ciflow/inductor/160152      -> ciflow/inductor/160152
2025-08-14T21:03:00.5121261Z  * [new tag]                 ciflow/inductor/160154      -> ciflow/inductor/160154
2025-08-14T21:03:00.5121825Z  * [new tag]                 ciflow/inductor/160156      -> ciflow/inductor/160156
2025-08-14T21:03:00.5122325Z  * [new tag]                 ciflow/inductor/160161      -> ciflow/inductor/160161
2025-08-14T21:03:00.5122888Z  * [new tag]                 ciflow/inductor/160166      -> ciflow/inductor/160166
2025-08-14T21:03:00.5123391Z  * [new tag]                 ciflow/inductor/160168      -> ciflow/inductor/160168
2025-08-14T21:03:00.5123954Z  * [new tag]                 ciflow/inductor/160174      -> ciflow/inductor/160174
2025-08-14T21:03:00.5124514Z  * [new tag]                 ciflow/inductor/160181      -> ciflow/inductor/160181
2025-08-14T21:03:00.5125018Z  * [new tag]                 ciflow/inductor/160183      -> ciflow/inductor/160183
2025-08-14T21:03:00.5125577Z  * [new tag]                 ciflow/inductor/160190      -> ciflow/inductor/160190
2025-08-14T21:03:00.5126138Z  * [new tag]                 ciflow/inductor/160198      -> ciflow/inductor/160198
2025-08-14T21:03:00.5126678Z  * [new tag]                 ciflow/inductor/160201      -> ciflow/inductor/160201
2025-08-14T21:03:00.5127212Z  * [new tag]                 ciflow/inductor/160209      -> ciflow/inductor/160209
2025-08-14T21:03:00.5127767Z  * [new tag]                 ciflow/inductor/160218      -> ciflow/inductor/160218
2025-08-14T21:03:00.5128330Z  * [new tag]                 ciflow/inductor/160239      -> ciflow/inductor/160239
2025-08-14T21:03:00.5129014Z  * [new tag]                 ciflow/inductor/160250      -> ciflow/inductor/160250
2025-08-14T21:03:00.5129529Z  * [new tag]                 ciflow/inductor/160253      -> ciflow/inductor/160253
2025-08-14T21:03:00.5130475Z  * [new tag]                 ciflow/inductor/160266      -> ciflow/inductor/160266
2025-08-14T21:03:00.5131450Z  * [new tag]                 ciflow/inductor/160282      -> ciflow/inductor/160282
2025-08-14T21:03:00.5132416Z  * [new tag]                 ciflow/inductor/160298      -> ciflow/inductor/160298
2025-08-14T21:03:00.5133379Z  * [new tag]                 ciflow/inductor/160301      -> ciflow/inductor/160301
2025-08-14T21:03:00.5134356Z  * [new tag]                 ciflow/inductor/160310      -> ciflow/inductor/160310
2025-08-14T21:03:00.5135298Z  * [new tag]                 ciflow/inductor/160323      -> ciflow/inductor/160323
2025-08-14T21:03:00.5136294Z  * [new tag]                 ciflow/inductor/160324      -> ciflow/inductor/160324
2025-08-14T21:03:00.5137245Z  * [new tag]                 ciflow/inductor/160325      -> ciflow/inductor/160325
2025-08-14T21:03:00.5138039Z  * [new tag]                 ciflow/inductor/160326      -> ciflow/inductor/160326
2025-08-14T21:03:00.5138930Z  * [new tag]                 ciflow/inductor/160327      -> ciflow/inductor/160327
2025-08-14T21:03:00.5139903Z  * [new tag]                 ciflow/inductor/160328      -> ciflow/inductor/160328
2025-08-14T21:03:00.5140835Z  * [new tag]                 ciflow/inductor/160329      -> ciflow/inductor/160329
2025-08-14T21:03:00.5141808Z  * [new tag]                 ciflow/inductor/160351      -> ciflow/inductor/160351
2025-08-14T21:03:00.5142870Z  * [new tag]                 ciflow/inductor/160353      -> ciflow/inductor/160353
2025-08-14T21:03:00.5143719Z  * [new tag]                 ciflow/inductor/160362      -> ciflow/inductor/160362
2025-08-14T21:03:00.5144611Z  * [new tag]                 ciflow/inductor/160363      -> ciflow/inductor/160363
2025-08-14T21:03:00.5145429Z  * [new tag]                 ciflow/inductor/160364      -> ciflow/inductor/160364
2025-08-14T21:03:00.5146381Z  * [new tag]                 ciflow/inductor/160365      -> ciflow/inductor/160365
2025-08-14T21:03:00.5147196Z  * [new tag]                 ciflow/inductor/160366      -> ciflow/inductor/160366
2025-08-14T21:03:00.5148141Z  * [new tag]                 ciflow/inductor/160367      -> ciflow/inductor/160367
2025-08-14T21:03:00.5149101Z  * [new tag]                 ciflow/inductor/160368      -> ciflow/inductor/160368
2025-08-14T21:03:00.5150061Z  * [new tag]                 ciflow/inductor/160369      -> ciflow/inductor/160369
2025-08-14T21:03:00.5151026Z  * [new tag]                 ciflow/inductor/160371      -> ciflow/inductor/160371
2025-08-14T21:03:00.5152072Z  * [new tag]                 ciflow/inductor/160374      -> ciflow/inductor/160374
2025-08-14T21:03:00.5152957Z  * [new tag]                 ciflow/inductor/160375      -> ciflow/inductor/160375
2025-08-14T21:03:00.5153915Z  * [new tag]                 ciflow/inductor/160377      -> ciflow/inductor/160377
2025-08-14T21:03:00.5154893Z  * [new tag]                 ciflow/inductor/160380      -> ciflow/inductor/160380
2025-08-14T21:03:00.5155831Z  * [new tag]                 ciflow/inductor/160381      -> ciflow/inductor/160381
2025-08-14T21:03:00.5156714Z  * [new tag]                 ciflow/inductor/160383      -> ciflow/inductor/160383
2025-08-14T21:03:00.5157682Z  * [new tag]                 ciflow/inductor/160394      -> ciflow/inductor/160394
2025-08-14T21:03:00.5158627Z  * [new tag]                 ciflow/inductor/160401      -> ciflow/inductor/160401
2025-08-14T21:03:00.5159584Z  * [new tag]                 ciflow/inductor/160402      -> ciflow/inductor/160402
2025-08-14T21:03:00.5160544Z  * [new tag]                 ciflow/inductor/160403      -> ciflow/inductor/160403
2025-08-14T21:03:00.5161154Z  * [new tag]                 ciflow/inductor/160424      -> ciflow/inductor/160424
2025-08-14T21:03:00.5161927Z  * [new tag]                 ciflow/inductor/160426      -> ciflow/inductor/160426
2025-08-14T21:03:00.5162904Z  * [new tag]                 ciflow/inductor/160431      -> ciflow/inductor/160431
2025-08-14T21:03:00.5163851Z  * [new tag]                 ciflow/inductor/160448      -> ciflow/inductor/160448
2025-08-14T21:03:00.5164722Z  * [new tag]                 ciflow/inductor/160450      -> ciflow/inductor/160450
2025-08-14T21:03:00.5165696Z  * [new tag]                 ciflow/inductor/160455      -> ciflow/inductor/160455
2025-08-14T21:03:00.5166650Z  * [new tag]                 ciflow/inductor/160456      -> ciflow/inductor/160456
2025-08-14T21:03:00.5167563Z  * [new tag]                 ciflow/inductor/160461      -> ciflow/inductor/160461
2025-08-14T21:03:00.5168501Z  * [new tag]                 ciflow/inductor/160462      -> ciflow/inductor/160462
2025-08-14T21:03:00.5169340Z  * [new tag]                 ciflow/inductor/160467      -> ciflow/inductor/160467
2025-08-14T21:03:00.5170310Z  * [new tag]                 ciflow/inductor/160470      -> ciflow/inductor/160470
2025-08-14T21:03:00.5171277Z  * [new tag]                 ciflow/inductor/160473      -> ciflow/inductor/160473
2025-08-14T21:03:00.5172197Z  * [new tag]                 ciflow/inductor/160476      -> ciflow/inductor/160476
2025-08-14T21:03:00.5173162Z  * [new tag]                 ciflow/inductor/160480      -> ciflow/inductor/160480
2025-08-14T21:03:00.5174133Z  * [new tag]                 ciflow/inductor/160481      -> ciflow/inductor/160481
2025-08-14T21:03:00.5175075Z  * [new tag]                 ciflow/inductor/160482      -> ciflow/inductor/160482
2025-08-14T21:03:00.5176154Z  * [new tag]                 ciflow/inductor/160483      -> ciflow/inductor/160483
2025-08-14T21:03:00.5177140Z  * [new tag]                 ciflow/inductor/160485      -> ciflow/inductor/160485
2025-08-14T21:03:00.5178101Z  * [new tag]                 ciflow/inductor/160486      -> ciflow/inductor/160486
2025-08-14T21:03:00.5179060Z  * [new tag]                 ciflow/inductor/160503      -> ciflow/inductor/160503
2025-08-14T21:03:00.5180035Z  * [new tag]                 ciflow/inductor/160510      -> ciflow/inductor/160510
2025-08-14T21:03:00.5180989Z  * [new tag]                 ciflow/inductor/160527      -> ciflow/inductor/160527
2025-08-14T21:03:00.5181969Z  * [new tag]                 ciflow/inductor/160530      -> ciflow/inductor/160530
2025-08-14T21:03:00.5182886Z  * [new tag]                 ciflow/inductor/160531      -> ciflow/inductor/160531
2025-08-14T21:03:00.5183612Z  * [new tag]                 ciflow/inductor/160538      -> ciflow/inductor/160538
2025-08-14T21:03:00.5184118Z  * [new tag]                 ciflow/inductor/160539      -> ciflow/inductor/160539
2025-08-14T21:03:00.5184685Z  * [new tag]                 ciflow/inductor/160540      -> ciflow/inductor/160540
2025-08-14T21:03:00.5185233Z  * [new tag]                 ciflow/inductor/160548      -> ciflow/inductor/160548
2025-08-14T21:03:00.5185737Z  * [new tag]                 ciflow/inductor/160561      -> ciflow/inductor/160561
2025-08-14T21:03:00.5186306Z  * [new tag]                 ciflow/inductor/160576      -> ciflow/inductor/160576
2025-08-14T21:03:00.5186860Z  * [new tag]                 ciflow/inductor/160578      -> ciflow/inductor/160578
2025-08-14T21:03:00.5187429Z  * [new tag]                 ciflow/inductor/160580      -> ciflow/inductor/160580
2025-08-14T21:03:00.5187994Z  * [new tag]                 ciflow/inductor/160583      -> ciflow/inductor/160583
2025-08-14T21:03:00.5188559Z  * [new tag]                 ciflow/inductor/160589      -> ciflow/inductor/160589
2025-08-14T21:03:00.5189090Z  * [new tag]                 ciflow/inductor/160590      -> ciflow/inductor/160590
2025-08-14T21:03:00.5189620Z  * [new tag]                 ciflow/inductor/160592      -> ciflow/inductor/160592
2025-08-14T21:03:00.5190183Z  * [new tag]                 ciflow/inductor/160596      -> ciflow/inductor/160596
2025-08-14T21:03:00.5190683Z  * [new tag]                 ciflow/inductor/160601      -> ciflow/inductor/160601
2025-08-14T21:03:00.5191356Z  * [new tag]                 ciflow/inductor/160607      -> ciflow/inductor/160607
2025-08-14T21:03:00.5191932Z  * [new tag]                 ciflow/inductor/160608      -> ciflow/inductor/160608
2025-08-14T21:03:00.5192504Z  * [new tag]                 ciflow/inductor/160611      -> ciflow/inductor/160611
2025-08-14T21:03:00.5193057Z  * [new tag]                 ciflow/inductor/160614      -> ciflow/inductor/160614
2025-08-14T21:03:00.5193616Z  * [new tag]                 ciflow/inductor/160616      -> ciflow/inductor/160616
2025-08-14T21:03:00.5194116Z  * [new tag]                 ciflow/inductor/160619      -> ciflow/inductor/160619
2025-08-14T21:03:00.5194681Z  * [new tag]                 ciflow/inductor/160625      -> ciflow/inductor/160625
2025-08-14T21:03:00.5195177Z  * [new tag]                 ciflow/inductor/160635      -> ciflow/inductor/160635
2025-08-14T21:03:00.5195770Z  * [new tag]                 ciflow/inductor/160649      -> ciflow/inductor/160649
2025-08-14T21:03:00.5196320Z  * [new tag]                 ciflow/inductor/160658      -> ciflow/inductor/160658
2025-08-14T21:03:00.5196888Z  * [new tag]                 ciflow/inductor/160662      -> ciflow/inductor/160662
2025-08-14T21:03:00.5197380Z  * [new tag]                 ciflow/inductor/160668      -> ciflow/inductor/160668
2025-08-14T21:03:00.5197948Z  * [new tag]                 ciflow/inductor/160669      -> ciflow/inductor/160669
2025-08-14T21:03:00.5198487Z  * [new tag]                 ciflow/inductor/160670      -> ciflow/inductor/160670
2025-08-14T21:03:00.5199049Z  * [new tag]                 ciflow/inductor/160671      -> ciflow/inductor/160671
2025-08-14T21:03:00.5199693Z  * [new tag]                 ciflow/inductor/160677      -> ciflow/inductor/160677
2025-08-14T21:03:00.5200658Z  * [new tag]                 ciflow/inductor/3b9a386     -> ciflow/inductor/3b9a386
2025-08-14T21:03:00.5201655Z  * [new tag]                 ciflow/inductor/3d4b92b     -> ciflow/inductor/3d4b92b
2025-08-14T21:03:00.5202648Z  * [new tag]                 ciflow/inductor/d224ac7     -> ciflow/inductor/d224ac7
2025-08-14T21:03:00.5203626Z  * [new tag]                 ciflow/linux-aarch64/147855 -> ciflow/linux-aarch64/147855
2025-08-14T21:03:00.5204197Z  * [new tag]                 ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994
2025-08-14T21:03:00.5205156Z  * [new tag]                 ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737
2025-08-14T21:03:00.5206149Z  * [new tag]                 ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078
2025-08-14T21:03:00.5207205Z  * [new tag]                 ciflow/linux-aarch64/160299 -> ciflow/linux-aarch64/160299
2025-08-14T21:03:00.5208165Z  * [new tag]                 ciflow/linux-aarch64/160301 -> ciflow/linux-aarch64/160301
2025-08-14T21:03:00.5209294Z  * [new tag]                 ciflow/mps/155923           -> ciflow/mps/155923
2025-08-14T21:03:00.5209930Z  * [new tag]                 ciflow/mps/157553           -> ciflow/mps/157553
2025-08-14T21:03:00.5210404Z  * [new tag]                 ciflow/mps/157635           -> ciflow/mps/157635
2025-08-14T21:03:00.5210865Z  * [new tag]                 ciflow/mps/160541           -> ciflow/mps/160541
2025-08-14T21:03:00.5211332Z  * [new tag]                 ciflow/nightly/156049       -> ciflow/nightly/156049
2025-08-14T21:03:00.5211837Z  * [new tag]                 ciflow/nightly/158104       -> ciflow/nightly/158104
2025-08-14T21:03:00.5212363Z  * [new tag]                 ciflow/op-benchmark/157994  -> ciflow/op-benchmark/157994
2025-08-14T21:03:00.5212983Z  * [new tag]                 ciflow/periodic-rocm-mi300/139971 -> ciflow/periodic-rocm-mi300/139971
2025-08-14T21:03:00.5214092Z  * [new tag]                 ciflow/periodic-rocm-mi300/160073 -> ciflow/periodic-rocm-mi300/160073
2025-08-14T21:03:00.5215172Z  * [new tag]                 ciflow/periodic-rocm-mi300/160538 -> ciflow/periodic-rocm-mi300/160538
2025-08-14T21:03:00.5216186Z  * [new tag]                 ciflow/periodic/054a2fd     -> ciflow/periodic/054a2fd
2025-08-14T21:03:00.5217281Z  * [new tag]                 ciflow/periodic/131296      -> ciflow/periodic/131296
2025-08-14T21:03:00.5218150Z  * [new tag]                 ciflow/periodic/139971      -> ciflow/periodic/139971
2025-08-14T21:03:00.5219070Z  * [new tag]                 ciflow/periodic/143959      -> ciflow/periodic/143959
2025-08-14T21:03:00.5220021Z  * [new tag]                 ciflow/periodic/154595      -> ciflow/periodic/154595
2025-08-14T21:03:00.5220897Z  * [new tag]                 ciflow/periodic/156703      -> ciflow/periodic/156703
2025-08-14T21:03:00.5221829Z  * [new tag]                 ciflow/periodic/160201      -> ciflow/periodic/160201
2025-08-14T21:03:00.5222717Z  * [new tag]                 ciflow/periodic/160424      -> ciflow/periodic/160424
2025-08-14T21:03:00.5223584Z  * [new tag]                 ciflow/periodic/160538      -> ciflow/periodic/160538
2025-08-14T21:03:00.5225136Z  * [new tag]                 ciflow/periodic/1febab2a89302464f6c7d69cfbef7a24c421ea65 -> ciflow/periodic/1febab2a89302464f6c7d69cfbef7a24c421ea65
2025-08-14T21:03:00.5226641Z  * [new tag]                 ciflow/periodic/2a6d37d     -> ciflow/periodic/2a6d37d
2025-08-14T21:03:00.5228206Z  * [new tag]                 ciflow/periodic/2ee22e435131369a7e4f8cc4732579acc29a941b -> ciflow/periodic/2ee22e435131369a7e4f8cc4732579acc29a941b
2025-08-14T21:03:00.5229431Z  * [new tag]                 ciflow/periodic/317eeb8     -> ciflow/periodic/317eeb8
2025-08-14T21:03:00.5230417Z  * [new tag]                 ciflow/periodic/3c32        -> ciflow/periodic/3c32
2025-08-14T21:03:00.5231449Z  * [new tag]                 ciflow/periodic/3e98831     -> ciflow/periodic/3e98831
2025-08-14T21:03:00.5233216Z  * [new tag]                 ciflow/periodic/4a773e1e867f28a8ff0b15203e5cd9548f74fcee -> ciflow/periodic/4a773e1e867f28a8ff0b15203e5cd9548f74fcee
2025-08-14T21:03:00.5235457Z  * [new tag]                 ciflow/periodic/5f5f508aa836a46dfe88857fb223049616b94e93 -> ciflow/periodic/5f5f508aa836a46dfe88857fb223049616b94e93
2025-08-14T21:03:00.5236871Z  * [new tag]                 ciflow/periodic/94512-point -> ciflow/periodic/94512-point
2025-08-14T21:03:00.5237843Z  * [new tag]                 ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519
2025-08-14T21:03:00.5239003Z  * [new tag]                 ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275
2025-08-14T21:03:00.5240054Z  * [new tag]                 ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761
2025-08-14T21:03:00.5241698Z  * [new tag]                 ciflow/periodic/d7114f05b10de8e6de81ffc567d63944c3117d51 -> ciflow/periodic/d7114f05b10de8e6de81ffc567d63944c3117d51
2025-08-14T21:03:00.5243360Z  * [new tag]                 ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12
2025-08-14T21:03:00.5244307Z  * [new tag]                 ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0
2025-08-14T21:03:00.5245323Z  * [new tag]                 ciflow/periodic/sha-ec5b83  -> ciflow/periodic/sha-ec5b83
2025-08-14T21:03:00.5246349Z  * [new tag]                 ciflow/rocm-mi300/151360    -> ciflow/rocm-mi300/151360
2025-08-14T21:03:00.5247278Z  * [new tag]                 ciflow/rocm-mi300/159158    -> ciflow/rocm-mi300/159158
2025-08-14T21:03:00.5248227Z  * [new tag]                 ciflow/rocm-mi300/160073    -> ciflow/rocm-mi300/160073
2025-08-14T21:03:00.5249089Z  * [new tag]                 ciflow/rocm-mi300/160468    -> ciflow/rocm-mi300/160468
2025-08-14T21:03:00.5250044Z  * [new tag]                 ciflow/rocm-mi300/160538    -> ciflow/rocm-mi300/160538
2025-08-14T21:03:00.5250983Z  * [new tag]                 ciflow/rocm-mi355/160215    -> ciflow/rocm-mi355/160215
2025-08-14T21:03:00.5251932Z  * [new tag]                 ciflow/rocm/148492          -> ciflow/rocm/148492
2025-08-14T21:03:00.5252771Z  * [new tag]                 ciflow/rocm/151360          -> ciflow/rocm/151360
2025-08-14T21:03:00.5253652Z  * [new tag]                 ciflow/rocm/151845          -> ciflow/rocm/151845
2025-08-14T21:03:00.5254458Z  * [new tag]                 ciflow/rocm/154864          -> ciflow/rocm/154864
2025-08-14T21:03:00.5255364Z  * [new tag]                 ciflow/rocm/156491          -> ciflow/rocm/156491
2025-08-14T21:03:00.5256236Z  * [new tag]                 ciflow/rocm/158219          -> ciflow/rocm/158219
2025-08-14T21:03:00.5257102Z  * [new tag]                 ciflow/rocm/158220          -> ciflow/rocm/158220
2025-08-14T21:03:00.5257983Z  * [new tag]                 ciflow/rocm/158224          -> ciflow/rocm/158224
2025-08-14T21:03:00.5258840Z  * [new tag]                 ciflow/rocm/159158          -> ciflow/rocm/159158
2025-08-14T21:03:00.5259734Z  * [new tag]                 ciflow/rocm/160215          -> ciflow/rocm/160215
2025-08-14T21:03:00.5260656Z  * [new tag]                 ciflow/rocm/160468          -> ciflow/rocm/160468
2025-08-14T21:03:00.5261527Z  * [new tag]                 ciflow/rocm/160538          -> ciflow/rocm/160538
2025-08-14T21:03:00.5262340Z  * [new tag]                 ciflow/s390/143959          -> ciflow/s390/143959
2025-08-14T21:03:00.5263151Z  * [new tag]                 ciflow/slow/01c7106         -> ciflow/slow/01c7106
2025-08-14T21:03:00.5263998Z  * [new tag]                 ciflow/slow/0577043         -> ciflow/slow/0577043
2025-08-14T21:03:00.5265597Z  * [new tag]                 ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym
2025-08-14T21:03:00.5267208Z  * [new tag]                 ciflow/slow/0e81104         -> ciflow/slow/0e81104
2025-08-14T21:03:00.5268091Z  * [new tag]                 ciflow/slow/154595          -> ciflow/slow/154595
2025-08-14T21:03:00.5269070Z  * [new tag]                 ciflow/slow/1732077         -> ciflow/slow/1732077
2025-08-14T21:03:00.5269986Z  * [new tag]                 ciflow/slow/187eb7c         -> ciflow/slow/187eb7c
2025-08-14T21:03:00.5270897Z  * [new tag]                 ciflow/slow/1faef89         -> ciflow/slow/1faef89
2025-08-14T21:03:00.5271820Z  * [new tag]                 ciflow/slow/3920ec1         -> ciflow/slow/3920ec1
2025-08-14T21:03:00.5272735Z  * [new tag]                 ciflow/slow/3b7c6b2         -> ciflow/slow/3b7c6b2
2025-08-14T21:03:00.5273646Z  * [new tag]                 ciflow/slow/59a3759         -> ciflow/slow/59a3759
2025-08-14T21:03:00.5274533Z  * [new tag]                 ciflow/slow/70ef0bb         -> ciflow/slow/70ef0bb
2025-08-14T21:03:00.5275439Z  * [new tag]                 ciflow/slow/788ff06         -> ciflow/slow/788ff06
2025-08-14T21:03:00.5276966Z  * [new tag]                 ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym
2025-08-14T21:03:00.5278450Z  * [new tag]                 ciflow/slow/9d85864         -> ciflow/slow/9d85864
2025-08-14T21:03:00.5279340Z  * [new tag]                 ciflow/slow/9ffad5b         -> ciflow/slow/9ffad5b
2025-08-14T21:03:00.5280250Z  * [new tag]                 ciflow/slow/a206e8b         -> ciflow/slow/a206e8b
2025-08-14T21:03:00.5281154Z  * [new tag]                 ciflow/slow/a837609         -> ciflow/slow/a837609
2025-08-14T21:03:00.5282037Z  * [new tag]                 ciflow/slow/af841f3         -> ciflow/slow/af841f3
2025-08-14T21:03:00.5283589Z  * [new tag]                 ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym
2025-08-14T21:03:00.5285014Z  * [new tag]                 ciflow/trunk/131296         -> ciflow/trunk/131296
2025-08-14T21:03:00.5285930Z  * [new tag]                 ciflow/trunk/137400         -> ciflow/trunk/137400
2025-08-14T21:03:00.5286801Z  * [new tag]                 ciflow/trunk/138996         -> ciflow/trunk/138996
2025-08-14T21:03:00.5287689Z  * [new tag]                 ciflow/trunk/139971         -> ciflow/trunk/139971
2025-08-14T21:03:00.5288607Z  * [new tag]                 ciflow/trunk/147360         -> ciflow/trunk/147360
2025-08-14T21:03:00.5289530Z  * [new tag]                 ciflow/trunk/147855         -> ciflow/trunk/147855
2025-08-14T21:03:00.5290441Z  * [new tag]                 ciflow/trunk/148180         -> ciflow/trunk/148180
2025-08-14T21:03:00.5291358Z  * [new tag]                 ciflow/trunk/148328         -> ciflow/trunk/148328
2025-08-14T21:03:00.5292269Z  * [new tag]                 ciflow/trunk/148492         -> ciflow/trunk/148492
2025-08-14T21:03:00.5293216Z  * [new tag]                 ciflow/trunk/150282         -> ciflow/trunk/150282
2025-08-14T21:03:00.5294064Z  * [new tag]                 ciflow/trunk/150302         -> ciflow/trunk/150302
2025-08-14T21:03:00.5294947Z  * [new tag]                 ciflow/trunk/151845         -> ciflow/trunk/151845
2025-08-14T21:03:00.5295864Z  * [new tag]                 ciflow/trunk/152624         -> ciflow/trunk/152624
2025-08-14T21:03:00.5296751Z  * [new tag]                 ciflow/trunk/154193         -> ciflow/trunk/154193
2025-08-14T21:03:00.5297655Z  * [new tag]                 ciflow/trunk/154595         -> ciflow/trunk/154595
2025-08-14T21:03:00.5298562Z  * [new tag]                 ciflow/trunk/154650         -> ciflow/trunk/154650
2025-08-14T21:03:00.5299460Z  * [new tag]                 ciflow/trunk/154694         -> ciflow/trunk/154694
2025-08-14T21:03:00.5300298Z  * [new tag]                 ciflow/trunk/155958         -> ciflow/trunk/155958
2025-08-14T21:03:00.5300927Z  * [new tag]                 ciflow/trunk/156049         -> ciflow/trunk/156049
2025-08-14T21:03:00.5301832Z  * [new tag]                 ciflow/trunk/156703         -> ciflow/trunk/156703
2025-08-14T21:03:00.5302713Z  * [new tag]                 ciflow/trunk/156851         -> ciflow/trunk/156851
2025-08-14T21:03:00.5303691Z  * [new tag]                 ciflow/trunk/157148         -> ciflow/trunk/157148
2025-08-14T21:03:00.5304609Z  * [new tag]                 ciflow/trunk/157432         -> ciflow/trunk/157432
2025-08-14T21:03:00.5305513Z  * [new tag]                 ciflow/trunk/157685         -> ciflow/trunk/157685
2025-08-14T21:03:00.5306390Z  * [new tag]                 ciflow/trunk/157689         -> ciflow/trunk/157689
2025-08-14T21:03:00.5307287Z  * [new tag]                 ciflow/trunk/157699         -> ciflow/trunk/157699
2025-08-14T21:03:00.5308178Z  * [new tag]                 ciflow/trunk/157813         -> ciflow/trunk/157813
2025-08-14T21:03:00.5308860Z  * [new tag]                 ciflow/trunk/157994         -> ciflow/trunk/157994
2025-08-14T21:03:00.5309941Z  * [new tag]                 ciflow/trunk/158091         -> ciflow/trunk/158091
2025-08-14T21:03:00.5310595Z  * [new tag]                 ciflow/trunk/158104         -> ciflow/trunk/158104
2025-08-14T21:03:00.5310939Z  * [new tag]                 ciflow/trunk/158219         -> ciflow/trunk/158219
2025-08-14T21:03:00.5311261Z  * [new tag]                 ciflow/trunk/158220         -> ciflow/trunk/158220
2025-08-14T21:03:00.5311670Z  * [new tag]                 ciflow/trunk/158224         -> ciflow/trunk/158224
2025-08-14T21:03:00.5312009Z  * [new tag]                 ciflow/trunk/158529         -> ciflow/trunk/158529
2025-08-14T21:03:00.5312344Z  * [new tag]                 ciflow/trunk/158647         -> ciflow/trunk/158647
2025-08-14T21:03:00.5312679Z  * [new tag]                 ciflow/trunk/158810         -> ciflow/trunk/158810
2025-08-14T21:03:00.5313014Z  * [new tag]                 ciflow/trunk/158812         -> ciflow/trunk/158812
2025-08-14T21:03:00.5313338Z  * [new tag]                 ciflow/trunk/158863         -> ciflow/trunk/158863
2025-08-14T21:03:00.5313616Z  * [new tag]                 ciflow/trunk/158864         -> ciflow/trunk/158864
2025-08-14T21:03:00.5313946Z  * [new tag]                 ciflow/trunk/158883         -> ciflow/trunk/158883
2025-08-14T21:03:00.5314319Z  * [new tag]                 ciflow/trunk/158914         -> ciflow/trunk/158914
2025-08-14T21:03:00.5314649Z  * [new tag]                 ciflow/trunk/158965         -> ciflow/trunk/158965
2025-08-14T21:03:00.5314937Z  * [new tag]                 ciflow/trunk/158987         -> ciflow/trunk/158987
2025-08-14T21:03:00.5315204Z  * [new tag]                 ciflow/trunk/159033         -> ciflow/trunk/159033
2025-08-14T21:03:00.5315767Z  * [new tag]                 ciflow/trunk/159140         -> ciflow/trunk/159140
2025-08-14T21:03:00.5316105Z  * [new tag]                 ciflow/trunk/159158         -> ciflow/trunk/159158
2025-08-14T21:03:00.5316432Z  * [new tag]                 ciflow/trunk/159530         -> ciflow/trunk/159530
2025-08-14T21:03:00.5316767Z  * [new tag]                 ciflow/trunk/159553         -> ciflow/trunk/159553
2025-08-14T21:03:00.5317097Z  * [new tag]                 ciflow/trunk/159562         -> ciflow/trunk/159562
2025-08-14T21:03:00.5317439Z  * [new tag]                 ciflow/trunk/159682         -> ciflow/trunk/159682
2025-08-14T21:03:00.5317761Z  * [new tag]                 ciflow/trunk/159691         -> ciflow/trunk/159691
2025-08-14T21:03:00.5318051Z  * [new tag]                 ciflow/trunk/159842         -> ciflow/trunk/159842
2025-08-14T21:03:00.5318391Z  * [new tag]                 ciflow/trunk/159889         -> ciflow/trunk/159889
2025-08-14T21:03:00.5318733Z  * [new tag]                 ciflow/trunk/159923         -> ciflow/trunk/159923
2025-08-14T21:03:00.5319095Z  * [new tag]                 ciflow/trunk/160000         -> ciflow/trunk/160000
2025-08-14T21:03:00.5319343Z  * [new tag]                 ciflow/trunk/160004         -> ciflow/trunk/160004
2025-08-14T21:03:00.5319529Z  * [new tag]                 ciflow/trunk/160113         -> ciflow/trunk/160113
2025-08-14T21:03:00.5319830Z  * [new tag]                 ciflow/trunk/160161         -> ciflow/trunk/160161
2025-08-14T21:03:00.5320181Z  * [new tag]                 ciflow/trunk/160168         -> ciflow/trunk/160168
2025-08-14T21:03:00.5320627Z  * [new tag]                 ciflow/trunk/160181         -> ciflow/trunk/160181
2025-08-14T21:03:00.5320968Z  * [new tag]                 ciflow/trunk/160183         -> ciflow/trunk/160183
2025-08-14T21:03:00.5321297Z  * [new tag]                 ciflow/trunk/160190         -> ciflow/trunk/160190
2025-08-14T21:03:00.5321611Z  * [new tag]                 ciflow/trunk/160198         -> ciflow/trunk/160198
2025-08-14T21:03:00.5321955Z  * [new tag]                 ciflow/trunk/160205         -> ciflow/trunk/160205
2025-08-14T21:03:00.5322281Z  * [new tag]                 ciflow/trunk/160219         -> ciflow/trunk/160219
2025-08-14T21:03:00.5322612Z  * [new tag]                 ciflow/trunk/160224         -> ciflow/trunk/160224
2025-08-14T21:03:00.5322947Z  * [new tag]                 ciflow/trunk/160250         -> ciflow/trunk/160250
2025-08-14T21:03:00.5323263Z  * [new tag]                 ciflow/trunk/160253         -> ciflow/trunk/160253
2025-08-14T21:03:00.5323600Z  * [new tag]                 ciflow/trunk/160335         -> ciflow/trunk/160335
2025-08-14T21:03:00.5323882Z  * [new tag]                 ciflow/trunk/160338         -> ciflow/trunk/160338
2025-08-14T21:03:00.5324196Z  * [new tag]                 ciflow/trunk/160383         -> ciflow/trunk/160383
2025-08-14T21:03:00.5324526Z  * [new tag]                 ciflow/trunk/160401         -> ciflow/trunk/160401
2025-08-14T21:03:00.5324864Z  * [new tag]                 ciflow/trunk/160403         -> ciflow/trunk/160403
2025-08-14T21:03:00.5325174Z  * [new tag]                 ciflow/trunk/160430         -> ciflow/trunk/160430
2025-08-14T21:03:00.5325524Z  * [new tag]                 ciflow/trunk/160431         -> ciflow/trunk/160431
2025-08-14T21:03:00.5325837Z  * [new tag]                 ciflow/trunk/160439         -> ciflow/trunk/160439
2025-08-14T21:03:00.5326189Z  * [new tag]                 ciflow/trunk/160449         -> ciflow/trunk/160449
2025-08-14T21:03:00.5326490Z  * [new tag]                 ciflow/trunk/160454         -> ciflow/trunk/160454
2025-08-14T21:03:00.5326725Z  * [new tag]                 ciflow/trunk/160468         -> ciflow/trunk/160468
2025-08-14T21:03:00.5327071Z  * [new tag]                 ciflow/trunk/160481         -> ciflow/trunk/160481
2025-08-14T21:03:00.5327385Z  * [new tag]                 ciflow/trunk/160485         -> ciflow/trunk/160485
2025-08-14T21:03:00.5327800Z  * [new tag]                 ciflow/trunk/160519         -> ciflow/trunk/160519
2025-08-14T21:03:00.5328130Z  * [new tag]                 ciflow/trunk/160527         -> ciflow/trunk/160527
2025-08-14T21:03:00.5328456Z  * [new tag]                 ciflow/trunk/160560         -> ciflow/trunk/160560
2025-08-14T21:03:00.5328785Z  * [new tag]                 ciflow/trunk/160578         -> ciflow/trunk/160578
2025-08-14T21:03:00.5329107Z  * [new tag]                 ciflow/trunk/160589         -> ciflow/trunk/160589
2025-08-14T21:03:00.5329425Z  * [new tag]                 ciflow/trunk/160592         -> ciflow/trunk/160592
2025-08-14T21:03:00.5329780Z  * [new tag]                 ciflow/trunk/160649         -> ciflow/trunk/160649
2025-08-14T21:03:00.5330005Z  * [new tag]                 ciflow/trunk/160656         -> ciflow/trunk/160656
2025-08-14T21:03:00.5330200Z  * [new tag]                 ciflow/unstable/123         -> ciflow/unstable/123
2025-08-14T21:03:00.5330367Z  * [new tag]                 ciflow/vllm/160116          -> ciflow/vllm/160116
2025-08-14T21:03:00.5330536Z  * [new tag]                 ciflow/vllm/160583          -> ciflow/vllm/160583
2025-08-14T21:03:00.5330783Z  * [new tag]                 ciflow/vllm/160619          -> ciflow/vllm/160619
2025-08-14T21:03:00.5331069Z  * [new tag]                 ciflow/vllm/160625          -> ciflow/vllm/160625
2025-08-14T21:03:00.5331415Z  * [new tag]                 ciflow/vllm/160627          -> ciflow/vllm/160627
2025-08-14T21:03:00.5331690Z  * [new tag]                 ciflow/win-arm64/156049     -> ciflow/win-arm64/156049
2025-08-14T21:03:00.5331951Z  * [new tag]                 ciflow/win-arm64/158104     -> ciflow/win-arm64/158104
2025-08-14T21:03:00.5332153Z  * [new tag]                 ciflow/win-arm64/159553     -> ciflow/win-arm64/159553
2025-08-14T21:03:00.5332336Z  * [new tag]                 ciflow/win-arm64/159562     -> ciflow/win-arm64/159562
2025-08-14T21:03:00.5332612Z  * [new tag]                 ciflow/win-arm64/159777     -> ciflow/win-arm64/159777
2025-08-14T21:03:00.5332992Z  * [new tag]                 ciflow/win-arm64/159780     -> ciflow/win-arm64/159780
2025-08-14T21:03:00.5333346Z  * [new tag]                 ciflow/win-arm64/159842     -> ciflow/win-arm64/159842
2025-08-14T21:03:00.5333549Z  * [new tag]                 ciflow/win-arm64/160250     -> ciflow/win-arm64/160250
2025-08-14T21:03:00.5333732Z  * [new tag]                 ciflow/win-arm64/160253     -> ciflow/win-arm64/160253
2025-08-14T21:03:00.5333964Z  * [new tag]                 ciflow/win-arm64/160454     -> ciflow/win-arm64/160454
2025-08-14T21:03:00.5334186Z  * [new tag]                 ciflow/win-arm64/160560     -> ciflow/win-arm64/160560
2025-08-14T21:03:00.5334355Z  * [new tag]                 ciflow/xpu/138996           -> ciflow/xpu/138996
2025-08-14T21:03:00.5334536Z  * [new tag]                 ciflow/xpu/139971           -> ciflow/xpu/139971
2025-08-14T21:03:00.5334702Z  * [new tag]                 ciflow/xpu/140972           -> ciflow/xpu/140972
2025-08-14T21:03:00.5334911Z  * [new tag]                 ciflow/xpu/143553           -> ciflow/xpu/143553
2025-08-14T21:03:00.5335115Z  * [new tag]                 ciflow/xpu/156272           -> ciflow/xpu/156272
2025-08-14T21:03:00.5335737Z  * [new tag]                 ciflow/xpu/156812           -> ciflow/xpu/156812
2025-08-14T21:03:00.5336412Z  * [new tag]                 ciflow/xpu/157699           -> ciflow/xpu/157699
2025-08-14T21:03:00.5337117Z  * [new tag]                 ciflow/xpu/157994           -> ciflow/xpu/157994
2025-08-14T21:03:00.5338028Z  * [new tag]                 ciflow/xpu/158336           -> ciflow/xpu/158336
2025-08-14T21:03:00.5338781Z  * [new tag]                 ciflow/xpu/158733           -> ciflow/xpu/158733
2025-08-14T21:03:00.5339487Z  * [new tag]                 ciflow/xpu/159033           -> ciflow/xpu/159033
2025-08-14T21:03:00.5340673Z  * [new tag]                 ciflow/xpu/159118           -> ciflow/xpu/159118
2025-08-14T21:03:00.5341680Z  * [new tag]                 ciflow/xpu/159140           -> ciflow/xpu/159140
2025-08-14T21:03:00.5342827Z  * [new tag]                 ciflow/xpu/159241           -> ciflow/xpu/159241
2025-08-14T21:03:00.5343539Z  * [new tag]                 ciflow/xpu/159473           -> ciflow/xpu/159473
2025-08-14T21:03:00.5344543Z  * [new tag]                 ciflow/xpu/159474           -> ciflow/xpu/159474
2025-08-14T21:03:00.5345442Z  * [new tag]                 ciflow/xpu/159553           -> ciflow/xpu/159553
2025-08-14T21:03:00.5346121Z  * [new tag]                 ciflow/xpu/159944           -> ciflow/xpu/159944
2025-08-14T21:03:00.5347198Z  * [new tag]                 ciflow/xpu/160062           -> ciflow/xpu/160062
2025-08-14T21:03:00.5347912Z  * [new tag]                 ciflow/xpu/160067           -> ciflow/xpu/160067
2025-08-14T21:03:00.5349236Z  * [new tag]                 ciflow/xpu/160158           -> ciflow/xpu/160158
2025-08-14T21:03:00.5349720Z  * [new tag]                 ciflow/xpu/160173           -> ciflow/xpu/160173
2025-08-14T21:03:00.5350638Z  * [new tag]                 ciflow/xpu/160183           -> ciflow/xpu/160183
2025-08-14T21:03:00.5351630Z  * [new tag]                 ciflow/xpu/160301           -> ciflow/xpu/160301
2025-08-14T21:03:00.5352459Z  * [new tag]                 ciflow/xpu/160403           -> ciflow/xpu/160403
2025-08-14T21:03:00.5353397Z  * [new tag]                 ciflow/xpu/160606           -> ciflow/xpu/160606
2025-08-14T21:03:00.5354458Z  * [new tag]                 cslpull75                   -> cslpull75
2025-08-14T21:03:00.5355364Z  * [new tag]                 cslpull76                   -> cslpull76
2025-08-14T21:03:00.5356260Z  * [new tag]                 cslpull77                   -> cslpull77
2025-08-14T21:03:00.5357514Z  * [new tag]                 cslpull78                   -> cslpull78
2025-08-14T21:03:00.5358650Z  * [new tag]                 cslpull79                   -> cslpull79
2025-08-14T21:03:00.5359914Z  * [new tag]                 cslpull80                   -> cslpull80
2025-08-14T21:03:00.5360837Z  * [new tag]                 cslpull81                   -> cslpull81
2025-08-14T21:03:00.5361696Z  * [new tag]                 cslpull82                   -> cslpull82
2025-08-14T21:03:00.5362393Z  * [new tag]                 cslpull83                   -> cslpull83
2025-08-14T21:03:00.5363260Z  * [new tag]                 cslpull84                   -> cslpull84
2025-08-14T21:03:00.5363916Z  * [new tag]                 cslpull85                   -> cslpull85
2025-08-14T21:03:00.5364836Z  * [new tag]                 cslpull86                   -> cslpull86
2025-08-14T21:03:00.5365538Z  * [new tag]                 cslpull87                   -> cslpull87
2025-08-14T21:03:00.5366424Z  * [new tag]                 cslpull88                   -> cslpull88
2025-08-14T21:03:00.5367038Z  * [new tag]                 cslpull89                   -> cslpull89
2025-08-14T21:03:00.5367929Z  * [new tag]                 cslpull90                   -> cslpull90
2025-08-14T21:03:00.5369286Z  * [new tag]                 cslpull91                   -> cslpull91
2025-08-14T21:03:00.5370150Z  * [new tag]                 cslpull92                   -> cslpull92
2025-08-14T21:03:00.5370975Z  * [new tag]                 flight_5                    -> flight_5
2025-08-14T21:03:00.5371832Z  * [new tag]                 flight_5.1                  -> flight_5.1
2025-08-14T21:03:00.5372688Z  * [new tag]                 flight_5.2                  -> flight_5.2
2025-08-14T21:03:00.5373285Z  * [new tag]                 flight_5.3                  -> flight_5.3
2025-08-14T21:03:00.5374136Z  * [new tag]                 forpull1                    -> forpull1
2025-08-14T21:03:00.5375177Z  * [new tag]                 malfet/tag-2ef5611          -> malfet/tag-2ef5611
2025-08-14T21:03:00.5375913Z  * [new tag]                 malfet/tag-317b1a0          -> malfet/tag-317b1a0
2025-08-14T21:03:00.5376803Z  * [new tag]                 malfet/tag-ec6f767          -> malfet/tag-ec6f767
2025-08-14T21:03:00.5377680Z  * [new tag]                 nightly-binary              -> nightly-binary
2025-08-14T21:03:00.5378214Z  * [new tag]                 sqzhang_flight4_plus        -> sqzhang_flight4_plus
2025-08-14T21:03:00.5379176Z  * [new tag]                 sqzhang_flight_3            -> sqzhang_flight_3
2025-08-14T21:03:00.5380374Z  * [new tag]                 trunk/01584d2a7d029c9749eb73678cf1dc313cc35df6 -> trunk/01584d2a7d029c9749eb73678cf1dc313cc35df6
2025-08-14T21:03:00.5381074Z  * [new tag]                 trunk/017259f9c65b6fad55fb9597d7077e2543eaae46 -> trunk/017259f9c65b6fad55fb9597d7077e2543eaae46
2025-08-14T21:03:00.5382204Z  * [new tag]                 trunk/01bcf9a40dea937637d2cdd530bed2652510943d -> trunk/01bcf9a40dea937637d2cdd530bed2652510943d
2025-08-14T21:03:00.5383094Z  * [new tag]                 trunk/01f66d08d93365015f4af005a252f439c4d4013a -> trunk/01f66d08d93365015f4af005a252f439c4d4013a
2025-08-14T21:03:00.5383834Z  * [new tag]                 trunk/03b254e49f2d4c092e6ca712e5702cf2895aa47e -> trunk/03b254e49f2d4c092e6ca712e5702cf2895aa47e
2025-08-14T21:03:00.5384565Z  * [new tag]                 trunk/05029ad1c30865d3f7e7fd13384db9d826e563eb -> trunk/05029ad1c30865d3f7e7fd13384db9d826e563eb
2025-08-14T21:03:00.5385407Z  * [new tag]                 trunk/05c19d1acecc01b0d2512364183058a6885b9869 -> trunk/05c19d1acecc01b0d2512364183058a6885b9869
2025-08-14T21:03:00.5386300Z  * [new tag]                 trunk/05c417715f791875fbf28cfc3fc86142de1a3206 -> trunk/05c417715f791875fbf28cfc3fc86142de1a3206
2025-08-14T21:03:00.5387117Z  * [new tag]                 trunk/06824f3c7268bb807a422b663047cd0900ddd126 -> trunk/06824f3c7268bb807a422b663047cd0900ddd126
2025-08-14T21:03:00.5387847Z  * [new tag]                 trunk/077cb389746a7d61cfc018aad2ba29a8aa195610 -> trunk/077cb389746a7d61cfc018aad2ba29a8aa195610
2025-08-14T21:03:00.5388747Z  * [new tag]                 trunk/089c4a1ba007ed4abb3e5e0eafd97b7584566057 -> trunk/089c4a1ba007ed4abb3e5e0eafd97b7584566057
2025-08-14T21:03:00.5389565Z  * [new tag]                 trunk/09381f5dacda7bbbfa361f5df76bde5cd309adc1 -> trunk/09381f5dacda7bbbfa361f5df76bde5cd309adc1
2025-08-14T21:03:00.5390405Z  * [new tag]                 trunk/0bd3af4fb87445f4de3a1f9b823e399c8b3cefde -> trunk/0bd3af4fb87445f4de3a1f9b823e399c8b3cefde
2025-08-14T21:03:00.5391177Z  * [new tag]                 trunk/0d3461bac0fb5177e35152d980b301ea3a0aa2c4 -> trunk/0d3461bac0fb5177e35152d980b301ea3a0aa2c4
2025-08-14T21:03:00.5392075Z  * [new tag]                 trunk/0d40ff3b496e68193bc16d5391fa2e3623709f81 -> trunk/0d40ff3b496e68193bc16d5391fa2e3623709f81
2025-08-14T21:03:00.5393015Z  * [new tag]                 trunk/0d71ca2c46753bb268bfdcf815c14415c122a289 -> trunk/0d71ca2c46753bb268bfdcf815c14415c122a289
2025-08-14T21:03:00.5393916Z  * [new tag]                 trunk/0d88593dd826544c9e7bd4aa615ef86847a78d2b -> trunk/0d88593dd826544c9e7bd4aa615ef86847a78d2b
2025-08-14T21:03:00.5394732Z  * [new tag]                 trunk/0e3e377bd5126cfcc69d70c4d77b352d3404cc11 -> trunk/0e3e377bd5126cfcc69d70c4d77b352d3404cc11
2025-08-14T21:03:00.5395538Z  * [new tag]                 trunk/0f3b10b8eebe68e3c75d473d499b87dfe14a2eca -> trunk/0f3b10b8eebe68e3c75d473d499b87dfe14a2eca
2025-08-14T21:03:00.5396488Z  * [new tag]                 trunk/101276f81b4d2a8c31bfd6796b986d4c1bfdf483 -> trunk/101276f81b4d2a8c31bfd6796b986d4c1bfdf483
2025-08-14T21:03:00.5397313Z  * [new tag]                 trunk/1028c5e2d50e121865bf98307e7c035f549a24b2 -> trunk/1028c5e2d50e121865bf98307e7c035f549a24b2
2025-08-14T21:03:00.5398155Z  * [new tag]                 trunk/10bc36fe840cb3510fab84d2ea22663b76702f1e -> trunk/10bc36fe840cb3510fab84d2ea22663b76702f1e
2025-08-14T21:03:00.5398931Z  * [new tag]                 trunk/10e3514c962b58cbbee994257872a626ff76d51b -> trunk/10e3514c962b58cbbee994257872a626ff76d51b
2025-08-14T21:03:00.5399745Z  * [new tag]                 trunk/1128f4c2a822cbe34a9d966306af15097179ffe1 -> trunk/1128f4c2a822cbe34a9d966306af15097179ffe1
2025-08-14T21:03:00.5400581Z  * [new tag]                 trunk/114a6c40434bfb9cfa5abc30e9e34d81300d743e -> trunk/114a6c40434bfb9cfa5abc30e9e34d81300d743e
2025-08-14T21:03:00.5401457Z  * [new tag]                 trunk/118bc97b14c24ac88a4b0c0750a9e7bf93154c76 -> trunk/118bc97b14c24ac88a4b0c0750a9e7bf93154c76
2025-08-14T21:03:00.5402187Z  * [new tag]                 trunk/1196bb1c2e4d5a7edc09f2260e3034132f0c6c91 -> trunk/1196bb1c2e4d5a7edc09f2260e3034132f0c6c91
2025-08-14T21:03:00.5402995Z  * [new tag]                 trunk/11a3565f1872bbad9c253a127e8d4ce7a1b40ec8 -> trunk/11a3565f1872bbad9c253a127e8d4ce7a1b40ec8
2025-08-14T21:03:00.5403817Z  * [new tag]                 trunk/15e49f61643e4c0eef420f0981609709ef55b848 -> trunk/15e49f61643e4c0eef420f0981609709ef55b848
2025-08-14T21:03:00.5404658Z  * [new tag]                 trunk/16d15445f8bd8740095b23de4af89d757af793ca -> trunk/16d15445f8bd8740095b23de4af89d757af793ca
2025-08-14T21:03:00.5405476Z  * [new tag]                 trunk/178515d0ff6833c8e9221482b2a650ab31e00019 -> trunk/178515d0ff6833c8e9221482b2a650ab31e00019
2025-08-14T21:03:00.5406317Z  * [new tag]                 trunk/182efe31dbe43376e7eef7338356aaf94d5bcabe -> trunk/182efe31dbe43376e7eef7338356aaf94d5bcabe
2025-08-14T21:03:00.5407120Z  * [new tag]                 trunk/194fcfcfbdad0add1a1b695321e31a576058f4cf -> trunk/194fcfcfbdad0add1a1b695321e31a576058f4cf
2025-08-14T21:03:00.5407932Z  * [new tag]                 trunk/195b5c2e27eb8f21cbc8ad1e90f42db5a8cfccca -> trunk/195b5c2e27eb8f21cbc8ad1e90f42db5a8cfccca
2025-08-14T21:03:00.5408749Z  * [new tag]                 trunk/198b5fd2d47fa3d5110ceba6827a3b18e0064014 -> trunk/198b5fd2d47fa3d5110ceba6827a3b18e0064014
2025-08-14T21:03:00.5409881Z  * [new tag]                 trunk/199e9abb6a366bbd27c39d1da7c3123b4eea9b5a -> trunk/199e9abb6a366bbd27c39d1da7c3123b4eea9b5a
2025-08-14T21:03:00.5410667Z  * [new tag]                 trunk/19b4283884b2d9b3a0eb364da10b1540d14ab7a7 -> trunk/19b4283884b2d9b3a0eb364da10b1540d14ab7a7
2025-08-14T21:03:00.5411762Z  * [new tag]                 trunk/1c2587119152cec3905647a47c65d3d26619c5a8 -> trunk/1c2587119152cec3905647a47c65d3d26619c5a8
2025-08-14T21:03:00.5412518Z  * [new tag]                 trunk/1c26c53851c212a7c90a325549a72f0571613a8c -> trunk/1c26c53851c212a7c90a325549a72f0571613a8c
2025-08-14T21:03:00.5413459Z  * [new tag]                 trunk/1c2cba17eab2b09d87142883da2bdbdbcf018613 -> trunk/1c2cba17eab2b09d87142883da2bdbdbcf018613
2025-08-14T21:03:00.5414890Z  * [new tag]                 trunk/1d80d697a269234b47ec7ede192faf3bb9b159e3 -> trunk/1d80d697a269234b47ec7ede192faf3bb9b159e3
2025-08-14T21:03:00.5415610Z  * [new tag]                 trunk/1ea688f9a2602fbcde32c0302b822526ca4219dc -> trunk/1ea688f9a2602fbcde32c0302b822526ca4219dc
2025-08-14T21:03:00.5416503Z  * [new tag]                 trunk/1f4057c11ac941fb324386ca594d0a6882185aad -> trunk/1f4057c11ac941fb324386ca594d0a6882185aad
2025-08-14T21:03:00.5417362Z  * [new tag]                 trunk/1fc683cf17c8c673044538d10266c00f92987be2 -> trunk/1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:03:00.5418084Z  * [new tag]                 trunk/1febab2a89302464f6c7d69cfbef7a24c421ea65 -> trunk/1febab2a89302464f6c7d69cfbef7a24c421ea65
2025-08-14T21:03:00.5418868Z  * [new tag]                 trunk/206c1eef6571f906c2792d899a09136b3fce9673 -> trunk/206c1eef6571f906c2792d899a09136b3fce9673
2025-08-14T21:03:00.5419800Z  * [new tag]                 trunk/20bdabbb3c5d6b118a94b2e045c777662563d5bb -> trunk/20bdabbb3c5d6b118a94b2e045c777662563d5bb
2025-08-14T21:03:00.5420540Z  * [new tag]                 trunk/21392c0e06ac2b2621950455975ca6332f0bf641 -> trunk/21392c0e06ac2b2621950455975ca6332f0bf641
2025-08-14T21:03:00.5421348Z  * [new tag]                 trunk/2247aa6d1d43e256255f5c74a781c3190a4387b6 -> trunk/2247aa6d1d43e256255f5c74a781c3190a4387b6
2025-08-14T21:03:00.5422028Z  * [new tag]                 trunk/2259dbed4e0d3f2a8174b5847fd0741aed42451d -> trunk/2259dbed4e0d3f2a8174b5847fd0741aed42451d
2025-08-14T21:03:00.5422844Z  * [new tag]                 trunk/231c72240d80091f099c95e326d3600cba866eee -> trunk/231c72240d80091f099c95e326d3600cba866eee
2025-08-14T21:03:00.5423575Z  * [new tag]                 trunk/24257f5bfaa37795f74d9f64c1b43584128d4b8c -> trunk/24257f5bfaa37795f74d9f64c1b43584128d4b8c
2025-08-14T21:03:00.5425011Z  * [new tag]                 trunk/24f43d0da7ad9c6e95a09a2fee610387728cc1cd -> trunk/24f43d0da7ad9c6e95a09a2fee610387728cc1cd
2025-08-14T21:03:00.5425738Z  * [new tag]                 trunk/2898d3f965e5cd9d02fc2ecdab7c580fd457fea9 -> trunk/2898d3f965e5cd9d02fc2ecdab7c580fd457fea9
2025-08-14T21:03:00.5426523Z  * [new tag]                 trunk/28ccc9e7247798980fe00a11bcd64a8016b5f227 -> trunk/28ccc9e7247798980fe00a11bcd64a8016b5f227
2025-08-14T21:03:00.5427377Z  * [new tag]                 trunk/29712314dd5cf500a8ea3d1c69483a3cb768ca72 -> trunk/29712314dd5cf500a8ea3d1c69483a3cb768ca72
2025-08-14T21:03:00.5428166Z  * [new tag]                 trunk/29d20d49f0b7f4e362e1cefdcdc4b5659969312c -> trunk/29d20d49f0b7f4e362e1cefdcdc4b5659969312c
2025-08-14T21:03:00.5429033Z  * [new tag]                 trunk/2c5e10a5fceb208b11c3d569ae02e348b5893b31 -> trunk/2c5e10a5fceb208b11c3d569ae02e348b5893b31
2025-08-14T21:03:00.5429760Z  * [new tag]                 trunk/2d0cdee394bccadcd0abe19dd4623ed978a331ad -> trunk/2d0cdee394bccadcd0abe19dd4623ed978a331ad
2025-08-14T21:03:00.5430517Z  * [new tag]                 trunk/2e4e5ab4be9e0aeffd9c49b5b2f9f820bd0895b1 -> trunk/2e4e5ab4be9e0aeffd9c49b5b2f9f820bd0895b1
2025-08-14T21:03:00.5431508Z  * [new tag]                 trunk/2ea40fba841b3af8103f332ba62e54f350ba9a51 -> trunk/2ea40fba841b3af8103f332ba62e54f350ba9a51
2025-08-14T21:03:00.5432303Z  * [new tag]                 trunk/2ee22e435131369a7e4f8cc4732579acc29a941b -> trunk/2ee22e435131369a7e4f8cc4732579acc29a941b
2025-08-14T21:03:00.5433161Z  * [new tag]                 trunk/2f4c2226175512af787725c4d5ad7313c60d4db1 -> trunk/2f4c2226175512af787725c4d5ad7313c60d4db1
2025-08-14T21:03:00.5433954Z  * [new tag]                 trunk/3008d985a8fc155eb89374afff50cb33a6bd10d5 -> trunk/3008d985a8fc155eb89374afff50cb33a6bd10d5
2025-08-14T21:03:00.5434783Z  * [new tag]                 trunk/3028fa6ce9d9c96671722ab8213a1a30670d7cf2 -> trunk/3028fa6ce9d9c96671722ab8213a1a30670d7cf2
2025-08-14T21:03:00.5435598Z  * [new tag]                 trunk/303c614f3df95ae2b659c5f6c1838b14e4776ce6 -> trunk/303c614f3df95ae2b659c5f6c1838b14e4776ce6
2025-08-14T21:03:00.5436829Z  * [new tag]                 trunk/305fa2239365ad17ac9c534a68bba8a149c42d67 -> trunk/305fa2239365ad17ac9c534a68bba8a149c42d67
2025-08-14T21:03:00.5437531Z  * [new tag]                 trunk/31c9ac4319c0cc2ed8c6be701c6ccf73f6cb4706 -> trunk/31c9ac4319c0cc2ed8c6be701c6ccf73f6cb4706
2025-08-14T21:03:00.5438294Z  * [new tag]                 trunk/32099961d588fc19ead8afe805d6b5108de75669 -> trunk/32099961d588fc19ead8afe805d6b5108de75669
2025-08-14T21:03:00.5439164Z  * [new tag]                 trunk/32e5e2f596d55bb9441d5d53f3c58bcb55828047 -> trunk/32e5e2f596d55bb9441d5d53f3c58bcb55828047
2025-08-14T21:03:00.5439882Z  * [new tag]                 trunk/334b38ccc4427b1d14981c48a3a0b92180d58225 -> trunk/334b38ccc4427b1d14981c48a3a0b92180d58225
2025-08-14T21:03:00.5441012Z  * [new tag]                 trunk/334ecbd4ffe11858cae7d23d1190ddb4777c2513 -> trunk/334ecbd4ffe11858cae7d23d1190ddb4777c2513
2025-08-14T21:03:00.5441744Z  * [new tag]                 trunk/33d94018668951611b318b7515ae96f04e48eac0 -> trunk/33d94018668951611b318b7515ae96f04e48eac0
2025-08-14T21:03:00.5442620Z  * [new tag]                 trunk/34358f335d95213d96b6cca6a83e7bf3af6a9fcb -> trunk/34358f335d95213d96b6cca6a83e7bf3af6a9fcb
2025-08-14T21:03:00.5443423Z  * [new tag]                 trunk/34ec5ed275f8aa875c80daa97b3e82af0b06f673 -> trunk/34ec5ed275f8aa875c80daa97b3e82af0b06f673
2025-08-14T21:03:00.5444204Z  * [new tag]                 trunk/355462e1278d818deb9ef4a184073d5b66074816 -> trunk/355462e1278d818deb9ef4a184073d5b66074816
2025-08-14T21:03:00.5449061Z  * [new tag]                 trunk/3626ba711b34397d1fbf0a9b1979f85cbf68b919 -> trunk/3626ba711b34397d1fbf0a9b1979f85cbf68b919
2025-08-14T21:03:00.5449806Z  * [new tag]                 trunk/36f46d082a4954921cb8493223f000f2aab79ed7 -> trunk/36f46d082a4954921cb8493223f000f2aab79ed7
2025-08-14T21:03:00.5450662Z  * [new tag]                 trunk/39aa3d1471549b7829c207d634dfdc1d26e346a2 -> trunk/39aa3d1471549b7829c207d634dfdc1d26e346a2
2025-08-14T21:03:00.5451759Z  * [new tag]                 trunk/3a562374401113187ce2566b87e3f1d87d7c53aa -> trunk/3a562374401113187ce2566b87e3f1d87d7c53aa
2025-08-14T21:03:00.5452515Z  * [new tag]                 trunk/3ac86e728dfaa7383ff7f865e9e7d33486188dae -> trunk/3ac86e728dfaa7383ff7f865e9e7d33486188dae
2025-08-14T21:03:00.5453280Z  * [new tag]                 trunk/3cec82a7e9aea040a34dd7a2587ae6d3bd65dba0 -> trunk/3cec82a7e9aea040a34dd7a2587ae6d3bd65dba0
2025-08-14T21:03:00.5454144Z  * [new tag]                 trunk/3cf7b4024ef83e44e9ae223dbff7c7ab68240cb2 -> trunk/3cf7b4024ef83e44e9ae223dbff7c7ab68240cb2
2025-08-14T21:03:00.5454958Z  * [new tag]                 trunk/3ef2e1ef769582a82c6ddf150e9d11bf4bf1c44f -> trunk/3ef2e1ef769582a82c6ddf150e9d11bf4bf1c44f
2025-08-14T21:03:00.5455830Z  * [new tag]                 trunk/3f1636ebef9b45e8a3cb0eb20d327ee6acb74be0 -> trunk/3f1636ebef9b45e8a3cb0eb20d327ee6acb74be0
2025-08-14T21:03:00.5456743Z  * [new tag]                 trunk/3faee0a6318afcbbbb48687009a459214910d820 -> trunk/3faee0a6318afcbbbb48687009a459214910d820
2025-08-14T21:03:00.5457491Z  * [new tag]                 trunk/3fcd79e023da7156ac584992ebab29205d3b7881 -> trunk/3fcd79e023da7156ac584992ebab29205d3b7881
2025-08-14T21:03:00.5458378Z  * [new tag]                 trunk/3fe19a7a0af3f4d692af30476c320be18c7e8ae6 -> trunk/3fe19a7a0af3f4d692af30476c320be18c7e8ae6
2025-08-14T21:03:00.5459276Z  * [new tag]                 trunk/41673110cd7c5960824cc74a6fcaeda1a8bc7a23 -> trunk/41673110cd7c5960824cc74a6fcaeda1a8bc7a23
2025-08-14T21:03:00.5460047Z  * [new tag]                 trunk/4183d4ff3dcc1d87400326a9a7998c3f9e966f60 -> trunk/4183d4ff3dcc1d87400326a9a7998c3f9e966f60
2025-08-14T21:03:00.5460839Z  * [new tag]                 trunk/422bd6808bb98cbbac31d157d9c82ad11ba9732d -> trunk/422bd6808bb98cbbac31d157d9c82ad11ba9732d
2025-08-14T21:03:00.5461678Z  * [new tag]                 trunk/42e51cd4b3973a053fcfa80878a3f346fd158e9f -> trunk/42e51cd4b3973a053fcfa80878a3f346fd158e9f
2025-08-14T21:03:00.5462524Z  * [new tag]                 trunk/4416433c7c625127b7f975c92f8ec98ea4c67fd3 -> trunk/4416433c7c625127b7f975c92f8ec98ea4c67fd3
2025-08-14T21:03:00.5463344Z  * [new tag]                 trunk/45ba7ecda876685b083cbbe932450560c566826b -> trunk/45ba7ecda876685b083cbbe932450560c566826b
2025-08-14T21:03:00.5464010Z  * [new tag]                 trunk/4a773e1e867f28a8ff0b15203e5cd9548f74fcee -> trunk/4a773e1e867f28a8ff0b15203e5cd9548f74fcee
2025-08-14T21:03:00.5464828Z  * [new tag]                 trunk/4a90dc0c1f68d1f98832b169f792ed1bb195a0f3 -> trunk/4a90dc0c1f68d1f98832b169f792ed1bb195a0f3
2025-08-14T21:03:00.5465642Z  * [new tag]                 trunk/4cde0acc0e4e795e1a12cbdd9b93c8c04c1fa05d -> trunk/4cde0acc0e4e795e1a12cbdd9b93c8c04c1fa05d
2025-08-14T21:03:00.5466533Z  * [new tag]                 trunk/4d419a74610c32b1372f8802dcc61893740a23cf -> trunk/4d419a74610c32b1372f8802dcc61893740a23cf
2025-08-14T21:03:00.5467387Z  * [new tag]                 trunk/4d5b3f2d5af7c8e4f41da4ffca53fafe8bb86235 -> trunk/4d5b3f2d5af7c8e4f41da4ffca53fafe8bb86235
2025-08-14T21:03:00.5468332Z  * [new tag]                 trunk/4e2ddb5db67617f9f5309c8bba0c17adc84cadbc -> trunk/4e2ddb5db67617f9f5309c8bba0c17adc84cadbc
2025-08-14T21:03:00.5469201Z  * [new tag]                 trunk/50a8c118754a6c5a46968f5c8e215ccba6831d42 -> trunk/50a8c118754a6c5a46968f5c8e215ccba6831d42
2025-08-14T21:03:00.5470043Z  * [new tag]                 trunk/50f23ff6f883db5021dd6bab4c146434f98dd15d -> trunk/50f23ff6f883db5021dd6bab4c146434f98dd15d
2025-08-14T21:03:00.5470937Z  * [new tag]                 trunk/515cb70367e84fcbad23fcc5b39eb1d7706df2aa -> trunk/515cb70367e84fcbad23fcc5b39eb1d7706df2aa
2025-08-14T21:03:00.5471891Z  * [new tag]                 trunk/53e39494958b7e2278cc8176f63636e812e8945f -> trunk/53e39494958b7e2278cc8176f63636e812e8945f
2025-08-14T21:03:00.5473233Z  * [new tag]                 trunk/556e2a73f4f0643f7c2aeb5c7dddda43388a40ce -> trunk/556e2a73f4f0643f7c2aeb5c7dddda43388a40ce
2025-08-14T21:03:00.5473957Z  * [new tag]                 trunk/5665dc9ab76b84d7c90d845ffb0f6349b3621919 -> trunk/5665dc9ab76b84d7c90d845ffb0f6349b3621919
2025-08-14T21:03:00.5474792Z  * [new tag]                 trunk/566c6d52ef1411c8262d7b9cf85e2044fdfbe1a3 -> trunk/566c6d52ef1411c8262d7b9cf85e2044fdfbe1a3
2025-08-14T21:03:00.5475648Z  * [new tag]                 trunk/56c828bef93eada0e18d2cc013207831ca80cc99 -> trunk/56c828bef93eada0e18d2cc013207831ca80cc99
2025-08-14T21:03:00.5476527Z  * [new tag]                 trunk/5737372862253a0ac0292407a5844796f02380ad -> trunk/5737372862253a0ac0292407a5844796f02380ad
2025-08-14T21:03:00.5477357Z  * [new tag]                 trunk/57f738b6357cc8fcdde479a0948e723809a1a44d -> trunk/57f738b6357cc8fcdde479a0948e723809a1a44d
2025-08-14T21:03:00.5478176Z  * [new tag]                 trunk/5a40c5784482255b9baf14086cc4b9349fc6d512 -> trunk/5a40c5784482255b9baf14086cc4b9349fc6d512
2025-08-14T21:03:00.5479024Z  * [new tag]                 trunk/5a9c4cfce42b9eb87da0de40c5633f083115c307 -> trunk/5a9c4cfce42b9eb87da0de40c5633f083115c307
2025-08-14T21:03:00.5479949Z  * [new tag]                 trunk/5ace061254af71aa83d1baae81aa1864c9746add -> trunk/5ace061254af71aa83d1baae81aa1864c9746add
2025-08-14T21:03:00.5480799Z  * [new tag]                 trunk/5dddcd5b07c6644efca8d613f4eca1dc95daa87f -> trunk/5dddcd5b07c6644efca8d613f4eca1dc95daa87f
2025-08-14T21:03:00.5481706Z  * [new tag]                 trunk/5ed4f9177907fe403ec4c4499d0d0e9be6b68fcf -> trunk/5ed4f9177907fe403ec4c4499d0d0e9be6b68fcf
2025-08-14T21:03:00.5482742Z  * [new tag]                 trunk/5f1010fbb3850d99c8fdf9a9de2f79260cdc586a -> trunk/5f1010fbb3850d99c8fdf9a9de2f79260cdc586a
2025-08-14T21:03:00.5483322Z  * [new tag]                 trunk/5f5f508aa836a46dfe88857fb223049616b94e93 -> trunk/5f5f508aa836a46dfe88857fb223049616b94e93
2025-08-14T21:03:00.5484197Z  * [new tag]                 trunk/62bac0798100e0e06a86b7a4cee1788413e3d0ca -> trunk/62bac0798100e0e06a86b7a4cee1788413e3d0ca
2025-08-14T21:03:00.5485117Z  * [new tag]                 trunk/63654ba4c5178fd12220cfc9d1c878af2fdd07cc -> trunk/63654ba4c5178fd12220cfc9d1c878af2fdd07cc
2025-08-14T21:03:00.5485903Z  * [new tag]                 trunk/639778b3ee3b80e0894367fdc4442b58ae1b3a62 -> trunk/639778b3ee3b80e0894367fdc4442b58ae1b3a62
2025-08-14T21:03:00.5486735Z  * [new tag]                 trunk/641ee7478150f26969968f49d8b358e199679a8a -> trunk/641ee7478150f26969968f49d8b358e199679a8a
2025-08-14T21:03:00.5487571Z  * [new tag]                 trunk/65053c03a3d209060cb239d20a229dac37cf9dd1 -> trunk/65053c03a3d209060cb239d20a229dac37cf9dd1
2025-08-14T21:03:00.5488437Z  * [new tag]                 trunk/652a6f5954d039d61dc6e6575ccf89d385d74537 -> trunk/652a6f5954d039d61dc6e6575ccf89d385d74537
2025-08-14T21:03:00.5489305Z  * [new tag]                 trunk/685f15dbea66e8ffa8564752f81ad2f6cb447a14 -> trunk/685f15dbea66e8ffa8564752f81ad2f6cb447a14
2025-08-14T21:03:00.5490008Z  * [new tag]                 trunk/68a4b4b2e336cfd4451ce6546d900568e5ddf96c -> trunk/68a4b4b2e336cfd4451ce6546d900568e5ddf96c
2025-08-14T21:03:00.5490934Z  * [new tag]                 trunk/69a0a9aa7f5e320a02e97fa789d2f72baff1554f -> trunk/69a0a9aa7f5e320a02e97fa789d2f72baff1554f
2025-08-14T21:03:00.5491828Z  * [new tag]                 trunk/6be6d06295c870c77a6eb69f96b3170d983520d5 -> trunk/6be6d06295c870c77a6eb69f96b3170d983520d5
2025-08-14T21:03:00.5492753Z  * [new tag]                 trunk/6c05ea6475beaf3acc05e1bda0f3f8fe3bdc1d49 -> trunk/6c05ea6475beaf3acc05e1bda0f3f8fe3bdc1d49
2025-08-14T21:03:00.5493683Z  * [new tag]                 trunk/6da11d9aafc0d84dc7f66030c181608ff2614f66 -> trunk/6da11d9aafc0d84dc7f66030c181608ff2614f66
2025-08-14T21:03:00.5494598Z  * [new tag]                 trunk/6e8865fbc161270e2ffc52817e6c667df417a3f7 -> trunk/6e8865fbc161270e2ffc52817e6c667df417a3f7
2025-08-14T21:03:00.5495448Z  * [new tag]                 trunk/6ea8376f84232048d6be0f7b2edf82aec1b61d58 -> trunk/6ea8376f84232048d6be0f7b2edf82aec1b61d58
2025-08-14T21:03:00.5496293Z  * [new tag]                 trunk/6ee175195ac7853734d64704171993cc6265eb38 -> trunk/6ee175195ac7853734d64704171993cc6265eb38
2025-08-14T21:03:00.5497172Z  * [new tag]                 trunk/6f0f4e0c3eacd479864319127915f869f64e1935 -> trunk/6f0f4e0c3eacd479864319127915f869f64e1935
2025-08-14T21:03:00.5497930Z  * [new tag]                 trunk/70ccdec44b89e355a2cb03ba14a634284f7750f8 -> trunk/70ccdec44b89e355a2cb03ba14a634284f7750f8
2025-08-14T21:03:00.5499057Z  * [new tag]                 trunk/72009ec6bebca7714f99c18449183787f202af4d -> trunk/72009ec6bebca7714f99c18449183787f202af4d
2025-08-14T21:03:00.5499789Z  * [new tag]                 trunk/731ee31f7b6ba19307daab323f6196172b71aaf8 -> trunk/731ee31f7b6ba19307daab323f6196172b71aaf8
2025-08-14T21:03:00.5500708Z  * [new tag]                 trunk/76a0609b6bddb2bc40f1eb4ade12885023653d59 -> trunk/76a0609b6bddb2bc40f1eb4ade12885023653d59
2025-08-14T21:03:00.5501536Z  * [new tag]                 trunk/781e9a7724c47496e3d38a81e6dd6194cf098c41 -> trunk/781e9a7724c47496e3d38a81e6dd6194cf098c41
2025-08-14T21:03:00.5502273Z  * [new tag]                 trunk/78a2fe1d42edeaa2ef7020b0fa0ac82ee4a640e4 -> trunk/78a2fe1d42edeaa2ef7020b0fa0ac82ee4a640e4
2025-08-14T21:03:00.5503139Z  * [new tag]                 trunk/7a974a88f2c529a614baeabe4debd00fc8a3b299 -> trunk/7a974a88f2c529a614baeabe4debd00fc8a3b299
2025-08-14T21:03:00.5504043Z  * [new tag]                 trunk/7ae0629d64b404e0ef5d9c931433ad25e65d6114 -> trunk/7ae0629d64b404e0ef5d9c931433ad25e65d6114
2025-08-14T21:03:00.5505316Z  * [new tag]                 trunk/7d2ec704e47f4b740cdecda5534b305e8e1875ef -> trunk/7d2ec704e47f4b740cdecda5534b305e8e1875ef
2025-08-14T21:03:00.5506232Z  * [new tag]                 trunk/7d87e358ac8440f666fabbfd99058bb5342be6ac -> trunk/7d87e358ac8440f666fabbfd99058bb5342be6ac
2025-08-14T21:03:00.5506978Z  * [new tag]                 trunk/7e27347fd353928c99620495c8c531a5eba7d56b -> trunk/7e27347fd353928c99620495c8c531a5eba7d56b
2025-08-14T21:03:00.5508316Z  * [new tag]                 trunk/7e91394955721c77645fcdb75a5d47a255d65020 -> trunk/7e91394955721c77645fcdb75a5d47a255d65020
2025-08-14T21:03:00.5509228Z  * [new tag]                 trunk/7f4cb4a3e018a621add2a37a3a2f67b982d51001 -> trunk/7f4cb4a3e018a621add2a37a3a2f67b982d51001
2025-08-14T21:03:00.5510324Z  * [new tag]                 trunk/7fbc22855c17741ae016992803b2e147a13aa22d -> trunk/7fbc22855c17741ae016992803b2e147a13aa22d
2025-08-14T21:03:00.5511250Z  * [new tag]                 trunk/8047421fbb607d70ede13b9cd5a60b7b8bdfe348 -> trunk/8047421fbb607d70ede13b9cd5a60b7b8bdfe348
2025-08-14T21:03:00.5512260Z  * [new tag]                 trunk/8088cfa592504a2897b4c78f8a46fe658ab5c2c2 -> trunk/8088cfa592504a2897b4c78f8a46fe658ab5c2c2
2025-08-14T21:03:00.5513093Z  * [new tag]                 trunk/80cca8307943ba64168208b54028f55b2c71daff -> trunk/80cca8307943ba64168208b54028f55b2c71daff
2025-08-14T21:03:00.5513993Z  * [new tag]                 trunk/8147370733bbdcd034cad54e9212e51885a11892 -> trunk/8147370733bbdcd034cad54e9212e51885a11892
2025-08-14T21:03:00.5514881Z  * [new tag]                 trunk/83875cdb5594ccb3c9206b8eb5745fe1d011cf26 -> trunk/83875cdb5594ccb3c9206b8eb5745fe1d011cf26
2025-08-14T21:03:00.5515694Z  * [new tag]                 trunk/8399cf88ce8399d2be93355f29d4cb69f51c0654 -> trunk/8399cf88ce8399d2be93355f29d4cb69f51c0654
2025-08-14T21:03:00.5516599Z  * [new tag]                 trunk/842cc77ab9aafd518593c2fce077d6abb42a5b7f -> trunk/842cc77ab9aafd518593c2fce077d6abb42a5b7f
2025-08-14T21:03:00.5517518Z  * [new tag]                 trunk/85db508af533649d0b3447ff3f0d5fe083150c84 -> trunk/85db508af533649d0b3447ff3f0d5fe083150c84
2025-08-14T21:03:00.5518235Z  * [new tag]                 trunk/86eb65f7f06016bcd5d7951dc9d74bc3993a827a -> trunk/86eb65f7f06016bcd5d7951dc9d74bc3993a827a
2025-08-14T21:03:00.5519325Z  * [new tag]                 trunk/87e6c4079d8ec7d04aff00ed82096b39836a8367 -> trunk/87e6c4079d8ec7d04aff00ed82096b39836a8367
2025-08-14T21:03:00.5520044Z  * [new tag]                 trunk/89654db1abccf7e5f261989a150db4d1619ea2aa -> trunk/89654db1abccf7e5f261989a150db4d1619ea2aa
2025-08-14T21:03:00.5520772Z  * [new tag]                 trunk/8a37f0c90392a2c38b7c5955471fa49edcaf5cb1 -> trunk/8a37f0c90392a2c38b7c5955471fa49edcaf5cb1
2025-08-14T21:03:00.5521622Z  * [new tag]                 trunk/8ab5868a2199fe485c2d66533b9244ccb97e487d -> trunk/8ab5868a2199fe485c2d66533b9244ccb97e487d
2025-08-14T21:03:00.5522459Z  * [new tag]                 trunk/8ae4d2652f64b8444b3d5314b9232bd2119bcde6 -> trunk/8ae4d2652f64b8444b3d5314b9232bd2119bcde6
2025-08-14T21:03:00.5523266Z  * [new tag]                 trunk/8c41cb800ae0411f02ea5da34bd5ccc3790633b0 -> trunk/8c41cb800ae0411f02ea5da34bd5ccc3790633b0
2025-08-14T21:03:00.5524094Z  * [new tag]                 trunk/8cb91e20bc205b1416648d0ffd98d1ba1f3a6fc4 -> trunk/8cb91e20bc205b1416648d0ffd98d1ba1f3a6fc4
2025-08-14T21:03:00.5524974Z  * [new tag]                 trunk/8cfaf51d4e29c9bd9f49ecc98d955ed53df1a13d -> trunk/8cfaf51d4e29c9bd9f49ecc98d955ed53df1a13d
2025-08-14T21:03:00.5525821Z  * [new tag]                 trunk/8d1cf529229dce7cd5ea04abb0faac83b87ca6d1 -> trunk/8d1cf529229dce7cd5ea04abb0faac83b87ca6d1
2025-08-14T21:03:00.5526660Z  * [new tag]                 trunk/8d3d1c844303cb1d46123a1caa76d4cf83973347 -> trunk/8d3d1c844303cb1d46123a1caa76d4cf83973347
2025-08-14T21:03:00.5527547Z  * [new tag]                 trunk/8d6d3246316e1767a57d5e855acd6208da753b75 -> trunk/8d6d3246316e1767a57d5e855acd6208da753b75
2025-08-14T21:03:00.5528575Z  * [new tag]                 trunk/8e6a3138581152ab827a0997f34c470271399f5e -> trunk/8e6a3138581152ab827a0997f34c470271399f5e
2025-08-14T21:03:00.5529943Z  * [new tag]                 trunk/8eee08d2279b98af2522debb6512d37e837e89e3 -> trunk/8eee08d2279b98af2522debb6512d37e837e89e3
2025-08-14T21:03:00.5530698Z  * [new tag]                 trunk/90b78ee50f73b5c963996076a3d54b74b1b965be -> trunk/90b78ee50f73b5c963996076a3d54b74b1b965be
2025-08-14T21:03:00.5531452Z  * [new tag]                 trunk/94b91a876327820a4bb6f5d39d156f13f2553ab6 -> trunk/94b91a876327820a4bb6f5d39d156f13f2553ab6
2025-08-14T21:03:00.5532736Z  * [new tag]                 trunk/95210cc409dd578988c7116b47725c304dea54c7 -> trunk/95210cc409dd578988c7116b47725c304dea54c7
2025-08-14T21:03:00.5533341Z  * [new tag]                 trunk/96bd33b2de79598566df395f32e27c4d33673f05 -> trunk/96bd33b2de79598566df395f32e27c4d33673f05
2025-08-14T21:03:00.5534291Z  * [new tag]                 trunk/9708fcf92db88b80b9010c68662d634434da3106 -> trunk/9708fcf92db88b80b9010c68662d634434da3106
2025-08-14T21:03:00.5535190Z  * [new tag]                 trunk/97c8c98f8dcb9c5c188b691d156e0043dba6c7f8 -> trunk/97c8c98f8dcb9c5c188b691d156e0043dba6c7f8
2025-08-14T21:03:00.5536085Z  * [new tag]                 trunk/9903ca4f70bdc1653016256f5b4fd74fdfc609f8 -> trunk/9903ca4f70bdc1653016256f5b4fd74fdfc609f8
2025-08-14T21:03:00.5537162Z  * [new tag]                 trunk/99bc2f94c1955657e950ebdad5f77e518785ccbd -> trunk/99bc2f94c1955657e950ebdad5f77e518785ccbd
2025-08-14T21:03:00.5537828Z  * [new tag]                 trunk/9a06e6d0310da9d8a59ae05e8ec9c0201b55cacd -> trunk/9a06e6d0310da9d8a59ae05e8ec9c0201b55cacd
2025-08-14T21:03:00.5538692Z  * [new tag]                 trunk/9a0f7a3bb01b235ea04581ee540970a098071b72 -> trunk/9a0f7a3bb01b235ea04581ee540970a098071b72
2025-08-14T21:03:00.5539616Z  * [new tag]                 trunk/9b803cdbe298009f08340c1aaccb25aafbca95d8 -> trunk/9b803cdbe298009f08340c1aaccb25aafbca95d8
2025-08-14T21:03:00.5540779Z  * [new tag]                 trunk/9ccd0f5e31ea54fcf42101dfbaacc103494e34df -> trunk/9ccd0f5e31ea54fcf42101dfbaacc103494e34df
2025-08-14T21:03:00.5541562Z  * [new tag]                 trunk/9d37c960a4fc44d5ac334ca8bf775f85b95d76fc -> trunk/9d37c960a4fc44d5ac334ca8bf775f85b95d76fc
2025-08-14T21:03:00.5542448Z  * [new tag]                 trunk/9e07673deb212c87b1c6fea23799a97474c476ed -> trunk/9e07673deb212c87b1c6fea23799a97474c476ed
2025-08-14T21:03:00.5543193Z  * [new tag]                 trunk/9eedd2a20b64302d0d116ea2802b50948d2ebb09 -> trunk/9eedd2a20b64302d0d116ea2802b50948d2ebb09
2025-08-14T21:03:00.5544080Z  * [new tag]                 trunk/9fa8ce26cf638504469852cbc3e7d04579fc8674 -> trunk/9fa8ce26cf638504469852cbc3e7d04579fc8674
2025-08-14T21:03:00.5545030Z  * [new tag]                 trunk/a06ec54d40013c97fbffc174ea8f524ea5a95715 -> trunk/a06ec54d40013c97fbffc174ea8f524ea5a95715
2025-08-14T21:03:00.5545930Z  * [new tag]                 trunk/a288b15ea9f87ddd665f249d492e0fb0861f5a69 -> trunk/a288b15ea9f87ddd665f249d492e0fb0861f5a69
2025-08-14T21:03:00.5546782Z  * [new tag]                 trunk/a2fd106d670bb4990cebfd00f25ecbae4145e76c -> trunk/a2fd106d670bb4990cebfd00f25ecbae4145e76c
2025-08-14T21:03:00.5547974Z  * [new tag]                 trunk/a354fa91e26b376d96385a2206c5ff5b42aa4600 -> trunk/a354fa91e26b376d96385a2206c5ff5b42aa4600
2025-08-14T21:03:00.5548659Z  * [new tag]                 trunk/a4f69a5da08eace1c1e6469dec6a18aa842da73b -> trunk/a4f69a5da08eace1c1e6469dec6a18aa842da73b
2025-08-14T21:03:00.5549575Z  * [new tag]                 trunk/a53d14d5f846ac44f6c205abb1c5bc4d2f3126ae -> trunk/a53d14d5f846ac44f6c205abb1c5bc4d2f3126ae
2025-08-14T21:03:00.5550413Z  * [new tag]                 trunk/a5652407e4f3d772fc44486ac2abf756decf0861 -> trunk/a5652407e4f3d772fc44486ac2abf756decf0861
2025-08-14T21:03:00.5551636Z  * [new tag]                 trunk/a7abf57aabec0ce686092e2d66e53ba185dbc56b -> trunk/a7abf57aabec0ce686092e2d66e53ba185dbc56b
2025-08-14T21:03:00.5552389Z  * [new tag]                 trunk/a84b60c0c4016785fd93b7b8a0c04f2d0770d332 -> trunk/a84b60c0c4016785fd93b7b8a0c04f2d0770d332
2025-08-14T21:03:00.5553589Z  * [new tag]                 trunk/aa75e917bdb0f95bb6dee81853c2d3c4ab3e1883 -> trunk/aa75e917bdb0f95bb6dee81853c2d3c4ab3e1883
2025-08-14T21:03:00.5554297Z  * [new tag]                 trunk/adcca7d9a1c053495e99012de801b2ea237faad0 -> trunk/adcca7d9a1c053495e99012de801b2ea237faad0
2025-08-14T21:03:00.5555159Z  * [new tag]                 trunk/af10f1f86cc4effc93142a447693d8be55966615 -> trunk/af10f1f86cc4effc93142a447693d8be55966615
2025-08-14T21:03:00.5556115Z  * [new tag]                 trunk/af3cabc55d5699f4da528e1ca39d83338f84ae8c -> trunk/af3cabc55d5699f4da528e1ca39d83338f84ae8c
2025-08-14T21:03:00.5557010Z  * [new tag]                 trunk/b0df7715e8c590c0001d1f9cdb97057be80c9107 -> trunk/b0df7715e8c590c0001d1f9cdb97057be80c9107
2025-08-14T21:03:00.5558151Z  * [new tag]                 trunk/b149c7204c218e7c4d6594a89dd74f72bd480ec5 -> trunk/b149c7204c218e7c4d6594a89dd74f72bd480ec5
2025-08-14T21:03:00.5558889Z  * [new tag]                 trunk/b1a602762e6a6674b406a3137e7e7a678885a97b -> trunk/b1a602762e6a6674b406a3137e7e7a678885a97b
2025-08-14T21:03:00.5559785Z  * [new tag]                 trunk/b1f43548cad8fc0e30bda250f6e196310fa7a4bc -> trunk/b1f43548cad8fc0e30bda250f6e196310fa7a4bc
2025-08-14T21:03:00.5560661Z  * [new tag]                 trunk/b219ca2a00a305753c4f1ea4c9c5d23243d54753 -> trunk/b219ca2a00a305753c4f1ea4c9c5d23243d54753
2025-08-14T21:03:00.5561528Z  * [new tag]                 trunk/b4596895b9d85a686c2cb978938b0a7797b3690a -> trunk/b4596895b9d85a686c2cb978938b0a7797b3690a
2025-08-14T21:03:00.5562443Z  * [new tag]                 trunk/b5fd7223b1bf44720dc9183bda7dfcf7aeccff02 -> trunk/b5fd7223b1bf44720dc9183bda7dfcf7aeccff02
2025-08-14T21:03:00.5575009Z  * [new tag]                 trunk/b602ea9cab7d43a7ee7b4051227090f23fbd3dbf -> trunk/b602ea9cab7d43a7ee7b4051227090f23fbd3dbf
2025-08-14T21:03:00.5575813Z  * [new tag]                 trunk/b6b74aed604bd2e96389ff99aaaf39abc64fdc64 -> trunk/b6b74aed604bd2e96389ff99aaaf39abc64fdc64
2025-08-14T21:03:00.5576429Z  * [new tag]                 trunk/b7db86600a2614adc71c92ca42d359a7ac534d78 -> trunk/b7db86600a2614adc71c92ca42d359a7ac534d78
2025-08-14T21:03:00.5576888Z  * [new tag]                 trunk/b9003ed3d87699e81e436719625a21996a6654e5 -> trunk/b9003ed3d87699e81e436719625a21996a6654e5
2025-08-14T21:03:00.5577366Z  * [new tag]                 trunk/b90feeac86bda00afc2789321bcd706015ff44e3 -> trunk/b90feeac86bda00afc2789321bcd706015ff44e3
2025-08-14T21:03:00.5577949Z  * [new tag]                 trunk/b9d7de3a094598c3dc0dd52e57bce30eb684c9d8 -> trunk/b9d7de3a094598c3dc0dd52e57bce30eb684c9d8
2025-08-14T21:03:00.5578485Z  * [new tag]                 trunk/ba47821f524eee50a214ed39fa2e7765d54aabf4 -> trunk/ba47821f524eee50a214ed39fa2e7765d54aabf4
2025-08-14T21:03:00.5578887Z  * [new tag]                 trunk/ba4ccf5d67e3d237f435eacc2bce3c6025f08491 -> trunk/ba4ccf5d67e3d237f435eacc2bce3c6025f08491
2025-08-14T21:03:00.5579404Z  * [new tag]                 trunk/bcf23ecc476df2bd7479f142567213e2623308ee -> trunk/bcf23ecc476df2bd7479f142567213e2623308ee
2025-08-14T21:03:00.5579818Z  * [new tag]                 trunk/be53f609aaf6f01e2863f490975ea9eaac3ee9ff -> trunk/be53f609aaf6f01e2863f490975ea9eaac3ee9ff
2025-08-14T21:03:00.5580348Z  * [new tag]                 trunk/beb4d7816dedc67a5de1f82e5a45b5910f407941 -> trunk/beb4d7816dedc67a5de1f82e5a45b5910f407941
2025-08-14T21:03:00.5580789Z  * [new tag]                 trunk/bfc873d02ec413344717493e4175a902921359fd -> trunk/bfc873d02ec413344717493e4175a902921359fd
2025-08-14T21:03:00.5581279Z  * [new tag]                 trunk/c184cb3852f0ff2d16a489d61abc3739c309e6ca -> trunk/c184cb3852f0ff2d16a489d61abc3739c309e6ca
2025-08-14T21:03:00.5581702Z  * [new tag]                 trunk/c24ca7f4bf79f62fd623d76346ca27e53f731431 -> trunk/c24ca7f4bf79f62fd623d76346ca27e53f731431
2025-08-14T21:03:00.5582197Z  * [new tag]                 trunk/c3dc8dc4122977893004c49d10e4676cd0a97da4 -> trunk/c3dc8dc4122977893004c49d10e4676cd0a97da4
2025-08-14T21:03:00.5582670Z  * [new tag]                 trunk/c5ec5458a547f7a774468ea0eb2258d3de596492 -> trunk/c5ec5458a547f7a774468ea0eb2258d3de596492
2025-08-14T21:03:00.5583187Z  * [new tag]                 trunk/c5efc5c8a66eca84865015058b3221013ebfe685 -> trunk/c5efc5c8a66eca84865015058b3221013ebfe685
2025-08-14T21:03:00.5583605Z  * [new tag]                 trunk/c6563341208003f64c131854a9cf029555f786d2 -> trunk/c6563341208003f64c131854a9cf029555f786d2
2025-08-14T21:03:00.5584106Z  * [new tag]                 trunk/c6d78d4dbda53837d298d23a5fbc09af90a42d9e -> trunk/c6d78d4dbda53837d298d23a5fbc09af90a42d9e
2025-08-14T21:03:00.5584522Z  * [new tag]                 trunk/c8205cb35435f39d2c26f6c94b45e4adeb6dcb23 -> trunk/c8205cb35435f39d2c26f6c94b45e4adeb6dcb23
2025-08-14T21:03:00.5585014Z  * [new tag]                 trunk/c859ba7114b1fcb49527e090745fa17091d1f8d5 -> trunk/c859ba7114b1fcb49527e090745fa17091d1f8d5
2025-08-14T21:03:00.5585430Z  * [new tag]                 trunk/c86040a8e68f754b90a84099187d3624954c7f36 -> trunk/c86040a8e68f754b90a84099187d3624954c7f36
2025-08-14T21:03:00.5585928Z  * [new tag]                 trunk/c9671dc865aa0fc1cb86df754e355b44d8e02bb4 -> trunk/c9671dc865aa0fc1cb86df754e355b44d8e02bb4
2025-08-14T21:03:00.5586343Z  * [new tag]                 trunk/ca7315c17162ea21b1ca5ba23f4bf6168766c7b9 -> trunk/ca7315c17162ea21b1ca5ba23f4bf6168766c7b9
2025-08-14T21:03:00.5586853Z  * [new tag]                 trunk/cae2b5e3d223829bdc553fc8601df4b1c1554cff -> trunk/cae2b5e3d223829bdc553fc8601df4b1c1554cff
2025-08-14T21:03:00.5587271Z  * [new tag]                 trunk/cbffde774557752cf20447d42d99ec6102673c31 -> trunk/cbffde774557752cf20447d42d99ec6102673c31
2025-08-14T21:03:00.5588017Z  * [new tag]                 trunk/cd8d8c18f5bafdc1c73d5ac0129e7b4d76ab45bc -> trunk/cd8d8c18f5bafdc1c73d5ac0129e7b4d76ab45bc
2025-08-14T21:03:00.5589350Z  * [new tag]                 trunk/cf0a0dcb0afa5e84b95461cc542f862b51ca96bf -> trunk/cf0a0dcb0afa5e84b95461cc542f862b51ca96bf
2025-08-14T21:03:00.5590165Z  * [new tag]                 trunk/cf4964be68fa9f4ffc334f01cce42d7424b1cc81 -> trunk/cf4964be68fa9f4ffc334f01cce42d7424b1cc81
2025-08-14T21:03:00.5591508Z  * [new tag]                 trunk/d0e2240f680ea2a553f7ee8188f52482e130bfd0 -> trunk/d0e2240f680ea2a553f7ee8188f52482e130bfd0
2025-08-14T21:03:00.5592348Z  * [new tag]                 trunk/d1950d4bb5cba8fb6b23e4d283eea5b9801737e2 -> trunk/d1950d4bb5cba8fb6b23e4d283eea5b9801737e2
2025-08-14T21:03:00.5593197Z  * [new tag]                 trunk/d20c4c20e61adecf00335c4d8c22eb1ace472cd3 -> trunk/d20c4c20e61adecf00335c4d8c22eb1ace472cd3
2025-08-14T21:03:00.5594096Z  * [new tag]                 trunk/d25c4f954d599ea512e2f70cd6df101c21479d4c -> trunk/d25c4f954d599ea512e2f70cd6df101c21479d4c
2025-08-14T21:03:00.5594926Z  * [new tag]                 trunk/d3d359dbafa89173a371e2637f22b47398e94a24 -> trunk/d3d359dbafa89173a371e2637f22b47398e94a24
2025-08-14T21:03:00.5595943Z  * [new tag]                 trunk/d46768db04499d07a5b0db984112a6d1b7d3b0c1 -> trunk/d46768db04499d07a5b0db984112a6d1b7d3b0c1
2025-08-14T21:03:00.5596943Z  * [new tag]                 trunk/d4c1a08c89f37d249a0146ff511c82ecc5c53b8f -> trunk/d4c1a08c89f37d249a0146ff511c82ecc5c53b8f
2025-08-14T21:03:00.5597895Z  * [new tag]                 trunk/d556586448f3caab85673c7da0978fe31c7748f7 -> trunk/d556586448f3caab85673c7da0978fe31c7748f7
2025-08-14T21:03:00.5598874Z  * [new tag]                 trunk/d670304001429a1a833255a918ed788d7ec4989a -> trunk/d670304001429a1a833255a918ed788d7ec4989a
2025-08-14T21:03:00.5599818Z  * [new tag]                 trunk/d6786741a77aba200c78002646cc069b7a1799b0 -> trunk/d6786741a77aba200c78002646cc069b7a1799b0
2025-08-14T21:03:00.5600846Z  * [new tag]                 trunk/d68c323692dedcbb74e670801e3502944fd790ff -> trunk/d68c323692dedcbb74e670801e3502944fd790ff
2025-08-14T21:03:00.5601772Z  * [new tag]                 trunk/d8cb3db5339b45e4b745b2b883ef3ecde9843e2c -> trunk/d8cb3db5339b45e4b745b2b883ef3ecde9843e2c
2025-08-14T21:03:00.5602570Z  * [new tag]                 trunk/da1f608ca33f3062535d0a4866d95db19e72fcbd -> trunk/da1f608ca33f3062535d0a4866d95db19e72fcbd
2025-08-14T21:03:00.5603391Z  * [new tag]                 trunk/db0b7f1cc9bb3fe71aaf8b964a644147ae8e1c35 -> trunk/db0b7f1cc9bb3fe71aaf8b964a644147ae8e1c35
2025-08-14T21:03:00.5604198Z  * [new tag]                 trunk/db32b60662b2f2bdcad980127d5dc4b66b02a7e4 -> trunk/db32b60662b2f2bdcad980127d5dc4b66b02a7e4
2025-08-14T21:03:00.5605067Z  * [new tag]                 trunk/db763b17175553ba09637362eb9773a91997a7ad -> trunk/db763b17175553ba09637362eb9773a91997a7ad
2025-08-14T21:03:00.5605981Z  * [new tag]                 trunk/db78943a1ca13a32a3d6045eb15e2b719ee13a2f -> trunk/db78943a1ca13a32a3d6045eb15e2b719ee13a2f
2025-08-14T21:03:00.5606837Z  * [new tag]                 trunk/dc0d18e023d9b7e314ebba0f234b6cb1579dbcfd -> trunk/dc0d18e023d9b7e314ebba0f234b6cb1579dbcfd
2025-08-14T21:03:00.5607754Z  * [new tag]                 trunk/dd21c8a578038ab2841a7ba809a06921093ac9d8 -> trunk/dd21c8a578038ab2841a7ba809a06921093ac9d8
2025-08-14T21:03:00.5608615Z  * [new tag]                 trunk/deea71a90e05eb320c04bebfead5317746637f0d -> trunk/deea71a90e05eb320c04bebfead5317746637f0d
2025-08-14T21:03:00.5609623Z  * [new tag]                 trunk/df55ec7d4b35f6d21691e9dd41c82f27de762948 -> trunk/df55ec7d4b35f6d21691e9dd41c82f27de762948
2025-08-14T21:03:00.5614042Z  * [new tag]                 trunk/e1cf0d496ea85d1807c8c740f296e77bf7bdc1df -> trunk/e1cf0d496ea85d1807c8c740f296e77bf7bdc1df
2025-08-14T21:03:00.5615070Z  * [new tag]                 trunk/e248719ac03c103767ab72034f6b9fd56855bf98 -> trunk/e248719ac03c103767ab72034f6b9fd56855bf98
2025-08-14T21:03:00.5616021Z  * [new tag]                 trunk/e49762026070f66be41bfa6537fbcf9bfc24e558 -> trunk/e49762026070f66be41bfa6537fbcf9bfc24e558
2025-08-14T21:03:00.5617049Z  * [new tag]                 trunk/e4de93f6a3e342bab34d3757cf90ec0ccc87e168 -> trunk/e4de93f6a3e342bab34d3757cf90ec0ccc87e168
2025-08-14T21:03:00.5617648Z  * [new tag]                 trunk/e619c6bb90b9dedaccd3cbeed86a288993a4e33f -> trunk/e619c6bb90b9dedaccd3cbeed86a288993a4e33f
2025-08-14T21:03:00.5618588Z  * [new tag]                 trunk/e63c2b21c186a7d2ab8a8953b8aa1535f2e96e58 -> trunk/e63c2b21c186a7d2ab8a8953b8aa1535f2e96e58
2025-08-14T21:03:00.5619439Z  * [new tag]                 trunk/e7152ff8a6a929a0db7f3f4a72a5b6d471769cd3 -> trunk/e7152ff8a6a929a0db7f3f4a72a5b6d471769cd3
2025-08-14T21:03:00.5620360Z  * [new tag]                 trunk/e96c7c4bb0f6aeae2ab3b6f040f7d67edbec199a -> trunk/e96c7c4bb0f6aeae2ab3b6f040f7d67edbec199a
2025-08-14T21:03:00.5621291Z  * [new tag]                 trunk/e9eb2096a59a79e7a94c3e28a0715e040369f34c -> trunk/e9eb2096a59a79e7a94c3e28a0715e040369f34c
2025-08-14T21:03:00.5621974Z  * [new tag]                 trunk/eac2d9d695a32dd456050f45cac35134ec3809f4 -> trunk/eac2d9d695a32dd456050f45cac35134ec3809f4
2025-08-14T21:03:00.5622899Z  * [new tag]                 trunk/ecde76c764752540edf9ef62a97936c86d984b17 -> trunk/ecde76c764752540edf9ef62a97936c86d984b17
2025-08-14T21:03:00.5623586Z  * [new tag]                 trunk/ecea81117b2fdc52907c97b3c32d779e07b5d55b -> trunk/ecea81117b2fdc52907c97b3c32d779e07b5d55b
2025-08-14T21:03:00.5624513Z  * [new tag]                 trunk/edaa151d0d5a4e75fbec9843f49cc78770eb61fb -> trunk/edaa151d0d5a4e75fbec9843f49cc78770eb61fb
2025-08-14T21:03:00.5625276Z  * [new tag]                 trunk/ee1b0412b919dfb358d5a697b3be49621497fbc2 -> trunk/ee1b0412b919dfb358d5a697b3be49621497fbc2
2025-08-14T21:03:00.5626075Z  * [new tag]                 trunk/ee1fb43450c2e985657f95a91b68328d6f20f24e -> trunk/ee1fb43450c2e985657f95a91b68328d6f20f24e
2025-08-14T21:03:00.5627319Z  * [new tag]                 trunk/ee89cc7a0acd69de25f98fe4ef828546db7b444c -> trunk/ee89cc7a0acd69de25f98fe4ef828546db7b444c
2025-08-14T21:03:00.5628158Z  * [new tag]                 trunk/ee9f8ba11d664b871a9e0c7933fdc8571635b78c -> trunk/ee9f8ba11d664b871a9e0c7933fdc8571635b78c
2025-08-14T21:03:00.5629215Z  * [new tag]                 trunk/eed9dbf70f43ee529fec78ac00ed9a4fd74c6e76 -> trunk/eed9dbf70f43ee529fec78ac00ed9a4fd74c6e76
2025-08-14T21:03:00.5630142Z  * [new tag]                 trunk/f077c2402e4eb5b0ed562b4ee5b7a0503f26ef94 -> trunk/f077c2402e4eb5b0ed562b4ee5b7a0503f26ef94
2025-08-14T21:03:00.5630966Z  * [new tag]                 trunk/f0980fc0bbd656d6c02d23ad97e945353b314f35 -> trunk/f0980fc0bbd656d6c02d23ad97e945353b314f35
2025-08-14T21:03:00.5631888Z  * [new tag]                 trunk/f15ada5c6fad97a7dcbfa4673f067b6942dda640 -> trunk/f15ada5c6fad97a7dcbfa4673f067b6942dda640
2025-08-14T21:03:00.5632841Z  * [new tag]                 trunk/f27232a2134150cb5e55d26a74d8c36c6a961ca5 -> trunk/f27232a2134150cb5e55d26a74d8c36c6a961ca5
2025-08-14T21:03:00.5633705Z  * [new tag]                 trunk/f33ce40bc062a281e1a1f57e8c1926d0a7d155cc -> trunk/f33ce40bc062a281e1a1f57e8c1926d0a7d155cc
2025-08-14T21:03:00.5634539Z  * [new tag]                 trunk/f341077ce4710172da20cfad916ee37159bfe9fe -> trunk/f341077ce4710172da20cfad916ee37159bfe9fe
2025-08-14T21:03:00.5635551Z  * [new tag]                 trunk/f3a4d742ece08de4cb0e59dcc62e0093a7d0b0c7 -> trunk/f3a4d742ece08de4cb0e59dcc62e0093a7d0b0c7
2025-08-14T21:03:00.5636406Z  * [new tag]                 trunk/f3f159ff8c4bad2edec99c68a941c628e983d04c -> trunk/f3f159ff8c4bad2edec99c68a941c628e983d04c
2025-08-14T21:03:00.5637302Z  * [new tag]                 trunk/f60454cce8b93e5bbf67f2f3c88c8ac01ed65457 -> trunk/f60454cce8b93e5bbf67f2f3c88c8ac01ed65457
2025-08-14T21:03:00.5638101Z  * [new tag]                 trunk/f7b2f3314cf7aede67d5fa5c75e4243208484344 -> trunk/f7b2f3314cf7aede67d5fa5c75e4243208484344
2025-08-14T21:03:00.5639077Z  * [new tag]                 trunk/f8f0414a5983ff481a2188e0c18594150430c8c5 -> trunk/f8f0414a5983ff481a2188e0c18594150430c8c5
2025-08-14T21:03:00.5639915Z  * [new tag]                 trunk/f95b58c2844b3444cd8446fed8570729dc4216eb -> trunk/f95b58c2844b3444cd8446fed8570729dc4216eb
2025-08-14T21:03:00.5640789Z  * [new tag]                 trunk/f990490a23815ea6ee27e487c70ba2cf513ba43d -> trunk/f990490a23815ea6ee27e487c70ba2cf513ba43d
2025-08-14T21:03:00.5641641Z  * [new tag]                 trunk/fb887c3bb588cfe782615e67f6c26db636b8539b -> trunk/fb887c3bb588cfe782615e67f6c26db636b8539b
2025-08-14T21:03:00.5643347Z  * [new tag]                 trunk/fc25c68f20f772290927a7031b998b92615259cf -> trunk/fc25c68f20f772290927a7031b998b92615259cf
2025-08-14T21:03:00.5644213Z  * [new tag]                 trunk/fc80f6859e0ccf66513a40f04b9e735e759d4ddb -> trunk/fc80f6859e0ccf66513a40f04b9e735e759d4ddb
2025-08-14T21:03:00.5645152Z  * [new tag]                 trunk/fdfd69bb05488d76123db9cc1cdd90ac4137bbfb -> trunk/fdfd69bb05488d76123db9cc1cdd90ac4137bbfb
2025-08-14T21:03:00.5646069Z  * [new tag]                 trunk/fe3f5fe4ea2ff6f56406dc5d954636ebb08d0a08 -> trunk/fe3f5fe4ea2ff6f56406dc5d954636ebb08d0a08
2025-08-14T21:03:00.5646908Z  * [new tag]                 trunk/fea7e9dd37c02c334b130f6624af6163fde6b2ab -> trunk/fea7e9dd37c02c334b130f6624af6163fde6b2ab
2025-08-14T21:03:00.5647645Z  * [new tag]                 trunk/ff0d56d03592aa03f3ced8359241d21df1783393 -> trunk/ff0d56d03592aa03f3ced8359241d21df1783393
2025-08-14T21:03:00.5648268Z  * [new tag]                 v0.1.1                      -> v0.1.1
2025-08-14T21:03:00.5649066Z  * [new tag]                 v0.1.10                     -> v0.1.10
2025-08-14T21:03:00.5649935Z  * [new tag]                 v0.1.11                     -> v0.1.11
2025-08-14T21:03:00.5651218Z  * [new tag]                 v0.1.12                     -> v0.1.12
2025-08-14T21:03:00.5651948Z  * [new tag]                 v0.1.2                      -> v0.1.2
2025-08-14T21:03:00.5652711Z  * [new tag]                 v0.1.3                      -> v0.1.3
2025-08-14T21:03:00.5653448Z  * [new tag]                 v0.1.4                      -> v0.1.4
2025-08-14T21:03:00.5654233Z  * [new tag]                 v0.1.5                      -> v0.1.5
2025-08-14T21:03:00.5654951Z  * [new tag]                 v0.1.6                      -> v0.1.6
2025-08-14T21:03:00.5655692Z  * [new tag]                 v0.1.7                      -> v0.1.7
2025-08-14T21:03:00.5656492Z  * [new tag]                 v0.1.8                      -> v0.1.8
2025-08-14T21:03:00.5657869Z  * [new tag]                 v0.1.9                      -> v0.1.9
2025-08-14T21:03:00.5658113Z  * [new tag]                 v0.2.0                      -> v0.2.0
2025-08-14T21:03:00.5658889Z  * [new tag]                 v0.3.0                      -> v0.3.0
2025-08-14T21:03:00.5659819Z  * [new tag]                 v0.3.1                      -> v0.3.1
2025-08-14T21:03:00.5660556Z  * [new tag]                 v0.4.0                      -> v0.4.0
2025-08-14T21:03:00.5661263Z  * [new tag]                 v0.4.1                      -> v0.4.1
2025-08-14T21:03:00.5662070Z  * [new tag]                 v1.0.0                      -> v1.0.0
2025-08-14T21:03:00.5662886Z  * [new tag]                 v1.0.0a0                    -> v1.0.0a0
2025-08-14T21:03:00.5663721Z  * [new tag]                 v1.0.1                      -> v1.0.1
2025-08-14T21:03:00.5664504Z  * [new tag]                 v1.0rc0                     -> v1.0rc0
2025-08-14T21:03:00.5665148Z  * [new tag]                 v1.0rc1                     -> v1.0rc1
2025-08-14T21:03:00.5665957Z  * [new tag]                 v1.1.0                      -> v1.1.0
2025-08-14T21:03:00.5666925Z  * [new tag]                 v1.1.0a0                    -> v1.1.0a0
2025-08-14T21:03:00.5667890Z  * [new tag]                 v1.10.0                     -> v1.10.0
2025-08-14T21:03:00.5668701Z  * [new tag]                 v1.10.0-rc1                 -> v1.10.0-rc1
2025-08-14T21:03:00.5669519Z  * [new tag]                 v1.10.0-rc2                 -> v1.10.0-rc2
2025-08-14T21:03:00.5670178Z  * [new tag]                 v1.10.0-rc3                 -> v1.10.0-rc3
2025-08-14T21:03:00.5671168Z  * [new tag]                 v1.10.1                     -> v1.10.1
2025-08-14T21:03:00.5671616Z  * [new tag]                 v1.10.1-rc1                 -> v1.10.1-rc1
2025-08-14T21:03:00.5672317Z  * [new tag]                 v1.10.2                     -> v1.10.2
2025-08-14T21:03:00.5672981Z  * [new tag]                 v1.10.2-rc1                 -> v1.10.2-rc1
2025-08-14T21:03:00.5673860Z  * [new tag]                 v1.11.0                     -> v1.11.0
2025-08-14T21:03:00.5674738Z  * [new tag]                 v1.11.0-rc1                 -> v1.11.0-rc1
2025-08-14T21:03:00.5675674Z  * [new tag]                 v1.11.0-rc2                 -> v1.11.0-rc2
2025-08-14T21:03:00.5676615Z  * [new tag]                 v1.11.0-rc3                 -> v1.11.0-rc3
2025-08-14T21:03:00.5677428Z  * [new tag]                 v1.11.0-rc4                 -> v1.11.0-rc4
2025-08-14T21:03:00.5678305Z  * [new tag]                 v1.11.0-rc5                 -> v1.11.0-rc5
2025-08-14T21:03:00.5678849Z  * [new tag]                 v1.11.0-rc6                 -> v1.11.0-rc6
2025-08-14T21:03:00.5679562Z  * [new tag]                 v1.11.0-rc7                 -> v1.11.0-rc7
2025-08-14T21:03:00.5680418Z  * [new tag]                 v1.12.0                     -> v1.12.0
2025-08-14T21:03:00.5681269Z  * [new tag]                 v1.12.0-rc1                 -> v1.12.0-rc1
2025-08-14T21:03:00.5682111Z  * [new tag]                 v1.12.0-rc2                 -> v1.12.0-rc2
2025-08-14T21:03:00.5683117Z  * [new tag]                 v1.12.0-rc3                 -> v1.12.0-rc3
2025-08-14T21:03:00.5683934Z  * [new tag]                 v1.12.0-rc4                 -> v1.12.0-rc4
2025-08-14T21:03:00.5684743Z  * [new tag]                 v1.12.0-rc5                 -> v1.12.0-rc5
2025-08-14T21:03:00.5685602Z  * [new tag]                 v1.12.0-rc6                 -> v1.12.0-rc6
2025-08-14T21:03:00.5686335Z  * [new tag]                 v1.12.0-rc7                 -> v1.12.0-rc7
2025-08-14T21:03:00.5686849Z  * [new tag]                 v1.12.0-rc8                 -> v1.12.0-rc8
2025-08-14T21:03:00.5687480Z  * [new tag]                 v1.12.1                     -> v1.12.1
2025-08-14T21:03:00.5688461Z  * [new tag]                 v1.12.1-rc1                 -> v1.12.1-rc1
2025-08-14T21:03:00.5689218Z  * [new tag]                 v1.12.1-rc2                 -> v1.12.1-rc2
2025-08-14T21:03:00.5690285Z  * [new tag]                 v1.12.1-rc3                 -> v1.12.1-rc3
2025-08-14T21:03:00.5690959Z  * [new tag]                 v1.12.1-rc4                 -> v1.12.1-rc4
2025-08-14T21:03:00.5691535Z  * [new tag]                 v1.12.1-rc5                 -> v1.12.1-rc5
2025-08-14T21:03:00.5692545Z  * [new tag]                 v1.13.0                     -> v1.13.0
2025-08-14T21:03:00.5693268Z  * [new tag]                 v1.13.0-rc1                 -> v1.13.0-rc1
2025-08-14T21:03:00.5694062Z  * [new tag]                 v1.13.0-rc2                 -> v1.13.0-rc2
2025-08-14T21:03:00.5694849Z  * [new tag]                 v1.13.0-rc3                 -> v1.13.0-rc3
2025-08-14T21:03:00.5695991Z  * [new tag]                 v1.13.0-rc4                 -> v1.13.0-rc4
2025-08-14T21:03:00.5696571Z  * [new tag]                 v1.13.0-rc5                 -> v1.13.0-rc5
2025-08-14T21:03:00.5697185Z  * [new tag]                 v1.13.0-rc6                 -> v1.13.0-rc6
2025-08-14T21:03:00.5698053Z  * [new tag]                 v1.13.1                     -> v1.13.1
2025-08-14T21:03:00.5698595Z  * [new tag]                 v1.13.1-rc1                 -> v1.13.1-rc1
2025-08-14T21:03:00.5699425Z  * [new tag]                 v1.2.0                      -> v1.2.0
2025-08-14T21:03:00.5700273Z  * [new tag]                 v1.2.0a0                    -> v1.2.0a0
2025-08-14T21:03:00.5701098Z  * [new tag]                 v1.3.0                      -> v1.3.0
2025-08-14T21:03:00.5702303Z  * [new tag]                 v1.3.0a0                    -> v1.3.0a0
2025-08-14T21:03:00.5702833Z  * [new tag]                 v1.3.1                      -> v1.3.1
2025-08-14T21:03:00.5703674Z  * [new tag]                 v1.4.0                      -> v1.4.0
2025-08-14T21:03:00.5704495Z  * [new tag]                 v1.4.0a0                    -> v1.4.0a0
2025-08-14T21:03:00.5705078Z  * [new tag]                 v1.4.1                      -> v1.4.1
2025-08-14T21:03:00.5705972Z  * [new tag]                 v1.5.0                      -> v1.5.0
2025-08-14T21:03:00.5706877Z  * [new tag]                 v1.5.0-rc1                  -> v1.5.0-rc1
2025-08-14T21:03:00.5707704Z  * [new tag]                 v1.5.0-rc2                  -> v1.5.0-rc2
2025-08-14T21:03:00.5708698Z  * [new tag]                 v1.5.0-rc3                  -> v1.5.0-rc3
2025-08-14T21:03:00.5709543Z  * [new tag]                 v1.5.0-rc4                  -> v1.5.0-rc4
2025-08-14T21:03:00.5710313Z  * [new tag]                 v1.5.0-rc5                  -> v1.5.0-rc5
2025-08-14T21:03:00.5711251Z  * [new tag]                 v1.5.1                      -> v1.5.1
2025-08-14T21:03:00.5712025Z  * [new tag]                 v1.5.1-rc1                  -> v1.5.1-rc1
2025-08-14T21:03:00.5712611Z  * [new tag]                 v1.6.0                      -> v1.6.0
2025-08-14T21:03:00.5713482Z  * [new tag]                 v1.6.0-rc1                  -> v1.6.0-rc1
2025-08-14T21:03:00.5714398Z  * [new tag]                 v1.6.0-rc2                  -> v1.6.0-rc2
2025-08-14T21:03:00.5715320Z  * [new tag]                 v1.6.0-rc3                  -> v1.6.0-rc3
2025-08-14T21:03:00.5716034Z  * [new tag]                 v1.6.0-rc4                  -> v1.6.0-rc4
2025-08-14T21:03:00.5716965Z  * [new tag]                 v1.6.0-rc5                  -> v1.6.0-rc5
2025-08-14T21:03:00.5717804Z  * [new tag]                 v1.6.0-rc6                  -> v1.6.0-rc6
2025-08-14T21:03:00.5718574Z  * [new tag]                 v1.6.0-rc7                  -> v1.6.0-rc7
2025-08-14T21:03:00.5719307Z  * [new tag]                 v1.7.0                      -> v1.7.0
2025-08-14T21:03:00.5720290Z  * [new tag]                 v1.7.0-rc1                  -> v1.7.0-rc1
2025-08-14T21:03:00.5721244Z  * [new tag]                 v1.7.0-rc2                  -> v1.7.0-rc2
2025-08-14T21:03:00.5721964Z  * [new tag]                 v1.7.0-rc3                  -> v1.7.0-rc3
2025-08-14T21:03:00.5722641Z  * [new tag]                 v1.7.0-rc4                  -> v1.7.0-rc4
2025-08-14T21:03:00.5723475Z  * [new tag]                 v1.7.1                      -> v1.7.1
2025-08-14T21:03:00.5724673Z  * [new tag]                 v1.7.1-rc1                  -> v1.7.1-rc1
2025-08-14T21:03:00.5725377Z  * [new tag]                 v1.7.1-rc2                  -> v1.7.1-rc2
2025-08-14T21:03:00.5725902Z  * [new tag]                 v1.7.1-rc3                  -> v1.7.1-rc3
2025-08-14T21:03:00.5726853Z  * [new tag]                 v1.8.0                      -> v1.8.0
2025-08-14T21:03:00.5727432Z  * [new tag]                 v1.8.0-rc1                  -> v1.8.0-rc1
2025-08-14T21:03:00.5728289Z  * [new tag]                 v1.8.0-rc2                  -> v1.8.0-rc2
2025-08-14T21:03:00.5729152Z  * [new tag]                 v1.8.0-rc3                  -> v1.8.0-rc3
2025-08-14T21:03:00.5729903Z  * [new tag]                 v1.8.0-rc4                  -> v1.8.0-rc4
2025-08-14T21:03:00.5730611Z  * [new tag]                 v1.8.0-rc5                  -> v1.8.0-rc5
2025-08-14T21:03:00.5731262Z  * [new tag]                 v1.8.1                      -> v1.8.1
2025-08-14T21:03:00.5732072Z  * [new tag]                 v1.8.1-rc1                  -> v1.8.1-rc1
2025-08-14T21:03:00.5732703Z  * [new tag]                 v1.8.1-rc2                  -> v1.8.1-rc2
2025-08-14T21:03:00.5733314Z  * [new tag]                 v1.8.1-rc3                  -> v1.8.1-rc3
2025-08-14T21:03:00.5734887Z  * [new tag]                 v1.8.2                      -> v1.8.2
2025-08-14T21:03:00.5735838Z  * [new tag]                 v1.8.2-rc1                  -> v1.8.2-rc1
2025-08-14T21:03:00.5736656Z  * [new tag]                 v1.9.0                      -> v1.9.0
2025-08-14T21:03:00.5737465Z  * [new tag]                 v1.9.0-rc1                  -> v1.9.0-rc1
2025-08-14T21:03:00.5738479Z  * [new tag]                 v1.9.0-rc2                  -> v1.9.0-rc2
2025-08-14T21:03:00.5739369Z  * [new tag]                 v1.9.0-rc3                  -> v1.9.0-rc3
2025-08-14T21:03:00.5739957Z  * [new tag]                 v1.9.0-rc4                  -> v1.9.0-rc4
2025-08-14T21:03:00.5740779Z  * [new tag]                 v1.9.1                      -> v1.9.1
2025-08-14T21:03:00.5741827Z  * [new tag]                 v1.9.1-rc1                  -> v1.9.1-rc1
2025-08-14T21:03:00.5742356Z  * [new tag]                 v1.9.1-rc2                  -> v1.9.1-rc2
2025-08-14T21:03:00.5743286Z  * [new tag]                 v2.0.0                      -> v2.0.0
2025-08-14T21:03:00.5744031Z  * [new tag]                 v2.0.0-rc1                  -> v2.0.0-rc1
2025-08-14T21:03:00.5744954Z  * [new tag]                 v2.0.0-rc2                  -> v2.0.0-rc2
2025-08-14T21:03:00.5745865Z  * [new tag]                 v2.0.0-rc3                  -> v2.0.0-rc3
2025-08-14T21:03:00.5746743Z  * [new tag]                 v2.0.0-rc4                  -> v2.0.0-rc4
2025-08-14T21:03:00.5747591Z  * [new tag]                 v2.0.0-rc5                  -> v2.0.0-rc5
2025-08-14T21:03:00.5748232Z  * [new tag]                 v2.0.0-rc6                  -> v2.0.0-rc6
2025-08-14T21:03:00.5749175Z  * [new tag]                 v2.0.1                      -> v2.0.1
2025-08-14T21:03:00.5749960Z  * [new tag]                 v2.0.1-rc1                  -> v2.0.1-rc1
2025-08-14T21:03:00.5750567Z  * [new tag]                 v2.0.1-rc2                  -> v2.0.1-rc2
2025-08-14T21:03:00.5751479Z  * [new tag]                 v2.0.1-rc3                  -> v2.0.1-rc3
2025-08-14T21:03:00.5752082Z  * [new tag]                 v2.0.1-rc4                  -> v2.0.1-rc4
2025-08-14T21:03:00.5753534Z  * [new tag]                 v2.1.0                      -> v2.1.0
2025-08-14T21:03:00.5754329Z  * [new tag]                 v2.1.0-rc1                  -> v2.1.0-rc1
2025-08-14T21:03:00.5755663Z  * [new tag]                 v2.1.0-rc2                  -> v2.1.0-rc2
2025-08-14T21:03:00.5756593Z  * [new tag]                 v2.1.0-rc3                  -> v2.1.0-rc3
2025-08-14T21:03:00.5757394Z  * [new tag]                 v2.1.0-rc4                  -> v2.1.0-rc4
2025-08-14T21:03:00.5758336Z  * [new tag]                 v2.1.0-rc5                  -> v2.1.0-rc5
2025-08-14T21:03:00.5759058Z  * [new tag]                 v2.1.0-rc6                  -> v2.1.0-rc6
2025-08-14T21:03:00.5759640Z  * [new tag]                 v2.1.1                      -> v2.1.1
2025-08-14T21:03:00.5760593Z  * [new tag]                 v2.1.1-rc1                  -> v2.1.1-rc1
2025-08-14T21:03:00.5761455Z  * [new tag]                 v2.1.1-rc2                  -> v2.1.1-rc2
2025-08-14T21:03:00.5762463Z  * [new tag]                 v2.1.1-rc3                  -> v2.1.1-rc3
2025-08-14T21:03:00.5763322Z  * [new tag]                 v2.1.1-rc4                  -> v2.1.1-rc4
2025-08-14T21:03:00.5764157Z  * [new tag]                 v2.1.1-rc5                  -> v2.1.1-rc5
2025-08-14T21:03:00.5764814Z  * [new tag]                 v2.1.1-rc6                  -> v2.1.1-rc6
2025-08-14T21:03:00.5765569Z  * [new tag]                 v2.1.2                      -> v2.1.2
2025-08-14T21:03:00.5766568Z  * [new tag]                 v2.1.2-rc1                  -> v2.1.2-rc1
2025-08-14T21:03:00.5767396Z  * [new tag]                 v2.1.2-rc2                  -> v2.1.2-rc2
2025-08-14T21:03:00.5768035Z  * [new tag]                 v2.1.2-rc3                  -> v2.1.2-rc3
2025-08-14T21:03:00.5768857Z  * [new tag]                 v2.2.0                      -> v2.2.0
2025-08-14T21:03:00.5769808Z  * [new tag]                 v2.2.0-rc1                  -> v2.2.0-rc1
2025-08-14T21:03:00.5770520Z  * [new tag]                 v2.2.0-rc2                  -> v2.2.0-rc2
2025-08-14T21:03:00.5771296Z  * [new tag]                 v2.2.0-rc3                  -> v2.2.0-rc3
2025-08-14T21:03:00.5772305Z  * [new tag]                 v2.2.0-rc4                  -> v2.2.0-rc4
2025-08-14T21:03:00.5772911Z  * [new tag]                 v2.2.0-rc5                  -> v2.2.0-rc5
2025-08-14T21:03:00.5773815Z  * [new tag]                 v2.2.0-rc6                  -> v2.2.0-rc6
2025-08-14T21:03:00.5774360Z  * [new tag]                 v2.2.0-rc7                  -> v2.2.0-rc7
2025-08-14T21:03:00.5775088Z  * [new tag]                 v2.2.0-rc8                  -> v2.2.0-rc8
2025-08-14T21:03:00.5775907Z  * [new tag]                 v2.2.1                      -> v2.2.1
2025-08-14T21:03:00.5776864Z  * [new tag]                 v2.2.1-rc1                  -> v2.2.1-rc1
2025-08-14T21:03:00.5777407Z  * [new tag]                 v2.2.1-rc2                  -> v2.2.1-rc2
2025-08-14T21:03:00.5778024Z  * [new tag]                 v2.2.1-rc3                  -> v2.2.1-rc3
2025-08-14T21:03:00.5778691Z  * [new tag]                 v2.2.2                      -> v2.2.2
2025-08-14T21:03:00.5779669Z  * [new tag]                 v2.2.2-rc1                  -> v2.2.2-rc1
2025-08-14T21:03:00.5780343Z  * [new tag]                 v2.2.2-rc2                  -> v2.2.2-rc2
2025-08-14T21:03:00.5780951Z  * [new tag]                 v2.2.2-rc3                  -> v2.2.2-rc3
2025-08-14T21:03:00.5781873Z  * [new tag]                 v2.3.0                      -> v2.3.0
2025-08-14T21:03:00.5782649Z  * [new tag]                 v2.3.0-rc1                  -> v2.3.0-rc1
2025-08-14T21:03:00.5783489Z  * [new tag]                 v2.3.0-rc10                 -> v2.3.0-rc10
2025-08-14T21:03:00.5784552Z  * [new tag]                 v2.3.0-rc11                 -> v2.3.0-rc11
2025-08-14T21:03:00.5784981Z  * [new tag]                 v2.3.0-rc12                 -> v2.3.0-rc12
2025-08-14T21:03:00.5785916Z  * [new tag]                 v2.3.0-rc2                  -> v2.3.0-rc2
2025-08-14T21:03:00.5786724Z  * [new tag]                 v2.3.0-rc3                  -> v2.3.0-rc3
2025-08-14T21:03:00.5787731Z  * [new tag]                 v2.3.0-rc4                  -> v2.3.0-rc4
2025-08-14T21:03:00.5788499Z  * [new tag]                 v2.3.0-rc5                  -> v2.3.0-rc5
2025-08-14T21:03:00.5789112Z  * [new tag]                 v2.3.0-rc6                  -> v2.3.0-rc6
2025-08-14T21:03:00.5790019Z  * [new tag]                 v2.3.0-rc7                  -> v2.3.0-rc7
2025-08-14T21:03:00.5790825Z  * [new tag]                 v2.3.0-rc8                  -> v2.3.0-rc8
2025-08-14T21:03:00.5791609Z  * [new tag]                 v2.3.0-rc9                  -> v2.3.0-rc9
2025-08-14T21:03:00.5792235Z  * [new tag]                 v2.3.1                      -> v2.3.1
2025-08-14T21:03:00.5793174Z  * [new tag]                 v2.3.1-rc1                  -> v2.3.1-rc1
2025-08-14T21:03:00.5793944Z  * [new tag]                 v2.3.1-rc2                  -> v2.3.1-rc2
2025-08-14T21:03:00.5794909Z  * [new tag]                 v2.3.1-rc3                  -> v2.3.1-rc3
2025-08-14T21:03:00.5795661Z  * [new tag]                 v2.4.0                      -> v2.4.0
2025-08-14T21:03:00.5796600Z  * [new tag]                 v2.4.0-rc1                  -> v2.4.0-rc1
2025-08-14T21:03:00.5797337Z  * [new tag]                 v2.4.0-rc2                  -> v2.4.0-rc2
2025-08-14T21:03:00.5798151Z  * [new tag]                 v2.4.0-rc3                  -> v2.4.0-rc3
2025-08-14T21:03:00.5798950Z  * [new tag]                 v2.4.0-rc4                  -> v2.4.0-rc4
2025-08-14T21:03:00.5799949Z  * [new tag]                 v2.4.0-rc5                  -> v2.4.0-rc5
2025-08-14T21:03:00.5800736Z  * [new tag]                 v2.4.0-rc6                  -> v2.4.0-rc6
2025-08-14T21:03:00.5801696Z  * [new tag]                 v2.4.0-rc7                  -> v2.4.0-rc7
2025-08-14T21:03:00.5802390Z  * [new tag]                 v2.4.0-rc8                  -> v2.4.0-rc8
2025-08-14T21:03:00.5803360Z  * [new tag]                 v2.4.0-rc9                  -> v2.4.0-rc9
2025-08-14T21:03:00.5804038Z  * [new tag]                 v2.4.1                      -> v2.4.1
2025-08-14T21:03:00.5804873Z  * [new tag]                 v2.4.1-rc1                  -> v2.4.1-rc1
2025-08-14T21:03:00.5805760Z  * [new tag]                 v2.4.1-rc2                  -> v2.4.1-rc2
2025-08-14T21:03:00.5806702Z  * [new tag]                 v2.4.1-rc3                  -> v2.4.1-rc3
2025-08-14T21:03:00.5808494Z  * [new tag]                 v2.5.0                      -> v2.5.0
2025-08-14T21:03:00.5809468Z  * [new tag]                 v2.5.0-rc1                  -> v2.5.0-rc1
2025-08-14T21:03:00.5810165Z  * [new tag]                 v2.5.0-rc10                 -> v2.5.0-rc10
2025-08-14T21:03:00.5811062Z  * [new tag]                 v2.5.0-rc2                  -> v2.5.0-rc2
2025-08-14T21:03:00.5811908Z  * [new tag]                 v2.5.0-rc3                  -> v2.5.0-rc3
2025-08-14T21:03:00.5812749Z  * [new tag]                 v2.5.0-rc4                  -> v2.5.0-rc4
2025-08-14T21:03:00.5813629Z  * [new tag]                 v2.5.0-rc5                  -> v2.5.0-rc5
2025-08-14T21:03:00.5814633Z  * [new tag]                 v2.5.0-rc6                  -> v2.5.0-rc6
2025-08-14T21:03:00.5815648Z  * [new tag]                 v2.5.0-rc7                  -> v2.5.0-rc7
2025-08-14T21:03:00.5816575Z  * [new tag]                 v2.5.0-rc8                  -> v2.5.0-rc8
2025-08-14T21:03:00.5817470Z  * [new tag]                 v2.5.0-rc9                  -> v2.5.0-rc9
2025-08-14T21:03:00.5818046Z  * [new tag]                 v2.5.1                      -> v2.5.1
2025-08-14T21:03:00.5818743Z  * [new tag]                 v2.5.1-rc1                  -> v2.5.1-rc1
2025-08-14T21:03:00.5819332Z  * [new tag]                 v2.6.0                      -> v2.6.0
2025-08-14T21:03:00.5820364Z  * [new tag]                 v2.6.0-rc1                  -> v2.6.0-rc1
2025-08-14T21:03:00.5821236Z  * [new tag]                 v2.6.0-rc2                  -> v2.6.0-rc2
2025-08-14T21:03:00.5822160Z  * [new tag]                 v2.6.0-rc3                  -> v2.6.0-rc3
2025-08-14T21:03:00.5823003Z  * [new tag]                 v2.6.0-rc4                  -> v2.6.0-rc4
2025-08-14T21:03:00.5824062Z  * [new tag]                 v2.6.0-rc5                  -> v2.6.0-rc5
2025-08-14T21:03:00.5825047Z  * [new tag]                 v2.6.0-rc6                  -> v2.6.0-rc6
2025-08-14T21:03:00.5825922Z  * [new tag]                 v2.6.0-rc7                  -> v2.6.0-rc7
2025-08-14T21:03:00.5826907Z  * [new tag]                 v2.6.0-rc8                  -> v2.6.0-rc8
2025-08-14T21:03:00.5827865Z  * [new tag]                 v2.6.0-rc9                  -> v2.6.0-rc9
2025-08-14T21:03:00.5828794Z  * [new tag]                 v2.7.0                      -> v2.7.0
2025-08-14T21:03:00.5829685Z  * [new tag]                 v2.7.0-rc1                  -> v2.7.0-rc1
2025-08-14T21:03:00.5830262Z  * [new tag]                 v2.7.0-rc10                 -> v2.7.0-rc10
2025-08-14T21:03:00.5831286Z  * [new tag]                 v2.7.0-rc2                  -> v2.7.0-rc2
2025-08-14T21:03:00.5832396Z  * [new tag]                 v2.7.0-rc3                  -> v2.7.0-rc3
2025-08-14T21:03:00.5833264Z  * [new tag]                 v2.7.0-rc4                  -> v2.7.0-rc4
2025-08-14T21:03:00.5834121Z  * [new tag]                 v2.7.0-rc5                  -> v2.7.0-rc5
2025-08-14T21:03:00.5834972Z  * [new tag]                 v2.7.0-rc6                  -> v2.7.0-rc6
2025-08-14T21:03:00.5835835Z  * [new tag]                 v2.7.0-rc7                  -> v2.7.0-rc7
2025-08-14T21:03:00.5836701Z  * [new tag]                 v2.7.0-rc8                  -> v2.7.0-rc8
2025-08-14T21:03:00.5837635Z  * [new tag]                 v2.7.0-rc9                  -> v2.7.0-rc9
2025-08-14T21:03:00.5838423Z  * [new tag]                 v2.7.1                      -> v2.7.1
2025-08-14T21:03:00.5839236Z  * [new tag]                 v2.7.1-rc1                  -> v2.7.1-rc1
2025-08-14T21:03:00.5840226Z  * [new tag]                 v2.7.1-rc2                  -> v2.7.1-rc2
2025-08-14T21:03:00.5841179Z  * [new tag]                 v2.7.1-rc3                  -> v2.7.1-rc3
2025-08-14T21:03:00.5841965Z  * [new tag]                 v2.7.1-rc4                  -> v2.7.1-rc4
2025-08-14T21:03:00.5842963Z  * [new tag]                 v2.7.1-rc5                  -> v2.7.1-rc5
2025-08-14T21:03:00.5843650Z  * [new tag]                 v2.8.0                      -> v2.8.0
2025-08-14T21:03:00.5844613Z  * [new tag]                 v2.8.0-rc1                  -> v2.8.0-rc1
2025-08-14T21:03:00.5845387Z  * [new tag]                 v2.8.0-rc2                  -> v2.8.0-rc2
2025-08-14T21:03:00.5846392Z  * [new tag]                 v2.8.0-rc3                  -> v2.8.0-rc3
2025-08-14T21:03:00.5847240Z  * [new tag]                 v2.8.0-rc4                  -> v2.8.0-rc4
2025-08-14T21:03:00.5848227Z  * [new tag]                 v2.8.0-rc5                  -> v2.8.0-rc5
2025-08-14T21:03:00.5848939Z  * [new tag]                 v2.8.0-rc6                  -> v2.8.0-rc6
2025-08-14T21:03:00.5849847Z  * [new tag]                 v2.8.0-rc7                  -> v2.8.0-rc7
2025-08-14T21:03:00.5850803Z  * [new tag]                 v2.8.0-rc8                  -> v2.8.0-rc8
2025-08-14T21:03:00.5851700Z  * [new tag]                 whc_flight_1                -> whc_flight_1
2025-08-14T21:03:00.5852349Z  * [new tag]                 whc_flight_2                -> whc_flight_2
2025-08-14T21:03:00.5853188Z  * [new tag]                 whc_flight_4                -> whc_flight_4
2025-08-14T21:03:00.6447772Z [command]/usr/bin/git rev-parse --verify --quiet 1fc683cf17c8c673044538d10266c00f92987be2^{object}
2025-08-14T21:03:00.6470109Z 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:03:00.6474898Z ##[endgroup]
2025-08-14T21:03:00.6475402Z ##[group]Determining the checkout info
2025-08-14T21:03:00.6476534Z ##[endgroup]
2025-08-14T21:03:00.6481351Z [command]/usr/bin/git sparse-checkout disable
2025-08-14T21:03:00.6518236Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig
2025-08-14T21:03:00.6542287Z ##[group]Checking out the ref
2025-08-14T21:03:00.6546478Z [command]/usr/bin/git checkout --progress --force 1fc683cf17c8c673044538d10266c00f92987be2
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2025-08-14T21:03:01.8725418Z Updating files: 100% (19474/19474), done.
2025-08-14T21:03:01.9015967Z Note: switching to '1fc683cf17c8c673044538d10266c00f92987be2'.
2025-08-14T21:03:01.9016550Z 
2025-08-14T21:03:01.9016790Z You are in 'detached HEAD' state. You can look around, make experimental
2025-08-14T21:03:01.9017350Z changes and commit them, and you can discard any commits you make in this
2025-08-14T21:03:01.9017925Z state without impacting any branches by switching back to a branch.
2025-08-14T21:03:01.9018260Z 
2025-08-14T21:03:01.9018507Z If you want to create a new branch to retain commits you create, you may
2025-08-14T21:03:01.9019038Z do so (now or later) by using -c with the switch command. Example:
2025-08-14T21:03:01.9019340Z 
2025-08-14T21:03:01.9019456Z   git switch -c <new-branch-name>
2025-08-14T21:03:01.9019672Z 
2025-08-14T21:03:01.9019781Z Or undo this operation with:
2025-08-14T21:03:01.9019975Z 
2025-08-14T21:03:01.9020081Z   git switch -
2025-08-14T21:03:01.9020219Z 
2025-08-14T21:03:01.9020461Z Turn off this advice by setting config variable advice.detachedHead to false
2025-08-14T21:03:01.9020834Z 
2025-08-14T21:03:01.9021246Z HEAD is now at 1fc683cf17c [Inductor] Allow indexing a flexible layout for extract_input_node_reduction_ranges (#160645)
2025-08-14T21:03:01.9084236Z ##[endgroup]
2025-08-14T21:03:01.9084675Z ##[group]Setting up auth for fetching submodules
2025-08-14T21:03:01.9090081Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-08-14T21:03:01.9148524Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf
2025-08-14T21:03:01.9178870Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com:
2025-08-14T21:03:01.9208493Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com:
2025-08-14T21:03:01.9241008Z ##[endgroup]
2025-08-14T21:03:01.9241704Z ##[group]Fetching submodules
2025-08-14T21:03:01.9244486Z [command]/usr/bin/git submodule sync --recursive
2025-08-14T21:03:01.9562088Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive
2025-08-14T21:03:01.9870745Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni'
2025-08-14T21:03:01.9872106Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16'
2025-08-14T21:03:01.9875039Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv'
2025-08-14T21:03:01.9877857Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK'
2025-08-14T21:03:01.9880873Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX'
2025-08-14T21:03:02.0421353Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator'
2025-08-14T21:03:02.0423328Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK'
2025-08-14T21:03:02.0426501Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter'
2025-08-14T21:03:02.0429899Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark'
2025-08-14T21:03:02.0433914Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel'
2025-08-14T21:03:02.0437207Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib'
2025-08-14T21:03:02.0441265Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo'
2025-08-14T21:03:02.0445265Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend'
2025-08-14T21:03:02.0449086Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass'
2025-08-14T21:03:02.0465353Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm'
2025-08-14T21:03:02.0469573Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention'
2025-08-14T21:03:02.0473873Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers'
2025-08-14T21:03:02.0478185Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt'
2025-08-14T21:03:02.0482715Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp'
2025-08-14T21:03:02.0487006Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo'
2025-08-14T21:03:02.0491622Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest'
2025-08-14T21:03:02.0497720Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep'
2025-08-14T21:03:02.0502493Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi'
2025-08-14T21:03:02.0519920Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto'
2025-08-14T21:03:02.0524771Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai'
2025-08-14T21:03:02.0529863Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc'
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2025-08-14T21:03:02.3457897Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FXdiv'...
2025-08-14T21:03:02.3458858Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FP16'...
2025-08-14T21:03:02.3491333Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/composable_kernel'...
2025-08-14T21:03:11.2964282Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NNPACK'...
2025-08-14T21:03:11.2965663Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NVTX'...
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2025-08-14T21:03:11.2968530Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpuinfo'...
2025-08-14T21:03:11.2970029Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpp-httplib'...
2025-08-14T21:03:11.2971586Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention'...
2025-08-14T21:03:11.2973144Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cudnn_frontend'...
2025-08-14T21:03:11.2974799Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'...
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2025-08-14T21:03:11.2977691Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gloo'...
2025-08-14T21:03:11.2978987Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cutlass'...
2025-08-14T21:03:11.2980771Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flatbuffers'...
2025-08-14T21:03:11.2982248Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep'...
2025-08-14T21:03:11.2983676Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fmt'...
2025-08-14T21:03:11.2985138Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ittapi'...
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2025-08-14T21:03:11.3143452Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto'...
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2025-08-14T21:03:12.5990092Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/mimalloc'...
2025-08-14T21:03:12.5991539Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/psimd'...
2025-08-14T21:03:12.5992951Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pthreadpool'...
2025-08-14T21:03:12.6039740Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'...
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2025-08-14T21:03:39.5716363Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/sleef'...
2025-08-14T21:03:39.5717827Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx'...
2025-08-14T21:03:39.5719154Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/nlohmann'...
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2025-08-14T21:03:42.7349545Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f'
2025-08-14T21:03:42.7474809Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3'
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2025-08-14T21:03:42.7819764Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73'
2025-08-14T21:03:42.8602735Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07'
2025-08-14T21:03:42.9137310Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1'
2025-08-14T21:03:43.6655464Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883'
2025-08-14T21:03:43.8180421Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150'
2025-08-14T21:03:43.8201816Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel'
2025-08-14T21:03:43.8228789Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'...
2025-08-14T21:03:47.3597285Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf'
2025-08-14T21:03:47.3843074Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f'
2025-08-14T21:03:47.7044468Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977'
2025-08-14T21:03:47.7596782Z Submodule path 'third_party/cpp-httplib': checked out '3af7f2c16147f3fbc6e4d717032daf505dc1652c'
2025-08-14T21:03:47.8582816Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d'
2025-08-14T21:03:47.9024220Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6'
2025-08-14T21:03:48.5345141Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491'
2025-08-14T21:03:48.6747481Z Submodule path 'third_party/fbgemm': checked out '21c7d30c526c0f1ad873ecc632dca6cfa8a69067'
2025-08-14T21:03:48.6770518Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit'
2025-08-14T21:03:48.6772119Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel'
2025-08-14T21:03:48.6774511Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo'
2025-08-14T21:03:48.6777062Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass'
2025-08-14T21:03:48.6779808Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest'
2025-08-14T21:03:48.6782725Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch'
2025-08-14T21:03:48.6785393Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json'
2025-08-14T21:03:48.6816984Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'...
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2025-08-14T21:03:50.9522791Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'...
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2025-08-14T21:03:57.7810219Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea'
2025-08-14T21:03:58.0447599Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9'
2025-08-14T21:03:58.1463152Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349'
2025-08-14T21:03:58.7650836Z Submodule path 'third_party/fbgemm/external/cutlass': checked out 'b40777404c174b9694a870bff5c13ce6b7f656ad'
2025-08-14T21:03:58.8126134Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723'
2025-08-14T21:03:58.8250884Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out 'a4337c69fe0e2552a7b7b0669178926beeed828c'
2025-08-14T21:03:58.9276704Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03'
2025-08-14T21:03:58.9980790Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5'
2025-08-14T21:03:59.0000481Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel'
2025-08-14T21:03:59.0001928Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass'
2025-08-14T21:03:59.0029773Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'...
2025-08-14T21:04:02.4453687Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'...
2025-08-14T21:04:02.6871767Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33'
2025-08-14T21:04:03.2581743Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420'
2025-08-14T21:04:03.4000519Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757'
2025-08-14T21:04:03.4347164Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21'
2025-08-14T21:04:03.4762581Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350'
2025-08-14T21:04:03.5022646Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2'
2025-08-14T21:04:03.5485843Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723'
2025-08-14T21:04:03.5626261Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3'
2025-08-14T21:04:03.5643387Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn'
2025-08-14T21:04:03.5668878Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'...
2025-08-14T21:04:16.4486397Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d'
2025-08-14T21:04:16.4690715Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959'
2025-08-14T21:04:16.5588902Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658'
2025-08-14T21:04:16.5609779Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog'
2025-08-14T21:04:16.5611831Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt'
2025-08-14T21:04:16.5614398Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest'
2025-08-14T21:04:16.5645658Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'...
2025-08-14T21:04:17.8211890Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'...
2025-08-14T21:04:18.7118883Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'...
2025-08-14T21:04:18.7980381Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e'
2025-08-14T21:04:18.7997036Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-08-14T21:04:18.7999023Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-08-14T21:04:18.8001435Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-08-14T21:04:18.8003984Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-08-14T21:04:18.8006590Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-08-14T21:04:18.8009649Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-08-14T21:04:18.8012423Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-08-14T21:04:18.8015312Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-08-14T21:04:18.8043849Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'...
2025-08-14T21:04:20.7229711Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'...
2025-08-14T21:04:20.7253506Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'...
2025-08-14T21:04:20.7255788Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'...
2025-08-14T21:04:20.7258042Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'...
2025-08-14T21:04:20.8231754Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'...
2025-08-14T21:04:21.2100236Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'...
2025-08-14T21:04:21.3102085Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'...
2025-08-14T21:04:27.6604374Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9'
2025-08-14T21:04:27.6783306Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400'
2025-08-14T21:04:27.7155368Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05'
2025-08-14T21:04:27.7294241Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067'
2025-08-14T21:04:27.7308954Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-08-14T21:04:27.7335950Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'...
2025-08-14T21:04:28.0564189Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4'
2025-08-14T21:04:28.0766848Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446'
2025-08-14T21:04:28.1186342Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850'
2025-08-14T21:04:28.2199270Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5'
2025-08-14T21:04:28.2373365Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150'
2025-08-14T21:04:28.2773777Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164'
2025-08-14T21:04:28.3378558Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347'
2025-08-14T21:04:28.3815354Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7'
2025-08-14T21:04:28.4205419Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e'
2025-08-14T21:04:28.5312579Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72'
2025-08-14T21:04:28.9301148Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83'
2025-08-14T21:04:28.9342623Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11'
2025-08-14T21:04:28.9373177Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'...
2025-08-14T21:04:29.9744338Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4'
2025-08-14T21:04:30.0474845Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878'
2025-08-14T21:04:30.0497314Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-08-14T21:04:30.0499306Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest'
2025-08-14T21:04:30.0501778Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-08-14T21:04:30.0504374Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-08-14T21:04:30.0507209Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-08-14T21:04:30.0510489Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-08-14T21:04:30.0513227Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-08-14T21:04:30.0515889Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-08-14T21:04:30.0546174Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'...
2025-08-14T21:04:30.5937180Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'...
2025-08-14T21:04:30.5939441Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'...
2025-08-14T21:04:30.5941542Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'...
2025-08-14T21:04:30.5943574Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'...
2025-08-14T21:04:30.6938312Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'...
2025-08-14T21:04:31.8995275Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'...
2025-08-14T21:04:41.5758456Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'...
2025-08-14T21:04:41.7444613Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2'
2025-08-14T21:04:41.7844851Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1'
2025-08-14T21:04:41.8015065Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa'
2025-08-14T21:04:41.9030166Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d'
2025-08-14T21:04:41.9163559Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce'
2025-08-14T21:04:41.9308575Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5'
2025-08-14T21:04:41.9470008Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d'
2025-08-14T21:04:41.9485293Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-08-14T21:04:41.9487613Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-08-14T21:04:41.9513389Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'...
2025-08-14T21:04:44.2646028Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'...
2025-08-14T21:04:44.5128764Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4'
2025-08-14T21:04:44.5585780Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929'
2025-08-14T21:04:45.0108688Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50'
2025-08-14T21:04:45.0225660Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa'
2025-08-14T21:04:45.2897624Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a'
2025-08-14T21:04:45.2918961Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/protobuf/third_party/benchmark'
2025-08-14T21:04:45.2921271Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/protobuf/third_party/googletest'
2025-08-14T21:04:45.2946895Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf/third_party/benchmark'...
2025-08-14T21:04:45.8463032Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf/third_party/googletest'...
2025-08-14T21:04:46.4779273Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8'
2025-08-14T21:04:46.5502584Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081'
2025-08-14T21:04:46.5594209Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900'
2025-08-14T21:04:46.5710279Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8'
2025-08-14T21:04:46.6063857Z Submodule path 'third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4'
2025-08-14T21:04:46.6342995Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67'
2025-08-14T21:04:46.6763428Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68'
2025-08-14T21:04:46.7029619Z Submodule path 'third_party/tensorpipe': checked out 'dacda0567d9f23d4bc503e1c4f84aa65f33ac38a'
2025-08-14T21:04:46.7046367Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/tensorpipe/third_party/googletest'
2025-08-14T21:04:46.7048560Z Submodule 'third_party/libnop' (https://github.com/google/libnop.git) registered for path 'third_party/tensorpipe/third_party/libnop'
2025-08-14T21:04:46.7050852Z Submodule 'third_party/libuv' (https://github.com/libuv/libuv.git) registered for path 'third_party/tensorpipe/third_party/libuv'
2025-08-14T21:04:46.7053327Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/tensorpipe/third_party/pybind11'
2025-08-14T21:04:46.7080409Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/googletest'...
2025-08-14T21:04:48.2903618Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libnop'...
2025-08-14T21:04:48.2905537Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/pybind11'...
2025-08-14T21:04:48.3904461Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libuv'...
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2025-08-14T21:04:49.1932547Z ##[endgroup]
2025-08-14T21:04:49.1933031Z ##[group]Persisting credentials for submodules
2025-08-14T21:04:49.1947161Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'url\.https\:\/\/github\.com\/\.insteadOf' && git config --local --unset-all 'url.https://github.com/.insteadOf' || :"
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2025-08-14T21:04:49.6245560Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-08-14T21:04:49.6309644Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url"
2025-08-14T21:04:49.6580097Z Entering 'android/libs/fbjni'
2025-08-14T21:04:49.6627025Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config	remote.origin.url
2025-08-14T21:04:49.6642422Z Entering 'third_party/FP16'
2025-08-14T21:04:49.6688725Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config	remote.origin.url
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2025-08-14T21:04:49.7144873Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config	remote.origin.url
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2025-08-14T21:04:49.7536959Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config	remote.origin.url
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2025-08-14T21:04:49.7672169Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config	remote.origin.url
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2025-08-14T21:04:50.3980764Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-08-14T21:04:50.4022275Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-08-14T21:04:50.4060954Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-08-14T21:04:50.4100823Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-08-14T21:04:50.4141571Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-08-14T21:04:50.4181456Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-08-14T21:04:50.4218661Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-08-14T21:04:50.4258902Z Entering 'third_party/kleidiai'
2025-08-14T21:04:50.4300404Z Entering 'third_party/mimalloc'
2025-08-14T21:04:50.4339550Z Entering 'third_party/nlohmann'
2025-08-14T21:04:50.4379846Z Entering 'third_party/onnx'
2025-08-14T21:04:50.4438241Z Entering 'third_party/onnx/third_party/pybind11'
2025-08-14T21:04:50.4480638Z Entering 'third_party/opentelemetry-cpp'
2025-08-14T21:04:50.4525090Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-08-14T21:04:50.4563274Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-08-14T21:04:50.4603160Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-08-14T21:04:50.4642924Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-08-14T21:04:50.4683130Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-08-14T21:04:50.4721536Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-08-14T21:04:50.4758620Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-08-14T21:04:50.4796615Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-08-14T21:04:50.4837453Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-08-14T21:04:50.4878743Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-08-14T21:04:50.4940447Z Entering 'third_party/pocketfft'
2025-08-14T21:04:50.4981306Z Entering 'third_party/protobuf'
2025-08-14T21:04:50.5024838Z Entering 'third_party/protobuf/third_party/benchmark'
2025-08-14T21:04:50.5062275Z Entering 'third_party/protobuf/third_party/googletest'
2025-08-14T21:04:50.5101734Z Entering 'third_party/psimd'
2025-08-14T21:04:50.5142195Z Entering 'third_party/pthreadpool'
2025-08-14T21:04:50.5182829Z Entering 'third_party/pybind11'
2025-08-14T21:04:50.5222946Z Entering 'third_party/python-peachpy'
2025-08-14T21:04:50.5261836Z Entering 'third_party/sleef'
2025-08-14T21:04:50.5300531Z Entering 'third_party/tensorpipe'
2025-08-14T21:04:50.5339771Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-08-14T21:04:50.5376674Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-08-14T21:04:50.5413382Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-08-14T21:04:50.5450621Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-08-14T21:04:50.5487348Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-08-14T21:04:50.5542081Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:'
2025-08-14T21:04:50.5815822Z Entering 'android/libs/fbjni'
2025-08-14T21:04:50.5854392Z Entering 'third_party/FP16'
2025-08-14T21:04:50.5891785Z Entering 'third_party/FXdiv'
2025-08-14T21:04:50.5929668Z Entering 'third_party/NNPACK'
2025-08-14T21:04:50.5967553Z Entering 'third_party/NVTX'
2025-08-14T21:04:50.6005779Z Entering 'third_party/VulkanMemoryAllocator'
2025-08-14T21:04:50.6044294Z Entering 'third_party/XNNPACK'
2025-08-14T21:04:50.6097272Z Entering 'third_party/aiter'
2025-08-14T21:04:50.6136685Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-08-14T21:04:50.6182637Z Entering 'third_party/benchmark'
2025-08-14T21:04:50.6221602Z Entering 'third_party/composable_kernel'
2025-08-14T21:04:50.6269614Z Entering 'third_party/cpp-httplib'
2025-08-14T21:04:50.6308120Z Entering 'third_party/cpuinfo'
2025-08-14T21:04:50.6348079Z Entering 'third_party/cudnn_frontend'
2025-08-14T21:04:50.6386773Z Entering 'third_party/cutlass'
2025-08-14T21:04:50.6434707Z Entering 'third_party/fbgemm'
2025-08-14T21:04:50.6477304Z Entering 'third_party/fbgemm/external/asmjit'
2025-08-14T21:04:50.6514929Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-08-14T21:04:50.6559726Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-08-14T21:04:50.6596536Z Entering 'third_party/fbgemm/external/cutlass'
2025-08-14T21:04:50.6643310Z Entering 'third_party/fbgemm/external/googletest'
2025-08-14T21:04:50.6680372Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-08-14T21:04:50.6717403Z Entering 'third_party/fbgemm/external/json'
2025-08-14T21:04:50.6756825Z Entering 'third_party/flash-attention'
2025-08-14T21:04:50.6797369Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-08-14T21:04:50.6839237Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-08-14T21:04:50.6883819Z Entering 'third_party/flatbuffers'
2025-08-14T21:04:50.6925164Z Entering 'third_party/fmt'
2025-08-14T21:04:50.6965040Z Entering 'third_party/gemmlowp/gemmlowp'
2025-08-14T21:04:50.7004881Z Entering 'third_party/gloo'
2025-08-14T21:04:50.7046283Z Entering 'third_party/googletest'
2025-08-14T21:04:50.7086663Z Entering 'third_party/ideep'
2025-08-14T21:04:50.7127149Z Entering 'third_party/ideep/mkl-dnn'
2025-08-14T21:04:50.7174797Z Entering 'third_party/ittapi'
2025-08-14T21:04:50.7214920Z Entering 'third_party/kineto'
2025-08-14T21:04:50.7254275Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-08-14T21:04:50.7292211Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-08-14T21:04:50.7332527Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-08-14T21:04:50.7369210Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-08-14T21:04:50.7406244Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-08-14T21:04:50.7442611Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-08-14T21:04:50.7482043Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-08-14T21:04:50.7520049Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-08-14T21:04:50.7557162Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-08-14T21:04:50.7595539Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-08-14T21:04:50.7635763Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-08-14T21:04:50.7673451Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-08-14T21:04:50.7713267Z Entering 'third_party/kleidiai'
2025-08-14T21:04:50.7753818Z Entering 'third_party/mimalloc'
2025-08-14T21:04:50.7793493Z Entering 'third_party/nlohmann'
2025-08-14T21:04:50.7833726Z Entering 'third_party/onnx'
2025-08-14T21:04:50.7890782Z Entering 'third_party/onnx/third_party/pybind11'
2025-08-14T21:04:50.7931142Z Entering 'third_party/opentelemetry-cpp'
2025-08-14T21:04:50.7971450Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-08-14T21:04:50.8008237Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-08-14T21:04:50.8045578Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-08-14T21:04:50.8082175Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-08-14T21:04:50.8123407Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-08-14T21:04:50.8159896Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-08-14T21:04:50.8196328Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-08-14T21:04:50.8233023Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-08-14T21:04:50.8271934Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-08-14T21:04:50.8311161Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-08-14T21:04:50.8368235Z Entering 'third_party/pocketfft'
2025-08-14T21:04:50.8406980Z Entering 'third_party/protobuf'
2025-08-14T21:04:50.8449301Z Entering 'third_party/protobuf/third_party/benchmark'
2025-08-14T21:04:50.8486443Z Entering 'third_party/protobuf/third_party/googletest'
2025-08-14T21:04:50.8525290Z Entering 'third_party/psimd'
2025-08-14T21:04:50.8563604Z Entering 'third_party/pthreadpool'
2025-08-14T21:04:50.8601942Z Entering 'third_party/pybind11'
2025-08-14T21:04:50.8640784Z Entering 'third_party/python-peachpy'
2025-08-14T21:04:50.8679467Z Entering 'third_party/sleef'
2025-08-14T21:04:50.8718655Z Entering 'third_party/tensorpipe'
2025-08-14T21:04:50.8757293Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-08-14T21:04:50.8794560Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-08-14T21:04:50.8831813Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-08-14T21:04:50.8868974Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-08-14T21:04:50.8904859Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-08-14T21:04:50.8955466Z ##[endgroup]
2025-08-14T21:04:50.8988719Z [command]/usr/bin/git log -1 --format=%H
2025-08-14T21:04:50.9010893Z 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:04:50.9210393Z Prepare all required actions
2025-08-14T21:04:50.9211259Z Getting action download info
2025-08-14T21:04:51.0475563Z ##[group]Run ./.github/actions/setup-linux
2025-08-14T21:04:51.0475914Z env:
2025-08-14T21:04:51.0476147Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:51.0476413Z ##[endgroup]
2025-08-14T21:04:51.0546277Z ##[group]Run set -euo pipefail
2025-08-14T21:04:51.0546657Z set -euo pipefail
2025-08-14T21:04:51.0546960Z function get_ec2_metadata() {
2025-08-14T21:04:51.0547342Z   # Pulled from instance metadata endpoint for EC2
2025-08-14T21:04:51.0548003Z   # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
2025-08-14T21:04:51.0548582Z   category=$1
2025-08-14T21:04:51.0548941Z   # If it is GCP runner (runner name contains gcp), do not run this
2025-08-14T21:04:51.0549412Z   runner_name_str=i-02d6cf458b1433fa4
2025-08-14T21:04:51.0549810Z   if [[ -f /.inarc ]]; then
2025-08-14T21:04:51.0550157Z     echo "ARC Runner, no info on ec2 metadata"
2025-08-14T21:04:51.0550557Z   elif [[ $runner_name_str == *"gcp"* ]]; then
2025-08-14T21:04:51.0551040Z     echo "Runner is from Google Cloud Platform, No info on ec2 metadata"
2025-08-14T21:04:51.0551609Z   else
2025-08-14T21:04:51.0552496Z     curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}"
2025-08-14T21:04:51.0553425Z   fi
2025-08-14T21:04:51.0553649Z }
2025-08-14T21:04:51.0553911Z echo "ami-id: $(get_ec2_metadata ami-id)"
2025-08-14T21:04:51.0554354Z echo "instance-id: $(get_ec2_metadata instance-id)"
2025-08-14T21:04:51.0554850Z echo "instance-type: $(get_ec2_metadata instance-type)"
2025-08-14T21:04:51.0555279Z echo "system info $(uname -a)"
2025-08-14T21:04:51.0562227Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:51.0562625Z env:
2025-08-14T21:04:51.0562854Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:51.0563109Z ##[endgroup]
2025-08-14T21:04:51.0712091Z ami-id: ami-05ffe3c48a9991133
2025-08-14T21:04:51.0815017Z instance-id: i-02d6cf458b1433fa4
2025-08-14T21:04:51.0916473Z instance-type: c5.2xlarge
2025-08-14T21:04:51.0926720Z system info Linux ip-10-1-41-230.ec2.internal 6.1.141-155.222.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Tue Jun 17 10:29:47 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux
2025-08-14T21:04:51.0954352Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:04:51.0955327Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:04:51.0961515Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:51.0961924Z env:
2025-08-14T21:04:51.0962157Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:51.0962431Z ##[endgroup]
2025-08-14T21:04:51.1021611Z ##[group]Run if systemctl is-active --quiet docker; then
2025-08-14T21:04:51.1022080Z if systemctl is-active --quiet docker; then
2025-08-14T21:04:51.1022484Z     echo "Docker daemon is running...";
2025-08-14T21:04:51.1022813Z else
2025-08-14T21:04:51.1023202Z     echo "Starting docker daemon..." && sudo systemctl start docker;
2025-08-14T21:04:51.1023637Z fi
2025-08-14T21:04:51.1028880Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:51.1029277Z env:
2025-08-14T21:04:51.1029504Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:51.1029762Z ##[endgroup]
2025-08-14T21:04:51.1101504Z Docker daemon is running...
2025-08-14T21:04:51.1146524Z ##[group]Run nick-fields/retry@v3.0.0
2025-08-14T21:04:51.1158771Z with:
2025-08-14T21:04:51.1159066Z   shell: bash
2025-08-14T21:04:51.1159518Z   timeout_minutes: 5
2025-08-14T21:04:51.1159785Z   max_attempts: 3
2025-08-14T21:04:51.1160024Z   retry_wait_seconds: 30
2025-08-14T21:04:51.1162378Z   command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\")
aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \
    --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com"

# For LF Runners we need to make sure we also login to Meta's ECR docker registry too.
META_AWS_ACCOUNT_ID=308535385114
if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then
    aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \
        --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com"
fi

2025-08-14T21:04:51.1164750Z   polling_interval_seconds: 1
2025-08-14T21:04:51.1165053Z   warning_on_retry: true
2025-08-14T21:04:51.1165332Z   continue_on_error: false
2025-08-14T21:04:51.1165587Z env:
2025-08-14T21:04:51.1165810Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:51.1166089Z   AWS_RETRY_MODE: standard
2025-08-14T21:04:51.1166345Z   AWS_MAX_ATTEMPTS: 5
2025-08-14T21:04:51.1166613Z   AWS_DEFAULT_REGION: us-east-1
2025-08-14T21:04:51.1166901Z ##[endgroup]
2025-08-14T21:04:52.2921906Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-08-14T21:04:52.2922546Z Configure a credential helper to remove this warning. See
2025-08-14T21:04:52.2923144Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-08-14T21:04:52.2923541Z 
2025-08-14T21:04:52.2923654Z Login Succeeded
2025-08-14T21:04:52.8285216Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-08-14T21:04:52.8285853Z Configure a credential helper to remove this warning. See
2025-08-14T21:04:52.8286556Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-08-14T21:04:52.8287059Z 
2025-08-14T21:04:52.8287183Z Login Succeeded
2025-08-14T21:04:53.1992166Z Command completed after 1 attempt(s).
2025-08-14T21:04:53.2056877Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:04:53.2057449Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:04:53.2057928Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:04:53.2065263Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:53.2065658Z env:
2025-08-14T21:04:53.2065890Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.2066155Z ##[endgroup]
2025-08-14T21:04:53.2160895Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty
2025-08-14T21:04:53.2161501Z # ignore expansion of "docker ps -q" since it could be empty
2025-08-14T21:04:53.2161933Z # shellcheck disable=SC2046
2025-08-14T21:04:53.2162282Z docker stop $(docker ps -q) || true
2025-08-14T21:04:53.2162778Z # Prune all of the docker images
2025-08-14T21:04:53.2163144Z docker system prune -af
2025-08-14T21:04:53.2169265Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:53.2169665Z env:
2025-08-14T21:04:53.2169899Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.2170157Z ##[endgroup]
2025-08-14T21:04:53.2414275Z "docker stop" requires at least 1 argument.
2025-08-14T21:04:53.2414705Z See 'docker stop --help'.
2025-08-14T21:04:53.2414887Z 
2025-08-14T21:04:53.2415077Z Usage:  docker stop [OPTIONS] CONTAINER [CONTAINER...]
2025-08-14T21:04:53.2415419Z 
2025-08-14T21:04:53.2415549Z Stop one or more running containers
2025-08-14T21:04:53.2596071Z Total reclaimed space: 0B
2025-08-14T21:04:53.2636800Z ##[group]Run set +e
2025-08-14T21:04:53.2637099Z set +e
2025-08-14T21:04:53.2637349Z set -x
2025-08-14T21:04:53.2637586Z 
2025-08-14T21:04:53.2637830Z PT_DOMAIN=download.pytorch.org
2025-08-14T21:04:53.2638452Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400,
2025-08-14T21:04:53.2639419Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last
2025-08-14T21:04:53.2639975Z # one is returned at random
2025-08-14T21:04:53.2640374Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1)
2025-08-14T21:04:53.2640769Z 
2025-08-14T21:04:53.2641010Z if [ -z "${RESOLVED_IP}" ]; then
2025-08-14T21:04:53.2641445Z   echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..."
2025-08-14T21:04:53.2641986Z   RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1)
2025-08-14T21:04:53.2642388Z 
2025-08-14T21:04:53.2642626Z   if [ -z "${RESOLVED_IP}" ]; then
2025-08-14T21:04:53.2643010Z     echo "Couldn't resolve ${PT_DOMAIN}, exiting..."
2025-08-14T21:04:53.2643395Z     exit 1
2025-08-14T21:04:53.2643634Z   fi
2025-08-14T21:04:53.2643839Z fi
2025-08-14T21:04:53.2644055Z 
2025-08-14T21:04:53.2644325Z if grep -r "${PT_DOMAIN}" /etc/hosts; then
2025-08-14T21:04:53.2644691Z   # Clean up any old records first
2025-08-14T21:04:53.2645069Z   sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts
2025-08-14T21:04:53.2645411Z fi
2025-08-14T21:04:53.2645626Z 
2025-08-14T21:04:53.2645930Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts
2025-08-14T21:04:53.2646341Z cat /etc/hosts
2025-08-14T21:04:53.2652226Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:53.2652601Z env:
2025-08-14T21:04:53.2652824Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.2653095Z ##[endgroup]
2025-08-14T21:04:53.2676401Z + PT_DOMAIN=download.pytorch.org
2025-08-14T21:04:53.2681998Z ++ dig -4 +short download.pytorch.org
2025-08-14T21:04:53.2682608Z ++ tail -n1
2025-08-14T21:04:53.3074647Z + RESOLVED_IP=18.160.10.36
2025-08-14T21:04:53.3074996Z + '[' -z 18.160.10.36 ']'
2025-08-14T21:04:53.3075309Z + grep -r download.pytorch.org /etc/hosts
2025-08-14T21:04:53.3089573Z + echo '18.160.10.36 download.pytorch.org'
2025-08-14T21:04:53.3090342Z + sudo tee -a /etc/hosts
2025-08-14T21:04:53.6374877Z 18.160.10.36 download.pytorch.org
2025-08-14T21:04:53.6389925Z + cat /etc/hosts
2025-08-14T21:04:53.6397882Z 127.0.0.1   localhost localhost.localdomain localhost4 localhost4.localdomain4
2025-08-14T21:04:53.6403664Z ::1         localhost6 localhost6.localdomain6
2025-08-14T21:04:53.6404088Z 18.160.10.36 download.pytorch.org
2025-08-14T21:04:53.6580653Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main
2025-08-14T21:04:53.6581152Z with:
2025-08-14T21:04:53.6581910Z   docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6582759Z   use-custom-docker-registry: true
2025-08-14T21:04:53.6583237Z   docker-build-dir: .ci/docker
2025-08-14T21:04:53.6583547Z   docker-build-script: ./build.sh
2025-08-14T21:04:53.6583843Z   working-directory: .
2025-08-14T21:04:53.6584205Z   docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:53.6584624Z   force-push: false
2025-08-14T21:04:53.6584851Z env:
2025-08-14T21:04:53.6585072Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.6585340Z ##[endgroup]
2025-08-14T21:04:53.6613588Z ##[group]Run set -ex
2025-08-14T21:04:53.6613911Z set -ex
2025-08-14T21:04:53.6614147Z 
2025-08-14T21:04:53.6614598Z # If the docker build directory or the build script doesn't exist, the action will
2025-08-14T21:04:53.6615292Z # gracefully return the docker image name as it is.  Pulling docker image in Linux
2025-08-14T21:04:53.6615872Z # job could then download the pre-built image as usual
2025-08-14T21:04:53.6616595Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then
2025-08-14T21:04:53.6617275Z   echo "skip=false" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6617605Z else
2025-08-14T21:04:53.6617876Z   echo "skip=true" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6618335Z   echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6618756Z 
2025-08-14T21:04:53.6619316Z   echo "Not using custom ECR registry.  Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..."
2025-08-14T21:04:53.6619976Z   exit 0
2025-08-14T21:04:53.6620206Z fi
2025-08-14T21:04:53.6620408Z 
2025-08-14T21:04:53.6620758Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then
2025-08-14T21:04:53.6621377Z   # The docker image name already includes the ECR prefix and tag, so we can just
2025-08-14T21:04:53.6621935Z   # use it as it is, but first let's extract the tag
2025-08-14T21:04:53.6622418Z   DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}')
2025-08-14T21:04:53.6622936Z   echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6623441Z   echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6623861Z else
2025-08-14T21:04:53.6624120Z   if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then
2025-08-14T21:04:53.6624514Z     CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:}
2025-08-14T21:04:53.6624928Z     DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*}
2025-08-14T21:04:53.6625263Z   fi
2025-08-14T21:04:53.6625731Z   DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}")
2025-08-14T21:04:53.6626360Z   echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6627018Z   echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6627733Z   echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6628175Z fi
2025-08-14T21:04:53.6636875Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:53.6637270Z env:
2025-08-14T21:04:53.6637494Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.6637760Z   REPO_NAME: pytorch
2025-08-14T21:04:53.6638695Z   DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6639543Z   DOCKER_BUILD_DIR: .ci/docker
2025-08-14T21:04:53.6639848Z   DOCKER_BUILD_SCRIPT: ./build.sh
2025-08-14T21:04:53.6640230Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:53.6640652Z   USE_CUSTOM_DOCKER_REGISTRY: true
2025-08-14T21:04:53.6640957Z   CUSTOM_TAG_PREFIX: 
2025-08-14T21:04:53.6641299Z ##[endgroup]
2025-08-14T21:04:53.6664637Z + [[ -d .ci/docker ]]
2025-08-14T21:04:53.6665181Z + [[ -f .ci/docker/./build.sh ]]
2025-08-14T21:04:53.6665513Z + [[ true == \t\r\u\e ]]
2025-08-14T21:04:53.6665993Z + echo skip=false
2025-08-14T21:04:53.6667202Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]]
2025-08-14T21:04:53.6671832Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6672659Z ++ awk -F '[:,]' '{print $2}'
2025-08-14T21:04:53.6693527Z + DOCKER_TAG=pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6694323Z + echo docker-tag=pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6695417Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6727417Z ##[group]Run set +e
2025-08-14T21:04:53.6727736Z set +e
2025-08-14T21:04:53.6727980Z set -x
2025-08-14T21:04:53.6728216Z 
2025-08-14T21:04:53.6728421Z login() {
2025-08-14T21:04:53.6728919Z   aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1"
2025-08-14T21:04:53.6729457Z }
2025-08-14T21:04:53.6729660Z 
2025-08-14T21:04:53.6729887Z retry () {
2025-08-14T21:04:53.6730165Z   $*  || (sleep 1 && $*) || (sleep 2 && $*)
2025-08-14T21:04:53.6730477Z }
2025-08-14T21:04:53.6730689Z 
2025-08-14T21:04:53.6730928Z retry login "${DOCKER_REGISTRY}"
2025-08-14T21:04:53.6731241Z 
2025-08-14T21:04:53.6731451Z START_TIME=$(date +%s)
2025-08-14T21:04:53.6731762Z # Wait up to 120 minutes
2025-08-14T21:04:53.6732136Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do
2025-08-14T21:04:53.6732633Z   # Check if image already exists, if it does then skip building it
2025-08-14T21:04:53.6733138Z   if docker manifest inspect "${DOCKER_IMAGE}"; then
2025-08-14T21:04:53.6733516Z     exit 0
2025-08-14T21:04:53.6733747Z   fi
2025-08-14T21:04:53.6733968Z 
2025-08-14T21:04:53.6734363Z   # NB: This flag is used by Docker build workflow to push the image to ECR, so we can
2025-08-14T21:04:53.6735053Z   # use this to differentiate between the Docker build and regular build jobs. For the
2025-08-14T21:04:53.6735731Z   # latter, it will wait for the Docker images to become available before continuing
2025-08-14T21:04:53.6736272Z   if [ "${DOCKER_PUSH:-false}" == "true" ]; then
2025-08-14T21:04:53.6736686Z     # It's a Docker build job, let's build the image
2025-08-14T21:04:53.6737049Z     break
2025-08-14T21:04:53.6737277Z   else
2025-08-14T21:04:53.6737632Z     # It's a regular build job, wait for the image to become available
2025-08-14T21:04:53.6738058Z     sleep 300
2025-08-14T21:04:53.6738301Z   fi
2025-08-14T21:04:53.6738524Z done
2025-08-14T21:04:53.6738748Z 
2025-08-14T21:04:53.6739098Z # NB: This part requires a full checkout. Otherwise, the merge base will
2025-08-14T21:04:53.6739684Z # be empty.  The default action would be to continue rebuild the image
2025-08-14T21:04:53.6740348Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then
2025-08-14T21:04:53.6740827Z   # if we're on the base branch then use the parent commit
2025-08-14T21:04:53.6741235Z   MERGE_BASE=$(git rev-parse HEAD~)
2025-08-14T21:04:53.6741564Z else
2025-08-14T21:04:53.6741905Z   # otherwise we're on a PR, so use the most recent base commit
2025-08-14T21:04:53.6742456Z   MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION")
2025-08-14T21:04:53.6742831Z fi
2025-08-14T21:04:53.6743050Z 
2025-08-14T21:04:53.6743288Z if [[ -z "${MERGE_BASE}" ]]; then
2025-08-14T21:04:53.6743643Z   echo "rebuild=true" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6743984Z 
2025-08-14T21:04:53.6744465Z   echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..."
2025-08-14T21:04:53.6745021Z   exit 0
2025-08-14T21:04:53.6745250Z fi
2025-08-14T21:04:53.6745468Z 
2025-08-14T21:04:53.6745769Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then
2025-08-14T21:04:53.6746476Z   echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit"
2025-08-14T21:04:53.6747080Z   exit 1
2025-08-14T21:04:53.6747314Z fi
2025-08-14T21:04:53.6747518Z 
2025-08-14T21:04:53.6747889Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}")
2025-08-14T21:04:53.6748567Z # If no image exists but the hash is the same as the previous hash then we should error out here
2025-08-14T21:04:53.6749176Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then
2025-08-14T21:04:53.6749867Z   echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch"
2025-08-14T21:04:53.6750663Z   echo "         Will re-build docker image to store in local cache, TTS may be longer"
2025-08-14T21:04:53.6751136Z fi
2025-08-14T21:04:53.6751429Z 
2025-08-14T21:04:53.6751705Z echo "rebuild=true" >> "${GITHUB_OUTPUT}"
2025-08-14T21:04:53.6757261Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:53.6757654Z env:
2025-08-14T21:04:53.6757866Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:53.6758165Z   DOCKER_BUILD_DIR: .ci/docker
2025-08-14T21:04:53.6758517Z   BASE_REVISION: 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:04:53.6759384Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6760423Z   DOCKER_TAG: pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:53.6761060Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:53.6761465Z   DOCKER_PUSH: 
2025-08-14T21:04:53.6761687Z ##[endgroup]
2025-08-14T21:04:53.6783181Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:53.6783626Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:53.6786007Z + aws ecr get-login-password --region us-east-1
2025-08-14T21:04:53.6786862Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:54.2378156Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-08-14T21:04:54.2378856Z Configure a credential helper to remove this warning. See
2025-08-14T21:04:54.2380070Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-08-14T21:04:54.2380502Z 
2025-08-14T21:04:54.2380618Z Login Succeeded
2025-08-14T21:04:54.2396545Z ++ date +%s
2025-08-14T21:04:54.2405264Z + START_TIME=1755205494
2025-08-14T21:04:54.2409454Z ++ date +%s
2025-08-14T21:04:54.2418017Z + [[ 1755198294 -lt 1755205494 ]]
2025-08-14T21:04:54.2420076Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:54.4467830Z {
2025-08-14T21:04:54.4468127Z 	"schemaVersion": 2,
2025-08-14T21:04:54.4468581Z 	"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
2025-08-14T21:04:54.4469038Z 	"config": {
2025-08-14T21:04:54.4469424Z 		"mediaType": "application/vnd.docker.container.image.v1+json",
2025-08-14T21:04:54.4470365Z 		"size": 30028,
2025-08-14T21:04:54.4471018Z 		"digest": "sha256:d23aa400d15c13cf4cd8d85388ce0304ef46d5163b945cf305903ce37fa5c8ba"
2025-08-14T21:04:54.4471856Z 	},
2025-08-14T21:04:54.4472065Z 	"layers": [
2025-08-14T21:04:54.4472282Z 		{
2025-08-14T21:04:54.4472614Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4473223Z 			"size": 30448173,
2025-08-14T21:04:54.4473888Z 			"digest": "sha256:660ffc76f83b006444a5731b215acc2e35138d8be5cac8ed1ffd40f947117495"
2025-08-14T21:04:54.4474802Z 		},
2025-08-14T21:04:54.4475016Z 		{
2025-08-14T21:04:54.4475361Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4475789Z 			"size": 1554,
2025-08-14T21:04:54.4476195Z 			"digest": "sha256:a7ac6822069caec96042d8957a65289c4aaae3ce024ea77fc19125134222c906"
2025-08-14T21:04:54.4476678Z 		},
2025-08-14T21:04:54.4476874Z 		{
2025-08-14T21:04:54.4477189Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4477628Z 			"size": 344010930,
2025-08-14T21:04:54.4478051Z 			"digest": "sha256:31f42505d41a2353752a9e5c6085593893fe632bd6d5f0e13b6895536742f09e"
2025-08-14T21:04:54.4478559Z 		},
2025-08-14T21:04:54.4478760Z 		{
2025-08-14T21:04:54.4479087Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4479502Z 			"size": 792,
2025-08-14T21:04:54.4479922Z 			"digest": "sha256:fed7b1c3e821e3e8bef41e41ce3164d16987e2e0d33c4127d4100594b9dd2687"
2025-08-14T21:04:54.4480406Z 		},
2025-08-14T21:04:54.4480605Z 		{
2025-08-14T21:04:54.4481044Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4481695Z 			"size": 63270240,
2025-08-14T21:04:54.4482406Z 			"digest": "sha256:f6ff1c4ec221178e5d3a1c3f8b7bdf762de8a1d29731355af55f27ebe795cc4e"
2025-08-14T21:04:54.4483215Z 		},
2025-08-14T21:04:54.4483530Z 		{
2025-08-14T21:04:54.4484066Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4484513Z 			"size": 703,
2025-08-14T21:04:54.4484941Z 			"digest": "sha256:2b3c95d5bdd39ee79b574df645dfcd7ac6917222169adeebf7ac42fce49a5535"
2025-08-14T21:04:54.4485537Z + exit 0
2025-08-14T21:04:54.4485749Z 		},
2025-08-14T21:04:54.4485936Z 		{
2025-08-14T21:04:54.4486271Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
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2025-08-14T21:04:54.4584661Z 			"digest": "sha256:667e6862828201f780ea912992e616aa880bb1c90331ac2771faeaffd217a2a1"
2025-08-14T21:04:54.4585128Z 		},
2025-08-14T21:04:54.4585327Z 		{
2025-08-14T21:04:54.4585664Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4586092Z 			"size": 1012,
2025-08-14T21:04:54.4586525Z 			"digest": "sha256:8b05e09cad0d98b3d86cb31d29df459fe80b5d31edab5002e509b74e3873739c"
2025-08-14T21:04:54.4587019Z 		},
2025-08-14T21:04:54.4587204Z 		{
2025-08-14T21:04:54.4587542Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4587975Z 			"size": 724,
2025-08-14T21:04:54.4588391Z 			"digest": "sha256:dea7b5130129251d8c5bb14ac048a6f027264dbdcdd03651891761d87685e53a"
2025-08-14T21:04:54.4588867Z 		},
2025-08-14T21:04:54.4589066Z 		{
2025-08-14T21:04:54.4589404Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4589819Z 			"size": 135,
2025-08-14T21:04:54.4590235Z 			"digest": "sha256:a20271f3e13588a2de4d699e92e5fc511a9278a421f3da5afd55fd2dadfdbd3a"
2025-08-14T21:04:54.4590728Z 		},
2025-08-14T21:04:54.4590912Z 		{
2025-08-14T21:04:54.4591256Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4591771Z 			"size": 32,
2025-08-14T21:04:54.4592181Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4592679Z 		},
2025-08-14T21:04:54.4592875Z 		{
2025-08-14T21:04:54.4593192Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4593621Z 			"size": 158,
2025-08-14T21:04:54.4594041Z 			"digest": "sha256:6de635554f5bedb7dc7495fd3ca61fa1aaf871cd4e3b05a35fde30730461ada5"
2025-08-14T21:04:54.4594526Z 		},
2025-08-14T21:04:54.4594708Z 		{
2025-08-14T21:04:54.4595038Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4595467Z 			"size": 1371,
2025-08-14T21:04:54.4595878Z 			"digest": "sha256:2327901bebfd55b72911728ecfd4e8cb08afe8b29996d781ebf01b8390054e44"
2025-08-14T21:04:54.4596355Z 		},
2025-08-14T21:04:54.4596554Z 		{
2025-08-14T21:04:54.4596874Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4597304Z 			"size": 32,
2025-08-14T21:04:54.4597724Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4598198Z 		},
2025-08-14T21:04:54.4598390Z 		{
2025-08-14T21:04:54.4598721Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4599146Z 			"size": 137,
2025-08-14T21:04:54.4599565Z 			"digest": "sha256:0e1acd221de3cc47d23da8c5d8a7d1e977ef4292ec9c7f281fe5a5f1d64e7bd9"
2025-08-14T21:04:54.4600065Z 		},
2025-08-14T21:04:54.4600260Z 		{
2025-08-14T21:04:54.4600582Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4601010Z 			"size": 381,
2025-08-14T21:04:54.4601426Z 			"digest": "sha256:883fad14abaf565a7b093b782bd849cd24c6660c8c07d9ef1a11e01088c5f0d7"
2025-08-14T21:04:54.4601898Z 		},
2025-08-14T21:04:54.4602090Z 		{
2025-08-14T21:04:54.4602419Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4602834Z 			"size": 32,
2025-08-14T21:04:54.4603377Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4603881Z 		},
2025-08-14T21:04:54.4604070Z 		{
2025-08-14T21:04:54.4604412Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4604844Z 			"size": 104,
2025-08-14T21:04:54.4605260Z 			"digest": "sha256:3cdf0c0557b941570c917e86e4d1e470d60032963d1b76062c30b4f1156fc758"
2025-08-14T21:04:54.4605791Z 		},
2025-08-14T21:04:54.4605988Z 		{
2025-08-14T21:04:54.4606320Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4606739Z 			"size": 408,
2025-08-14T21:04:54.4607157Z 			"digest": "sha256:49f35c818257f5545e2b3372c00bca591efedc9b05e5cf8ea6b7d62407496c1f"
2025-08-14T21:04:54.4607639Z 		},
2025-08-14T21:04:54.4607823Z 		{
2025-08-14T21:04:54.4608156Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4608577Z 			"size": 32,
2025-08-14T21:04:54.4608988Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4609728Z 		},
2025-08-14T21:04:54.4609932Z 		{
2025-08-14T21:04:54.4610258Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4610693Z 			"size": 109,
2025-08-14T21:04:54.4611126Z 			"digest": "sha256:d7a2ef6024dcdbae3e781f757c4f3599f0db121c128604a47afb78f1093b6649"
2025-08-14T21:04:54.4611625Z 		},
2025-08-14T21:04:54.4611807Z 		{
2025-08-14T21:04:54.4612140Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4612565Z 			"size": 1897,
2025-08-14T21:04:54.4612973Z 			"digest": "sha256:e069f49d0a3523173c0e6e8ea5a81d8d4a3bdfe609314b500bbf36103c03d81b"
2025-08-14T21:04:54.4613451Z 		},
2025-08-14T21:04:54.4613645Z 		{
2025-08-14T21:04:54.4613964Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4614396Z 			"size": 242602026,
2025-08-14T21:04:54.4614830Z 			"digest": "sha256:c5150ca5ac67725ab2236b5f7a9745838c31a44677d136ca91ebe0377b60cf5e"
2025-08-14T21:04:54.4615306Z 		},
2025-08-14T21:04:54.4615502Z 		{
2025-08-14T21:04:54.4615842Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4616269Z 			"size": 106,
2025-08-14T21:04:54.4616676Z 			"digest": "sha256:bebe10ca43f6318912ad558760fa4414a890e6a2589e4c5c7e61fbd1b4b78a01"
2025-08-14T21:04:54.4617166Z 		},
2025-08-14T21:04:54.4617363Z 		{
2025-08-14T21:04:54.4617687Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4618116Z 			"size": 165,
2025-08-14T21:04:54.4618533Z 			"digest": "sha256:adc4a16c409d97bc4e93280336e24564b7d494342ce8d1dc7861f721bdacb921"
2025-08-14T21:04:54.4619007Z 		},
2025-08-14T21:04:54.4619198Z 		{
2025-08-14T21:04:54.4619531Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4619943Z 			"size": 7943,
2025-08-14T21:04:54.4620361Z 			"digest": "sha256:b7028bbd1f0eec067553ade80e9a6ee43634423f2921e8c031290e00b5e83002"
2025-08-14T21:04:54.4620851Z 		},
2025-08-14T21:04:54.4621036Z 		{
2025-08-14T21:04:54.4621375Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4621801Z 			"size": 8073,
2025-08-14T21:04:54.4622223Z 			"digest": "sha256:53acff155ed940723ac8c626fe629e503d762c950eb9e5f8632e9e266da11e65"
2025-08-14T21:04:54.4622696Z 		},
2025-08-14T21:04:54.4622897Z 		{
2025-08-14T21:04:54.4623247Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4623666Z 			"size": 304,
2025-08-14T21:04:54.4624096Z 			"digest": "sha256:dee80f9872f35c35c7c6d0ea6256cd4ba23031fab6a56ff10e4351f4ab21c0e4"
2025-08-14T21:04:54.4624589Z 		},
2025-08-14T21:04:54.4624782Z 		{
2025-08-14T21:04:54.4625125Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4625560Z 			"size": 32,
2025-08-14T21:04:54.4625980Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4626478Z 		},
2025-08-14T21:04:54.4626679Z 		{
2025-08-14T21:04:54.4627220Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4627652Z 			"size": 108,
2025-08-14T21:04:54.4628078Z 			"digest": "sha256:a254ee8e69154845b968df80ab4d75eb4a88fd7042dec8dbf39b0c981e4dd20a"
2025-08-14T21:04:54.4628571Z 		},
2025-08-14T21:04:54.4628760Z 		{
2025-08-14T21:04:54.4629098Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4629610Z 			"size": 54145660,
2025-08-14T21:04:54.4630043Z 			"digest": "sha256:e7bcb72e6b9e10c8e2f101145bd6d1b6ca9bebfdb042a7199218aa2ee2e3a725"
2025-08-14T21:04:54.4630541Z 		},
2025-08-14T21:04:54.4630737Z 		{
2025-08-14T21:04:54.4631058Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-08-14T21:04:54.4631603Z 			"size": 32,
2025-08-14T21:04:54.4632024Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-08-14T21:04:54.4632499Z 		}
2025-08-14T21:04:54.4632702Z 	]
2025-08-14T21:04:54.4632896Z }
2025-08-14T21:04:54.4669878Z ##[group]Run set -eux
2025-08-14T21:04:54.4670170Z set -eux
2025-08-14T21:04:54.4671085Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin
2025-08-14T21:04:54.4679205Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:54.4679609Z env:
2025-08-14T21:04:54.4679839Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:54.4680118Z ##[endgroup]
2025-08-14T21:04:54.4709436Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token
2025-08-14T21:04:54.4710337Z + jq --raw-output .SecretString
2025-08-14T21:04:54.4710939Z + jq -r .docker_hub_readonly_token
2025-08-14T21:04:54.4712661Z + docker login --username pytorchbot --password-stdin
2025-08-14T21:04:55.1364563Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-08-14T21:04:55.1365298Z Configure a credential helper to remove this warning. See
2025-08-14T21:04:55.1366139Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-08-14T21:04:55.1366748Z 
2025-08-14T21:04:55.1369444Z Login Succeeded
2025-08-14T21:04:55.1455314Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:}
2025-08-14T21:04:55.1455715Z tag=${ECR_DOCKER_IMAGE##*:}
2025-08-14T21:04:55.1456147Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
2025-08-14T21:04:55.1461934Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:55.1462327Z env:
2025-08-14T21:04:55.1462542Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:55.1463432Z   ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.1464260Z ##[endgroup]
2025-08-14T21:04:55.1490006Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.1540963Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main
2025-08-14T21:04:55.1541425Z with:
2025-08-14T21:04:55.1542157Z   docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.1543059Z   docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:55.1543473Z env:
2025-08-14T21:04:55.1543692Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:55.1543947Z ##[endgroup]
2025-08-14T21:04:55.1564958Z ##[group]Run set -x
2025-08-14T21:04:55.1565249Z set -x
2025-08-14T21:04:55.1565485Z set +e
2025-08-14T21:04:55.1565715Z 
2025-08-14T21:04:55.1565923Z login() {
2025-08-14T21:04:55.1566420Z   aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1"
2025-08-14T21:04:55.1566958Z }
2025-08-14T21:04:55.1567162Z 
2025-08-14T21:04:55.1567426Z retry () {
2025-08-14T21:04:55.1567693Z   $*  || (sleep 1 && $*) || (sleep 2 && $*)
2025-08-14T21:04:55.1568022Z }
2025-08-14T21:04:55.1568235Z 
2025-08-14T21:04:55.1568474Z retry login "${DOCKER_REGISTRY}"
2025-08-14T21:04:55.1568783Z 
2025-08-14T21:04:55.1569296Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024')
2025-08-14T21:04:55.1570158Z echo "Compressed size of image in MB: ${IMAGE_SIZE}"
2025-08-14T21:04:55.1570538Z 
2025-08-14T21:04:55.1570759Z set -e
2025-08-14T21:04:55.1571119Z # ignore output since only exit code is used for conditional
2025-08-14T21:04:55.1571629Z # only pull docker image if it's not available locally
2025-08-14T21:04:55.1572178Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then
2025-08-14T21:04:55.1572704Z   retry docker pull "${DOCKER_IMAGE}"
2025-08-14T21:04:55.1573037Z fi
2025-08-14T21:04:55.1578777Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:04:55.1579167Z env:
2025-08-14T21:04:55.1579405Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:04:55.1580173Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.1581100Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:55.1581506Z ##[endgroup]
2025-08-14T21:04:55.1604604Z + set +e
2025-08-14T21:04:55.1605325Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:55.1608354Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:55.1608802Z + aws ecr get-login-password --region us-east-1
2025-08-14T21:04:55.1609617Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-08-14T21:04:55.6647134Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-08-14T21:04:55.6647779Z Configure a credential helper to remove this warning. See
2025-08-14T21:04:55.6648381Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-08-14T21:04:55.6648932Z 
2025-08-14T21:04:55.6649090Z Login Succeeded
2025-08-14T21:04:55.6666619Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.6667978Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024'
2025-08-14T21:04:55.8598887Z + IMAGE_SIZE=4410.942840576172
2025-08-14T21:04:55.8599431Z Compressed size of image in MB: 4410.942840576172
2025-08-14T21:04:55.8599872Z + echo 'Compressed size of image in MB: 4410.942840576172'
2025-08-14T21:04:55.8600260Z + set -e
2025-08-14T21:04:55.8601387Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.8713101Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:55.8714461Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:04:56.1135187Z pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe: Pulling from pytorch/ci-image
2025-08-14T21:04:56.1139817Z 660ffc76f83b: Pulling fs layer
2025-08-14T21:04:56.1140499Z a7ac6822069c: Pulling fs layer
2025-08-14T21:04:56.1141432Z 31f42505d41a: Pulling fs layer
2025-08-14T21:04:56.1141956Z fed7b1c3e821: Pulling fs layer
2025-08-14T21:04:56.1142593Z f6ff1c4ec221: Pulling fs layer
2025-08-14T21:04:56.1143101Z 2b3c95d5bdd3: Pulling fs layer
2025-08-14T21:04:56.1143640Z 64e5c40daf9a: Pulling fs layer
2025-08-14T21:04:56.1144139Z fed7b1c3e821: Waiting
2025-08-14T21:04:56.1144600Z 0113773a5bba: Pulling fs layer
2025-08-14T21:04:56.1145087Z 12513ab032b1: Pulling fs layer
2025-08-14T21:04:56.1145563Z 72da40fd831c: Pulling fs layer
2025-08-14T21:04:56.1145976Z 4ea4b6ca480f: Pulling fs layer
2025-08-14T21:04:56.1146278Z dea7b5130129: Pulling fs layer
2025-08-14T21:04:56.1146565Z f6ff1c4ec221: Waiting
2025-08-14T21:04:56.1146937Z 7a90440a78c7: Pulling fs layer
2025-08-14T21:04:56.1147673Z 258d086c6347: Pulling fs layer
2025-08-14T21:04:56.1148072Z 2b3c95d5bdd3: Waiting
2025-08-14T21:04:56.1148315Z 64e5c40daf9a: Waiting
2025-08-14T21:04:56.1148669Z 4f4fb700ef54: Pulling fs layer
2025-08-14T21:04:56.1149044Z 0113773a5bba: Waiting
2025-08-14T21:04:56.1149306Z ab642c9771e0: Pulling fs layer
2025-08-14T21:04:56.1149574Z 12513ab032b1: Waiting
2025-08-14T21:04:56.1149835Z d947308ec6c0: Pulling fs layer
2025-08-14T21:04:56.1150130Z 82f3234546b3: Pulling fs layer
2025-08-14T21:04:56.1150434Z 72da40fd831c: Waiting
2025-08-14T21:04:56.1150681Z 4ea4b6ca480f: Waiting
2025-08-14T21:04:56.1150940Z 4f4fb700ef54: Waiting
2025-08-14T21:04:56.1151176Z ab642c9771e0: Waiting
2025-08-14T21:04:56.1151576Z 960d25169df1: Pulling fs layer
2025-08-14T21:04:56.1151942Z dbc40137a811: Pulling fs layer
2025-08-14T21:04:56.1152213Z dea7b5130129: Waiting
2025-08-14T21:04:56.1152484Z 7a90440a78c7: Waiting
2025-08-14T21:04:56.1152736Z 28d6214975c0: Pulling fs layer
2025-08-14T21:04:56.1153058Z d947308ec6c0: Waiting
2025-08-14T21:04:56.1153308Z 258d086c6347: Waiting
2025-08-14T21:04:56.1153578Z e75d4694ae82: Pulling fs layer
2025-08-14T21:04:56.1153842Z 960d25169df1: Waiting
2025-08-14T21:04:56.1154136Z dbc40137a811: Waiting
2025-08-14T21:04:56.1154392Z c8fd1f66c221: Pulling fs layer
2025-08-14T21:04:56.1154672Z 73a036f4a5d4: Pulling fs layer
2025-08-14T21:04:56.1154946Z 82f3234546b3: Waiting
2025-08-14T21:04:56.1155270Z c8fd1f66c221: Waiting
2025-08-14T21:04:56.1155527Z 92c311949fb1: Pulling fs layer
2025-08-14T21:04:56.1155825Z 73a036f4a5d4: Waiting
2025-08-14T21:04:56.1156071Z 28d6214975c0: Waiting
2025-08-14T21:04:56.1156331Z 29f6cfbe4c15: Pulling fs layer
2025-08-14T21:04:56.1156671Z fb6c7ee8061b: Pulling fs layer
2025-08-14T21:04:56.1156952Z 0302c90f502f: Pulling fs layer
2025-08-14T21:04:56.1157237Z 3ca1010f3846: Pulling fs layer
2025-08-14T21:04:56.1157513Z fb6c7ee8061b: Waiting
2025-08-14T21:04:56.1157753Z 072215d97c72: Pulling fs layer
2025-08-14T21:04:56.1158111Z 0302c90f502f: Waiting
2025-08-14T21:04:56.1158446Z 3ca1010f3846: Waiting
2025-08-14T21:04:56.1158679Z 29f6cfbe4c15: Waiting
2025-08-14T21:04:56.1158998Z 51a8de8f5ab2: Pulling fs layer
2025-08-14T21:04:56.1159294Z 8a649a6063cf: Pulling fs layer
2025-08-14T21:04:56.1159569Z 6f5614ef0259: Pulling fs layer
2025-08-14T21:04:56.1159856Z 5c0a31477213: Pulling fs layer
2025-08-14T21:04:56.1160129Z 072215d97c72: Waiting
2025-08-14T21:04:56.1160374Z b9bc257d5af6: Pulling fs layer
2025-08-14T21:04:56.1160655Z 51a8de8f5ab2: Waiting
2025-08-14T21:04:56.1160899Z 6f5614ef0259: Waiting
2025-08-14T21:04:56.1161128Z 5c0a31477213: Waiting
2025-08-14T21:04:56.1161579Z 4a977d8955e6: Pulling fs layer
2025-08-14T21:04:56.1161920Z 32a65e5a5d0d: Pulling fs layer
2025-08-14T21:04:56.1162220Z 88b9c7fbb7f5: Pulling fs layer
2025-08-14T21:04:56.1162649Z 4a977d8955e6: Waiting
2025-08-14T21:04:56.1163111Z 32a65e5a5d0d: Waiting
2025-08-14T21:04:56.1163552Z 88b9c7fbb7f5: Waiting
2025-08-14T21:04:56.1163977Z ad0aa3946f36: Pulling fs layer
2025-08-14T21:04:56.1164469Z f78553d91b8d: Pulling fs layer
2025-08-14T21:04:56.1165044Z 0b7ea6453230: Pulling fs layer
2025-08-14T21:04:56.1165518Z 8330e7ea1b20: Pulling fs layer
2025-08-14T21:04:56.1165979Z ad0aa3946f36: Waiting
2025-08-14T21:04:56.1166403Z e7aff2fc4378: Pulling fs layer
2025-08-14T21:04:56.1166856Z f78553d91b8d: Waiting
2025-08-14T21:04:56.1167259Z 8330e7ea1b20: Waiting
2025-08-14T21:04:56.1167663Z 0b7ea6453230: Waiting
2025-08-14T21:04:56.1168066Z e7aff2fc4378: Waiting
2025-08-14T21:04:56.1168464Z 8a649a6063cf: Waiting
2025-08-14T21:04:56.1168881Z b9bc257d5af6: Waiting
2025-08-14T21:04:56.1169284Z 667e68628282: Pulling fs layer
2025-08-14T21:04:56.1169757Z 8b05e09cad0d: Pulling fs layer
2025-08-14T21:04:56.1170051Z a20271f3e135: Pulling fs layer
2025-08-14T21:04:56.1170313Z a20271f3e135: Waiting
2025-08-14T21:04:56.1170611Z 6de635554f5b: Pulling fs layer
2025-08-14T21:04:56.1170899Z 8b05e09cad0d: Waiting
2025-08-14T21:04:56.1171140Z 667e68628282: Waiting
2025-08-14T21:04:56.1171444Z 2327901bebfd: Pulling fs layer
2025-08-14T21:04:56.1172157Z 6de635554f5b: Waiting
2025-08-14T21:04:56.1172653Z 0e1acd221de3: Pulling fs layer
2025-08-14T21:04:56.1173241Z 883fad14abaf: Pulling fs layer
2025-08-14T21:04:56.1173544Z 3cdf0c0557b9: Pulling fs layer
2025-08-14T21:04:56.1173861Z 2327901bebfd: Waiting
2025-08-14T21:04:56.1174185Z 49f35c818257: Pulling fs layer
2025-08-14T21:04:56.1174508Z 883fad14abaf: Waiting
2025-08-14T21:04:56.1174753Z 49f35c818257: Waiting
2025-08-14T21:04:56.1174999Z d7a2ef6024dc: Pulling fs layer
2025-08-14T21:04:56.1185993Z 0e1acd221de3: Waiting
2025-08-14T21:04:56.1186523Z e069f49d0a35: Pulling fs layer
2025-08-14T21:04:56.1186912Z d7a2ef6024dc: Waiting
2025-08-14T21:04:56.1187252Z c5150ca5ac67: Pulling fs layer
2025-08-14T21:04:56.1187538Z bebe10ca43f6: Pulling fs layer
2025-08-14T21:04:56.1187859Z c5150ca5ac67: Waiting
2025-08-14T21:04:56.1188231Z 3cdf0c0557b9: Waiting
2025-08-14T21:04:56.1188653Z adc4a16c409d: Pulling fs layer
2025-08-14T21:04:56.1189100Z bebe10ca43f6: Waiting
2025-08-14T21:04:56.1189362Z b7028bbd1f0e: Pulling fs layer
2025-08-14T21:04:56.1189668Z 53acff155ed9: Pulling fs layer
2025-08-14T21:04:56.1189954Z dee80f9872f3: Pulling fs layer
2025-08-14T21:04:56.1190239Z adc4a16c409d: Waiting
2025-08-14T21:04:56.1190610Z a254ee8e6915: Pulling fs layer
2025-08-14T21:04:56.1191131Z b7028bbd1f0e: Waiting
2025-08-14T21:04:56.1191635Z 53acff155ed9: Waiting
2025-08-14T21:04:56.1192083Z e7bcb72e6b9e: Pulling fs layer
2025-08-14T21:04:56.1192532Z e7bcb72e6b9e: Waiting
2025-08-14T21:04:56.1192795Z dee80f9872f3: Waiting
2025-08-14T21:04:56.1193134Z a254ee8e6915: Waiting
2025-08-14T21:04:56.1873973Z a7ac6822069c: Verifying Checksum
2025-08-14T21:04:56.1874445Z a7ac6822069c: Download complete
2025-08-14T21:04:56.2940112Z fed7b1c3e821: Verifying Checksum
2025-08-14T21:04:56.2940666Z fed7b1c3e821: Download complete
2025-08-14T21:04:56.4742896Z 660ffc76f83b: Verifying Checksum
2025-08-14T21:04:56.4743304Z 660ffc76f83b: Download complete
2025-08-14T21:04:56.5654853Z 2b3c95d5bdd3: Download complete
2025-08-14T21:04:56.6476327Z 64e5c40daf9a: Verifying Checksum
2025-08-14T21:04:56.6476951Z 64e5c40daf9a: Download complete
2025-08-14T21:04:56.7152030Z 0113773a5bba: Verifying Checksum
2025-08-14T21:04:56.7152468Z 0113773a5bba: Download complete
2025-08-14T21:04:56.7791688Z 12513ab032b1: Verifying Checksum
2025-08-14T21:04:56.7792327Z 12513ab032b1: Download complete
2025-08-14T21:04:56.8551596Z 72da40fd831c: Verifying Checksum
2025-08-14T21:04:56.8552158Z 72da40fd831c: Download complete
2025-08-14T21:04:56.9405999Z 4ea4b6ca480f: Download complete
2025-08-14T21:04:56.9769922Z f6ff1c4ec221: Verifying Checksum
2025-08-14T21:04:56.9770925Z f6ff1c4ec221: Download complete
2025-08-14T21:04:57.0247749Z dea7b5130129: Verifying Checksum
2025-08-14T21:04:57.0248143Z dea7b5130129: Download complete
2025-08-14T21:04:57.0437015Z 7a90440a78c7: Download complete
2025-08-14T21:04:57.0518202Z 4f4fb700ef54: Verifying Checksum
2025-08-14T21:04:57.0518735Z 4f4fb700ef54: Download complete
2025-08-14T21:04:57.1306500Z ab642c9771e0: Verifying Checksum
2025-08-14T21:04:57.2012661Z d947308ec6c0: Download complete
2025-08-14T21:04:57.2862992Z 82f3234546b3: Download complete
2025-08-14T21:04:57.4015704Z 660ffc76f83b: Pull complete
2025-08-14T21:04:57.4225958Z a7ac6822069c: Pull complete
2025-08-14T21:04:57.4315211Z 960d25169df1: Verifying Checksum
2025-08-14T21:04:57.4315591Z 960d25169df1: Download complete
2025-08-14T21:04:57.5139637Z dbc40137a811: Download complete
2025-08-14T21:04:57.6004623Z 28d6214975c0: Verifying Checksum
2025-08-14T21:04:57.6005152Z 28d6214975c0: Download complete
2025-08-14T21:04:57.6763248Z e75d4694ae82: Verifying Checksum
2025-08-14T21:04:57.6763750Z e75d4694ae82: Download complete
2025-08-14T21:04:57.7567342Z c8fd1f66c221: Verifying Checksum
2025-08-14T21:04:57.7567983Z c8fd1f66c221: Download complete
2025-08-14T21:04:57.8339834Z 73a036f4a5d4: Download complete
2025-08-14T21:04:57.9242250Z 92c311949fb1: Verifying Checksum
2025-08-14T21:04:57.9242620Z 92c311949fb1: Download complete
2025-08-14T21:04:57.9967012Z 29f6cfbe4c15: Verifying Checksum
2025-08-14T21:04:57.9967983Z 29f6cfbe4c15: Download complete
2025-08-14T21:04:58.0972843Z fb6c7ee8061b: Download complete
2025-08-14T21:04:59.6187258Z 31f42505d41a: Verifying Checksum
2025-08-14T21:04:59.6187748Z 31f42505d41a: Download complete
2025-08-14T21:04:59.7138548Z 3ca1010f3846: Verifying Checksum
2025-08-14T21:04:59.7139141Z 3ca1010f3846: Download complete
2025-08-14T21:04:59.7879911Z 072215d97c72: Verifying Checksum
2025-08-14T21:04:59.7880546Z 072215d97c72: Download complete
2025-08-14T21:04:59.8594782Z 51a8de8f5ab2: Verifying Checksum
2025-08-14T21:04:59.8595441Z 51a8de8f5ab2: Download complete
2025-08-14T21:04:59.9529078Z 8a649a6063cf: Download complete
2025-08-14T21:05:00.1954431Z 6f5614ef0259: Verifying Checksum
2025-08-14T21:05:00.1955278Z 6f5614ef0259: Download complete
2025-08-14T21:05:00.2679270Z 5c0a31477213: Verifying Checksum
2025-08-14T21:05:00.2682049Z 5c0a31477213: Download complete
2025-08-14T21:05:00.3533291Z b9bc257d5af6: Verifying Checksum
2025-08-14T21:05:00.3534042Z b9bc257d5af6: Download complete
2025-08-14T21:05:00.4462917Z 4a977d8955e6: Verifying Checksum
2025-08-14T21:05:00.4463449Z 4a977d8955e6: Download complete
2025-08-14T21:05:00.5207336Z 32a65e5a5d0d: Verifying Checksum
2025-08-14T21:05:00.5207829Z 32a65e5a5d0d: Download complete
2025-08-14T21:05:00.6044786Z 88b9c7fbb7f5: Verifying Checksum
2025-08-14T21:05:00.6045259Z 88b9c7fbb7f5: Download complete
2025-08-14T21:05:00.6970148Z ad0aa3946f36: Download complete
2025-08-14T21:05:00.7760704Z f78553d91b8d: Download complete
2025-08-14T21:05:00.8641908Z 0b7ea6453230: Verifying Checksum
2025-08-14T21:05:00.8642504Z 0b7ea6453230: Download complete
2025-08-14T21:05:00.9466821Z 8330e7ea1b20: Verifying Checksum
2025-08-14T21:05:00.9468769Z 8330e7ea1b20: Download complete
2025-08-14T21:05:01.0246356Z e7aff2fc4378: Verifying Checksum
2025-08-14T21:05:01.0246742Z e7aff2fc4378: Download complete
2025-08-14T21:05:01.1143205Z 667e68628282: Verifying Checksum
2025-08-14T21:05:01.1143786Z 667e68628282: Download complete
2025-08-14T21:05:01.1970289Z 8b05e09cad0d: Download complete
2025-08-14T21:05:01.2873576Z a20271f3e135: Download complete
2025-08-14T21:05:01.3556247Z 6de635554f5b: Verifying Checksum
2025-08-14T21:05:01.3556833Z 6de635554f5b: Download complete
2025-08-14T21:05:01.4466654Z 2327901bebfd: Verifying Checksum
2025-08-14T21:05:01.4467316Z 2327901bebfd: Download complete
2025-08-14T21:05:01.5492799Z 0e1acd221de3: Verifying Checksum
2025-08-14T21:05:01.5493348Z 0e1acd221de3: Download complete
2025-08-14T21:05:01.6245745Z 883fad14abaf: Verifying Checksum
2025-08-14T21:05:01.6246272Z 883fad14abaf: Download complete
2025-08-14T21:05:01.6904954Z 3cdf0c0557b9: Verifying Checksum
2025-08-14T21:05:01.6905501Z 3cdf0c0557b9: Download complete
2025-08-14T21:05:01.7715276Z 49f35c818257: Verifying Checksum
2025-08-14T21:05:01.7715839Z 49f35c818257: Download complete
2025-08-14T21:05:01.8590658Z d7a2ef6024dc: Download complete
2025-08-14T21:05:01.9367439Z e069f49d0a35: Verifying Checksum
2025-08-14T21:05:01.9367977Z e069f49d0a35: Download complete
2025-08-14T21:05:02.6862591Z 0302c90f502f: Verifying Checksum
2025-08-14T21:05:02.6863108Z 0302c90f502f: Download complete
2025-08-14T21:05:02.7655965Z bebe10ca43f6: Download complete
2025-08-14T21:05:02.8615066Z adc4a16c409d: Verifying Checksum
2025-08-14T21:05:02.8615653Z adc4a16c409d: Download complete
2025-08-14T21:05:02.9495275Z b7028bbd1f0e: Download complete
2025-08-14T21:05:03.0298418Z 53acff155ed9: Verifying Checksum
2025-08-14T21:05:03.0299448Z 53acff155ed9: Download complete
2025-08-14T21:05:03.1231675Z dee80f9872f3: Download complete
2025-08-14T21:05:03.2073620Z a254ee8e6915: Verifying Checksum
2025-08-14T21:05:03.2074309Z a254ee8e6915: Download complete
2025-08-14T21:05:03.8040575Z e7bcb72e6b9e: Verifying Checksum
2025-08-14T21:05:03.8041213Z e7bcb72e6b9e: Download complete
2025-08-14T21:05:04.4104705Z c5150ca5ac67: Download complete
2025-08-14T21:05:08.5325776Z 31f42505d41a: Pull complete
2025-08-14T21:05:08.6614469Z fed7b1c3e821: Pull complete
2025-08-14T21:05:09.9937319Z f6ff1c4ec221: Pull complete
2025-08-14T21:05:10.0929540Z 2b3c95d5bdd3: Pull complete
2025-08-14T21:05:10.2122953Z 64e5c40daf9a: Pull complete
2025-08-14T21:05:10.3331718Z 0113773a5bba: Pull complete
2025-08-14T21:05:10.4496515Z 12513ab032b1: Pull complete
2025-08-14T21:05:10.6000398Z 72da40fd831c: Pull complete
2025-08-14T21:05:10.7096279Z 4ea4b6ca480f: Pull complete
2025-08-14T21:05:10.8189184Z dea7b5130129: Pull complete
2025-08-14T21:05:10.9383226Z 7a90440a78c7: Pull complete
2025-08-14T21:05:31.2039777Z 258d086c6347: Verifying Checksum
2025-08-14T21:05:31.2041102Z 258d086c6347: Download complete
2025-08-14T21:06:24.8199073Z 258d086c6347: Pull complete
2025-08-14T21:06:25.1268936Z 4f4fb700ef54: Pull complete
2025-08-14T21:06:25.3646893Z ab642c9771e0: Pull complete
2025-08-14T21:06:25.4882500Z d947308ec6c0: Pull complete
2025-08-14T21:06:25.6316196Z 82f3234546b3: Pull complete
2025-08-14T21:06:25.8446400Z 960d25169df1: Pull complete
2025-08-14T21:06:25.8686419Z dbc40137a811: Pull complete
2025-08-14T21:06:25.9906425Z 28d6214975c0: Pull complete
2025-08-14T21:06:26.0468269Z e75d4694ae82: Pull complete
2025-08-14T21:06:26.0930592Z c8fd1f66c221: Pull complete
2025-08-14T21:06:26.1883624Z 73a036f4a5d4: Pull complete
2025-08-14T21:06:26.2539947Z 92c311949fb1: Pull complete
2025-08-14T21:06:26.3118068Z 29f6cfbe4c15: Pull complete
2025-08-14T21:06:26.3382134Z fb6c7ee8061b: Pull complete
2025-08-14T21:06:37.9512563Z 0302c90f502f: Pull complete
2025-08-14T21:06:38.0848139Z 3ca1010f3846: Pull complete
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2025-08-14T21:06:38.2063097Z 51a8de8f5ab2: Pull complete
2025-08-14T21:06:38.2295204Z 8a649a6063cf: Pull complete
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2025-08-14T21:06:38.9247291Z 4a977d8955e6: Pull complete
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2025-08-14T21:06:39.0831978Z 88b9c7fbb7f5: Pull complete
2025-08-14T21:06:39.4736181Z ad0aa3946f36: Pull complete
2025-08-14T21:06:39.4957759Z f78553d91b8d: Pull complete
2025-08-14T21:06:39.5376524Z 0b7ea6453230: Pull complete
2025-08-14T21:06:39.5581368Z 8330e7ea1b20: Pull complete
2025-08-14T21:06:39.5999948Z e7aff2fc4378: Pull complete
2025-08-14T21:06:39.6418696Z 667e68628282: Pull complete
2025-08-14T21:06:39.6660907Z 8b05e09cad0d: Pull complete
2025-08-14T21:06:39.7073100Z a20271f3e135: Pull complete
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2025-08-14T21:06:39.7697336Z 2327901bebfd: Pull complete
2025-08-14T21:06:39.8117332Z 0e1acd221de3: Pull complete
2025-08-14T21:06:39.8327005Z 883fad14abaf: Pull complete
2025-08-14T21:06:39.8733436Z 3cdf0c0557b9: Pull complete
2025-08-14T21:06:39.8941035Z 49f35c818257: Pull complete
2025-08-14T21:06:39.9373164Z d7a2ef6024dc: Pull complete
2025-08-14T21:06:39.9596139Z e069f49d0a35: Pull complete
2025-08-14T21:06:46.7664504Z c5150ca5ac67: Pull complete
2025-08-14T21:06:46.9272327Z bebe10ca43f6: Pull complete
2025-08-14T21:06:47.0036042Z adc4a16c409d: Pull complete
2025-08-14T21:06:47.0595337Z b7028bbd1f0e: Pull complete
2025-08-14T21:06:47.0923849Z 53acff155ed9: Pull complete
2025-08-14T21:06:47.1190372Z dee80f9872f3: Pull complete
2025-08-14T21:06:47.1709667Z a254ee8e6915: Pull complete
2025-08-14T21:06:49.0574825Z e7bcb72e6b9e: Pull complete
2025-08-14T21:06:49.2151106Z Digest: sha256:e5a191418e9f11a59a218b040bad54b9c3113ac41271ba5a6874e1c6d47db7c7
2025-08-14T21:06:49.2398239Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:06:49.2440492Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:06:49.2482268Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:06:49.2483280Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-08-14T21:06:49.2490428Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:06:49.2490811Z env:
2025-08-14T21:06:49.2491036Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:49.2491309Z ##[endgroup]
2025-08-14T21:06:49.2621023Z Prepare all required actions
2025-08-14T21:06:49.2740190Z ##[group]Run ./.github/actions/get-workflow-job-id
2025-08-14T21:06:49.2740563Z with:
2025-08-14T21:06:49.2741311Z   github-token: ***
2025-08-14T21:06:49.2741542Z env:
2025-08-14T21:06:49.2741768Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:49.2742043Z ##[endgroup]
2025-08-14T21:06:49.2788745Z ##[group]Run set -eux
2025-08-14T21:06:49.2789058Z set -eux
2025-08-14T21:06:49.2789519Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-08-14T21:06:49.2796130Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:06:49.2796731Z env:
2025-08-14T21:06:49.2797035Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:49.2797552Z   GITHUB_TOKEN: ***
2025-08-14T21:06:49.2797784Z ##[endgroup]
2025-08-14T21:06:49.2822148Z + python3 .github/scripts/get_workflow_job_id.py 16976255017 i-02d6cf458b1433fa4
2025-08-14T21:06:50.6757627Z Setting output job-id=48127032084
2025-08-14T21:06:50.6758370Z Setting output job-name=linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:06:50.6949353Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
2025-08-14T21:06:50.6950123Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
2025-08-14T21:06:50.6951117Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
2025-08-14T21:06:50.6952091Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
2025-08-14T21:06:50.6958483Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:06:50.6958898Z env:
2025-08-14T21:06:50.6959127Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:50.6959388Z   JOB_ID: 48127032084
2025-08-14T21:06:50.6959791Z   JOB_NAME: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:06:50.6960267Z   WORKFLOW_NAME: pull
2025-08-14T21:06:50.6960523Z   WORKFLOW_RUN_ID: 16976255017
2025-08-14T21:06:50.6960859Z   MONITOR_LOG_INTERVAL: 5
2025-08-14T21:06:50.6961131Z   MONITOR_DATA_COLLECT_INTERVAL: 1
2025-08-14T21:06:50.6961430Z ##[endgroup]
2025-08-14T21:06:51.9592085Z Defaulting to user installation because normal site-packages is not writeable
2025-08-14T21:06:52.4301226Z Collecting psutil==5.9.8
2025-08-14T21:06:52.4485233Z   Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (288 kB)
2025-08-14T21:06:52.5574668Z Collecting dataclasses_json==0.6.7
2025-08-14T21:06:52.5613848Z   Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB)
2025-08-14T21:06:52.5926632Z Collecting nvidia-ml-py==11.525.84
2025-08-14T21:06:52.5963887Z   Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB)
2025-08-14T21:06:52.7297610Z Collecting marshmallow<4.0.0,>=3.18.0
2025-08-14T21:06:52.7335931Z   Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB)
2025-08-14T21:06:52.7720155Z Collecting typing-inspect<1,>=0.4.0
2025-08-14T21:06:52.7755098Z   Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)
2025-08-14T21:06:52.8470127Z Collecting packaging>=17.0
2025-08-14T21:06:52.8508406Z   Downloading packaging-25.0-py3-none-any.whl (66 kB)
2025-08-14T21:06:52.9284799Z Collecting mypy-extensions>=0.3.0
2025-08-14T21:06:52.9320072Z   Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB)
2025-08-14T21:06:53.0207032Z Collecting typing-extensions>=3.7.4
2025-08-14T21:06:53.0243990Z   Downloading typing_extensions-4.14.1-py3-none-any.whl (43 kB)
2025-08-14T21:06:53.2648299Z Installing collected packages: typing-extensions, packaging, mypy-extensions, typing-inspect, marshmallow, psutil, nvidia-ml-py, dataclasses-json
2025-08-14T21:06:53.8901268Z Successfully installed dataclasses-json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.8 typing-extensions-4.14.1 typing-inspect-0.9.0
2025-08-14T21:06:54.1392593Z Prepare all required actions
2025-08-14T21:06:54.1393016Z Getting action download info
2025-08-14T21:06:54.2798393Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6)
2025-08-14T21:06:54.9348449Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093)
2025-08-14T21:06:55.4391771Z ##[group]Run ./.github/actions/download-build-artifacts
2025-08-14T21:06:55.4392150Z with:
2025-08-14T21:06:55.4392393Z   name: linux-jammy-py3.13-clang12
2025-08-14T21:06:55.4392695Z   s3-bucket: gha-artifacts
2025-08-14T21:06:55.4392967Z env:
2025-08-14T21:06:55.4393192Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:55.4393463Z ##[endgroup]
2025-08-14T21:06:55.4427673Z ##[group]Run seemethere/download-artifact-s3@v4
2025-08-14T21:06:55.4428029Z with:
2025-08-14T21:06:55.4428271Z   name: linux-jammy-py3.13-clang12
2025-08-14T21:06:55.4428587Z   s3-bucket: gha-artifacts
2025-08-14T21:06:55.4428892Z   region: us-east-1
2025-08-14T21:06:55.4429112Z env:
2025-08-14T21:06:55.4429328Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:06:55.4429589Z ##[endgroup]
2025-08-14T21:06:55.9081298Z (node:41610) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023.
2025-08-14T21:06:55.9081839Z 
2025-08-14T21:06:55.9082037Z Please migrate your code to use AWS SDK for JavaScript (v3).
2025-08-14T21:06:55.9082609Z For more information, check the migration guide at https://a.co/7PzMCcy
2025-08-14T21:06:55.9083198Z (Use `node --trace-warnings ...` to show where the warning was created)
2025-08-14T21:06:56.1002826Z Found 1 objects with prefix pytorch/pytorch/16976255017/linux-jammy-py3.13-clang12/
2025-08-14T21:06:56.1003601Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip
2025-08-14T21:07:00.7357417Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip
2025-08-14T21:07:00.7363404Z Artifact download has finished successfully
2025-08-14T21:07:00.7543245Z ##[group]Run unzip -o artifacts.zip
2025-08-14T21:07:00.7543597Z unzip -o artifacts.zip
2025-08-14T21:07:00.7549965Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:00.7550350Z env:
2025-08-14T21:07:00.7550574Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:00.7550852Z ##[endgroup]
2025-08-14T21:07:00.8033284Z Archive:  artifacts.zip
2025-08-14T21:07:00.8033963Z    creating: dist/
2025-08-14T21:07:01.9440364Z   inflating: dist/torch-2.9.0a0+git1fc683c-cp313-cp313-linux_x86_64.whl  
2025-08-14T21:07:01.9556766Z   inflating: dist/.ninja_log         
2025-08-14T21:07:01.9557614Z    creating: build/custom_test_artifacts/
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2025-08-14T21:07:07.5225632Z   inflating: build/bin/cpu_allocator_test  
2025-08-14T21:07:07.5280361Z   inflating: build/bin/cpu_generator_test  
2025-08-14T21:07:07.5331290Z   inflating: build/bin/cpu_profiling_allocator_test  
2025-08-14T21:07:07.5419992Z   inflating: build/bin/cpu_rng_test  
2025-08-14T21:07:07.5469607Z   inflating: build/bin/dlconvertor_test  
2025-08-14T21:07:07.5525955Z   inflating: build/bin/extension_backend_test  
2025-08-14T21:07:07.5576791Z   inflating: build/bin/half_test     
2025-08-14T21:07:07.5671232Z   inflating: build/bin/ivalue_test   
2025-08-14T21:07:07.5719581Z   inflating: build/bin/lazy_tensor_test  
2025-08-14T21:07:07.5770676Z   inflating: build/bin/math_kernel_test  
2025-08-14T21:07:07.5822043Z   inflating: build/bin/memory_format_test  
2025-08-14T21:07:07.5872622Z   inflating: build/bin/memory_overlapping_test  
2025-08-14T21:07:07.5923617Z   inflating: build/bin/mobile_memory_cleanup  
2025-08-14T21:07:07.5978374Z   inflating: build/bin/native_test   
2025-08-14T21:07:07.6027429Z   inflating: build/bin/operator_name_test  
2025-08-14T21:07:07.6076729Z   inflating: build/bin/operators_test  
2025-08-14T21:07:07.6146756Z   inflating: build/bin/pow_test      
2025-08-14T21:07:07.6196262Z   inflating: build/bin/packedtensoraccessor_test  
2025-08-14T21:07:07.6251141Z   inflating: build/bin/quantized_test  
2025-08-14T21:07:07.6299777Z   inflating: build/bin/reduce_ops_test  
2025-08-14T21:07:07.6348800Z   inflating: build/bin/reportMemoryUsage_test  
2025-08-14T21:07:07.6402979Z   inflating: build/bin/scalar_tensor_test  
2025-08-14T21:07:07.6459023Z   inflating: build/bin/scalar_test   
2025-08-14T21:07:07.6508002Z   inflating: build/bin/StorageUtils_test  
2025-08-14T21:07:07.6558606Z   inflating: build/bin/stride_properties_test  
2025-08-14T21:07:07.6636268Z   inflating: build/bin/tensor_iterator_test  
2025-08-14T21:07:07.6687657Z   inflating: build/bin/test_parallel  
2025-08-14T21:07:07.6736313Z   inflating: build/bin/thread_init_test  
2025-08-14T21:07:07.6786734Z   inflating: build/bin/type_ptr_test  
2025-08-14T21:07:07.6836779Z   inflating: build/bin/undefined_tensor_test  
2025-08-14T21:07:07.6894648Z   inflating: build/bin/type_test     
2025-08-14T21:07:07.6942432Z   inflating: build/bin/verify_api_visibility  
2025-08-14T21:07:07.7013840Z   inflating: build/bin/legacy_vmap_test  
2025-08-14T21:07:07.7063188Z   inflating: build/bin/weakref_test  
2025-08-14T21:07:07.7113090Z   inflating: build/bin/wrapdim_test  
2025-08-14T21:07:07.7162671Z   inflating: build/bin/xla_tensor_test  
2025-08-14T21:07:07.7219711Z   inflating: build/bin/IListRef_test  
2025-08-14T21:07:07.7313317Z   inflating: build/bin/List_test     
2025-08-14T21:07:07.7374652Z   inflating: build/bin/KernelFunction_test  
2025-08-14T21:07:07.7498740Z   inflating: build/bin/kernel_function_legacy_test  
2025-08-14T21:07:07.7591804Z   inflating: build/bin/kernel_function_test  
2025-08-14T21:07:07.7691233Z   inflating: build/bin/kernel_lambda_test  
2025-08-14T21:07:07.7818122Z   inflating: build/bin/kernel_lambda_legacy_test  
2025-08-14T21:07:07.7876219Z   inflating: build/bin/kernel_stackbased_test  
2025-08-14T21:07:07.7970239Z   inflating: build/bin/make_boxed_from_unboxed_functor_test  
2025-08-14T21:07:07.8018935Z   inflating: build/bin/CppSignature_test  
2025-08-14T21:07:07.8071363Z   inflating: build/bin/backend_fallback_test  
2025-08-14T21:07:07.8119034Z   inflating: build/bin/op_allowlist_test  
2025-08-14T21:07:07.8418537Z   inflating: build/bin/op_registration_test  
2025-08-14T21:07:07.8480545Z   inflating: build/bin/inline_container_test  
2025-08-14T21:07:07.8750483Z   inflating: build/bin/test_nativert  
2025-08-14T21:07:07.8815050Z   inflating: build/bin/ProcessGroupGlooTest  
2025-08-14T21:07:07.8817934Z   inflating: build/bin/example_allreduce  
2025-08-14T21:07:07.9864014Z   inflating: build/bin/test_jit      
2025-08-14T21:07:07.9917436Z   inflating: build/bin/test_dist_autograd  
2025-08-14T21:07:07.9981963Z   inflating: build/bin/test_cpp_rpc  
2025-08-14T21:07:08.1245288Z   inflating: build/bin/test_api      
2025-08-14T21:07:08.1246877Z   inflating: build/bin/parallel_benchmark  
2025-08-14T21:07:08.1558803Z   inflating: build/bin/test_lazy     
2025-08-14T21:07:08.1562799Z   inflating: build/bin/torch_shm_manager  
2025-08-14T21:07:08.1563464Z    creating: .additional_ci_files/
2025-08-14T21:07:08.1640137Z   inflating: .additional_ci_files/test-times.json  
2025-08-14T21:07:08.1932228Z   inflating: .additional_ci_files/test-class-times.json  
2025-08-14T21:07:08.1958433Z ##[group]Run rm artifacts.zip
2025-08-14T21:07:08.1958778Z rm artifacts.zip
2025-08-14T21:07:08.1964668Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:08.1965057Z env:
2025-08-14T21:07:08.1965281Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:08.1965559Z ##[endgroup]
2025-08-14T21:07:08.2456978Z ##[group]Run df -H
2025-08-14T21:07:08.2457263Z df -H
2025-08-14T21:07:08.2463131Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:08.2463520Z env:
2025-08-14T21:07:08.2463750Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:08.2464021Z ##[endgroup]
2025-08-14T21:07:08.2634751Z Filesystem        Size  Used Avail Use% Mounted on
2025-08-14T21:07:08.2635349Z devtmpfs          4.2M     0  4.2M   0% /dev
2025-08-14T21:07:08.2635723Z tmpfs             8.2G     0  8.2G   0% /dev/shm
2025-08-14T21:07:08.2636075Z tmpfs             3.3G  484k  3.3G   1% /run
2025-08-14T21:07:08.2636411Z /dev/nvme0n1p1    161G   27G  135G  17% /
2025-08-14T21:07:08.2636990Z tmpfs             8.2G   13k  8.2G   1% /tmp
2025-08-14T21:07:08.2637461Z /dev/nvme0n1p128   11M  1.4M  9.2M  13% /boot/efi
2025-08-14T21:07:08.2702388Z Prepare all required actions
2025-08-14T21:07:08.2703173Z Getting action download info
2025-08-14T21:07:08.4046530Z ##[group]Run ./.github/actions/download-td-artifacts
2025-08-14T21:07:08.4046905Z with:
2025-08-14T21:07:08.4047132Z env:
2025-08-14T21:07:08.4047357Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:08.4047619Z ##[endgroup]
2025-08-14T21:07:08.4089264Z ##[group]Run seemethere/download-artifact-s3@v4
2025-08-14T21:07:08.4089611Z with:
2025-08-14T21:07:08.4089833Z   name: td_results
2025-08-14T21:07:08.4090082Z   s3-bucket: gha-artifacts
2025-08-14T21:07:08.4090343Z   region: us-east-1
2025-08-14T21:07:08.4090735Z env:
2025-08-14T21:07:08.4090955Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:08.4091221Z ##[endgroup]
2025-08-14T21:07:08.8694318Z (node:41627) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023.
2025-08-14T21:07:08.8694843Z 
2025-08-14T21:07:08.8695110Z Please migrate your code to use AWS SDK for JavaScript (v3).
2025-08-14T21:07:08.8695663Z For more information, check the migration guide at https://a.co/7PzMCcy
2025-08-14T21:07:08.8696241Z (Use `node --trace-warnings ...` to show where the warning was created)
2025-08-14T21:07:08.9809364Z Found 1 objects with prefix pytorch/pytorch/16976255017/td_results/
2025-08-14T21:07:08.9810213Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json
2025-08-14T21:07:09.0350266Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json
2025-08-14T21:07:09.0355310Z Artifact download has finished successfully
2025-08-14T21:07:09.0536238Z ##[group]Run mkdir -p .additional_ci_files
2025-08-14T21:07:09.0536615Z mkdir -p .additional_ci_files
2025-08-14T21:07:09.0537073Z mv td_results.json .additional_ci_files/td_results.json || true
2025-08-14T21:07:09.0542797Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:09.0543178Z env:
2025-08-14T21:07:09.0543422Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:09.0543697Z ##[endgroup]
2025-08-14T21:07:09.0630407Z ##[group]Run .github/scripts/parse_ref.py
2025-08-14T21:07:09.0630790Z .github/scripts/parse_ref.py
2025-08-14T21:07:09.0636302Z shell: /usr/bin/bash -e {0}
2025-08-14T21:07:09.0636592Z env:
2025-08-14T21:07:09.0636824Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:09.0637191Z ##[endgroup]
2025-08-14T21:07:09.0846326Z Setting output branch=main
2025-08-14T21:07:09.0980742Z Prepare all required actions
2025-08-14T21:07:09.0981159Z Getting action download info
2025-08-14T21:07:09.2242864Z ##[group]Run ./.github/actions/filter-test-configs
2025-08-14T21:07:09.2243249Z with:
2025-08-14T21:07:09.2243756Z   github-token: ***
2025-08-14T21:07:09.2246727Z   test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}
2025-08-14T21:07:09.2249892Z   job-name: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:09.2250364Z env:
2025-08-14T21:07:09.2250575Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:09.2250850Z ##[endgroup]
2025-08-14T21:07:09.2294868Z ##[group]Run nick-fields/retry@v3.0.0
2025-08-14T21:07:09.2295184Z with:
2025-08-14T21:07:09.2295400Z   shell: bash
2025-08-14T21:07:09.2295634Z   timeout_minutes: 10
2025-08-14T21:07:09.2295880Z   max_attempts: 5
2025-08-14T21:07:09.2296130Z   retry_wait_seconds: 30
2025-08-14T21:07:09.2296949Z   command: set -eux
# PyYAML 6.0 doesn't work with MacOS x86 anymore
# This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2
python3 -m pip install requests==2.27.1 pyyaml==6.0.2

2025-08-14T21:07:09.2297878Z   polling_interval_seconds: 1
2025-08-14T21:07:09.2298164Z   warning_on_retry: true
2025-08-14T21:07:09.2298442Z   continue_on_error: false
2025-08-14T21:07:09.2298715Z env:
2025-08-14T21:07:09.2299090Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:09.2299567Z   GITHUB_TOKEN: ***
2025-08-14T21:07:09.2299813Z ##[endgroup]
2025-08-14T21:07:09.3231019Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2
2025-08-14T21:07:09.5656964Z Defaulting to user installation because normal site-packages is not writeable
2025-08-14T21:07:09.6836194Z Collecting requests==2.27.1
2025-08-14T21:07:09.6994999Z   Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)
2025-08-14T21:07:09.8560792Z Collecting pyyaml==6.0.2
2025-08-14T21:07:09.8597665Z   Downloading PyYAML-6.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (737 kB)
2025-08-14T21:07:09.9281658Z Collecting certifi>=2017.4.17
2025-08-14T21:07:09.9317942Z   Downloading certifi-2025.8.3-py3-none-any.whl (161 kB)
2025-08-14T21:07:10.2816607Z Collecting charset-normalizer~=2.0.0
2025-08-14T21:07:10.2855676Z   Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB)
2025-08-14T21:07:10.2904763Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (1.25.10)
2025-08-14T21:07:10.2916808Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (2.10)
2025-08-14T21:07:10.3763808Z Installing collected packages: charset-normalizer, certifi, requests, pyyaml
2025-08-14T21:07:10.4963516Z Successfully installed certifi-2025.8.3 charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1
2025-08-14T21:07:11.3060377Z Command completed after 1 attempt(s).
2025-08-14T21:07:11.3115320Z ##[group]Run set -x
2025-08-14T21:07:11.3115601Z set -x
2025-08-14T21:07:11.3115836Z 
2025-08-14T21:07:11.3116220Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-08-14T21:07:11.3116893Z # in runner workspace
2025-08-14T21:07:11.3117302Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py"
2025-08-14T21:07:11.3123207Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:11.3123603Z env:
2025-08-14T21:07:11.3123826Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.3124097Z ##[endgroup]
2025-08-14T21:07:11.3147579Z + python3 /home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py
2025-08-14T21:07:11.3324710Z Setting output branch=main
2025-08-14T21:07:11.3391643Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}"
2025-08-14T21:07:11.3392340Z echo "Workflow: ${GITHUB_WORKFLOW}"
2025-08-14T21:07:11.3392908Z echo "Job name: ${JOB_NAME}"
2025-08-14T21:07:11.3393416Z 
2025-08-14T21:07:11.3393998Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-08-14T21:07:11.3394804Z # in runner workspace
2025-08-14T21:07:11.3395319Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \
2025-08-14T21:07:11.3395830Z   --workflow "${GITHUB_WORKFLOW}" \
2025-08-14T21:07:11.3396182Z   --job-name "${JOB_NAME}" \
2025-08-14T21:07:11.3399244Z   --test-matrix "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}" \
2025-08-14T21:07:11.3402529Z   --selected-test-configs "" \
2025-08-14T21:07:11.3402885Z   --pr-number "${PR_NUMBER}" \
2025-08-14T21:07:11.3403225Z   --tag "${TAG}" \
2025-08-14T21:07:11.3403520Z   --event-name "${EVENT_NAME}" \
2025-08-14T21:07:11.3403869Z   --schedule "${SCHEDULE}" \
2025-08-14T21:07:11.3404200Z   --branch "${HEAD_BRANCH}"
2025-08-14T21:07:11.3410681Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:11.3411082Z env:
2025-08-14T21:07:11.3411318Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.3411991Z   GITHUB_TOKEN: ***
2025-08-14T21:07:11.3412556Z   JOB_NAME: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:11.3413300Z   PR_NUMBER: 
2025-08-14T21:07:11.3413538Z   TAG: 
2025-08-14T21:07:11.3413758Z   EVENT_NAME: push
2025-08-14T21:07:11.3413997Z   SCHEDULE: 
2025-08-14T21:07:11.3414224Z   HEAD_BRANCH: main
2025-08-14T21:07:11.3414456Z ##[endgroup]
2025-08-14T21:07:11.3439142Z Workflow: pull
2025-08-14T21:07:11.3439594Z Job name: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:11.5374292Z Setting output keep-going=True
2025-08-14T21:07:11.5374667Z Setting output ci-verbose-test-logs=False
2025-08-14T21:07:11.5375038Z Setting output ci-test-showlocals=False
2025-08-14T21:07:11.5375395Z Setting output ci-no-test-timeout=False
2025-08-14T21:07:11.5375721Z Setting output ci-no-td=False
2025-08-14T21:07:11.5376040Z Setting output ci-td-distributed=False
2025-08-14T21:07:11.5376380Z Setting output is-unstable=False
2025-08-14T21:07:11.5376684Z Setting output reenabled-issues=
2025-08-14T21:07:11.5380000Z Setting output test-matrix={"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}
2025-08-14T21:07:11.5383134Z Setting output is-test-matrix-empty=False
2025-08-14T21:07:11.5522488Z ##[group]Run echo "Filtered matrix:"
2025-08-14T21:07:11.5522867Z echo "Filtered matrix:"
2025-08-14T21:07:11.5525865Z echo "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}"
2025-08-14T21:07:11.5528842Z 
2025-08-14T21:07:11.5529063Z echo
2025-08-14T21:07:11.5529338Z echo "Is the current job unstable? False"
2025-08-14T21:07:11.5529686Z 
2025-08-14T21:07:11.5530050Z echo
2025-08-14T21:07:11.5530302Z echo "Is keep-going label set? True"
2025-08-14T21:07:11.5530640Z 
2025-08-14T21:07:11.5530853Z echo
2025-08-14T21:07:11.5531088Z echo "Reenabled issues? "
2025-08-14T21:07:11.5536845Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:11.5537243Z env:
2025-08-14T21:07:11.5537459Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.5551909Z ##[endgroup]
2025-08-14T21:07:11.5575650Z Filtered matrix:
2025-08-14T21:07:11.5579608Z {include: [{config: default, shard: 1, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 2, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 3, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 4, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 5, num_shards: 5, runner: lf.linux.4xlarge}, {config: crossref, shard: 1, num_shards: 2, runner: lf.linux.2xlarge}, {config: crossref, shard: 2, num_shards: 2, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 1, num_shards: 3, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 2, num_shards: 3, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 3, num_shards: 3, runner: lf.linux.2xlarge}, {config: einops, shard: 1, num_shards: 1, runner: lf.linux.2xlarge}]}
2025-08-14T21:07:11.5582438Z 
2025-08-14T21:07:11.5582570Z Is the current job unstable? False
2025-08-14T21:07:11.5582777Z 
2025-08-14T21:07:11.5582886Z Is keep-going label set? True
2025-08-14T21:07:11.5583084Z 
2025-08-14T21:07:11.5583177Z Reenabled issues? 
2025-08-14T21:07:11.5629344Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-08-14T21:07:11.5629888Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-08-14T21:07:11.5635484Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:11.5635862Z env:
2025-08-14T21:07:11.5636083Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.5636353Z   JOB_TIMEOUT: 240
2025-08-14T21:07:11.5636597Z ##[endgroup]
2025-08-14T21:07:11.5689572Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:07:11.5690114Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:07:11.5690583Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-08-14T21:07:11.5695706Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T21:07:11.5696103Z env:
2025-08-14T21:07:11.5696328Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.5696595Z ##[endgroup]
2025-08-14T21:07:11.5792636Z ##[group]Run set -x
2025-08-14T21:07:11.5792989Z set -x
2025-08-14T21:07:11.5793212Z 
2025-08-14T21:07:11.5793476Z if [[ $TEST_CONFIG == 'multigpu' ]]; then
2025-08-14T21:07:11.5793886Z   TEST_COMMAND=.ci/pytorch/multigpu-test.sh
2025-08-14T21:07:11.5794288Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then
2025-08-14T21:07:11.5794664Z   TEST_COMMAND=.ci/onnx/test.sh
2025-08-14T21:07:11.5794993Z else
2025-08-14T21:07:11.5795255Z   TEST_COMMAND=.ci/pytorch/test.sh
2025-08-14T21:07:11.5795565Z fi
2025-08-14T21:07:11.5795778Z 
2025-08-14T21:07:11.5796056Z # Leaving 1GB for the runner and other things
2025-08-14T21:07:11.5796645Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo)
2025-08-14T21:07:11.5797556Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap
2025-08-14T21:07:11.5798290Z # comes from https://github.com/pytorch/test-infra/pull/6058
2025-08-14T21:07:11.5798836Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3))
2025-08-14T21:07:11.5799270Z 
2025-08-14T21:07:11.5799546Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
2025-08-14T21:07:11.5799891Z   SHM_OPTS=
2025-08-14T21:07:11.5800146Z   JENKINS_USER=
2025-08-14T21:07:11.5800633Z   # ensure that docker container cleanly exits in 12 hours
2025-08-14T21:07:11.5801123Z   # if for some reason cleanup action doesn't stop container
2025-08-14T21:07:11.5801537Z   # when job is cancelled
2025-08-14T21:07:11.5801856Z   DOCKER_SHELL_CMD="sleep 12h"
2025-08-14T21:07:11.5802168Z else
2025-08-14T21:07:11.5802414Z   SHM_OPTS="--shm-size=${SHM_SIZE}"
2025-08-14T21:07:11.5802764Z   JENKINS_USER="--user jenkins"
2025-08-14T21:07:11.5803099Z   DOCKER_SHELL_CMD=
2025-08-14T21:07:11.5803356Z fi
2025-08-14T21:07:11.5803569Z 
2025-08-14T21:07:11.5803911Z # detached container should get cleaned up by teardown_ec2_linux
2025-08-14T21:07:11.5804455Z # TODO: Stop building test binaries as part of the build phase
2025-08-14T21:07:11.5805091Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice
2025-08-14T21:07:11.5805647Z # shellcheck disable=SC2086,SC2090
2025-08-14T21:07:11.5806000Z container_name=$(docker run \
2025-08-14T21:07:11.5806310Z   ${GPU_FLAG:-} \
2025-08-14T21:07:11.5806623Z   ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \
2025-08-14T21:07:11.5806973Z   -e BUILD_ENVIRONMENT \
2025-08-14T21:07:11.5807264Z   -e PR_NUMBER \
2025-08-14T21:07:11.5807544Z   -e GITHUB_ACTIONS \
2025-08-14T21:07:11.5807844Z   -e GITHUB_REPOSITORY \
2025-08-14T21:07:11.5808159Z   -e GITHUB_WORKFLOW \
2025-08-14T21:07:11.5808447Z   -e GITHUB_JOB \
2025-08-14T21:07:11.5808728Z   -e GITHUB_RUN_ID \
2025-08-14T21:07:11.5809236Z   -e GITHUB_RUN_NUMBER \
2025-08-14T21:07:11.5809547Z   -e GITHUB_RUN_ATTEMPT \
2025-08-14T21:07:11.5809854Z   -e JOB_ID \
2025-08-14T21:07:11.5810116Z   -e JOB_NAME \
2025-08-14T21:07:11.5810375Z   -e BASE_SHA \
2025-08-14T21:07:11.5810644Z   -e BRANCH \
2025-08-14T21:07:11.5810907Z   -e SHA1 \
2025-08-14T21:07:11.5811152Z   -e AWS_DEFAULT_REGION \
2025-08-14T21:07:11.5811457Z   -e IN_WHEEL_TEST \
2025-08-14T21:07:11.5811737Z   -e SHARD_NUMBER \
2025-08-14T21:07:11.5812019Z   -e TEST_CONFIG \
2025-08-14T21:07:11.5812290Z   -e NUM_TEST_SHARDS \
2025-08-14T21:07:11.5812589Z   -e REENABLED_ISSUES \
2025-08-14T21:07:11.5812901Z   -e CONTINUE_THROUGH_ERROR \
2025-08-14T21:07:11.5813365Z   -e VERBOSE_TEST_LOGS \
2025-08-14T21:07:11.5813674Z   -e TEST_SHOWLOCALS \
2025-08-14T21:07:11.5813976Z   -e NO_TEST_TIMEOUT \
2025-08-14T21:07:11.5814250Z   -e NO_TD \
2025-08-14T21:07:11.5814515Z   -e TD_DISTRIBUTED \
2025-08-14T21:07:11.5814808Z   -e PR_LABELS \
2025-08-14T21:07:11.5815117Z   -e MAX_JOBS="$(nproc --ignore=2)" \
2025-08-14T21:07:11.5815450Z   -e SCCACHE_BUCKET \
2025-08-14T21:07:11.5815750Z   -e SCCACHE_REGION \
2025-08-14T21:07:11.5816035Z   -e XLA_CUDA \
2025-08-14T21:07:11.5816320Z   -e XLA_CLANG_CACHE_S3_BUCKET_NAME \
2025-08-14T21:07:11.5816693Z   -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \
2025-08-14T21:07:11.5817075Z   -e PYTORCH_TEST_RERUN_DISABLED_TESTS \
2025-08-14T21:07:11.5817443Z   -e SKIP_SCCACHE_INITIALIZATION=1 \
2025-08-14T21:07:11.5817793Z   -e HUGGING_FACE_HUB_TOKEN \
2025-08-14T21:07:11.5818136Z   -e SCRIBE_GRAPHQL_ACCESS_TOKEN \
2025-08-14T21:07:11.5818476Z   -e DASHBOARD_TAG \
2025-08-14T21:07:11.5818761Z   -e ARTIFACTS_FILE_SUFFIX \
2025-08-14T21:07:11.5819135Z   --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
2025-08-14T21:07:11.5819565Z   --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
2025-08-14T21:07:11.5819983Z   --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
2025-08-14T21:07:11.5820392Z   --security-opt seccomp=unconfined \
2025-08-14T21:07:11.5820837Z   --cap-add=SYS_PTRACE \
2025-08-14T21:07:11.5821142Z   --ipc=host \
2025-08-14T21:07:11.5821445Z   ${SHM_OPTS} \
2025-08-14T21:07:11.5821756Z   --tty \
2025-08-14T21:07:11.5821997Z   --detach \
2025-08-14T21:07:11.5822258Z   --name="${container_name}" \
2025-08-14T21:07:11.5822582Z   ${JENKINS_USER} \
2025-08-14T21:07:11.5822943Z   -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
2025-08-14T21:07:11.5823354Z   -w /var/lib/jenkins/workspace \
2025-08-14T21:07:11.5823686Z   "${DOCKER_IMAGE}" \
2025-08-14T21:07:11.5823978Z   ${DOCKER_SHELL_CMD}
2025-08-14T21:07:11.5824243Z )
2025-08-14T21:07:11.5824548Z # Propagate download.pytorch.org IP to container
2025-08-14T21:07:11.5825247Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts"
2025-08-14T21:07:11.5825992Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
2025-08-14T21:07:11.5826405Z 
2025-08-14T21:07:11.5826682Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
2025-08-14T21:07:11.5827281Z   docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt"
2025-08-14T21:07:11.5827814Z fi
2025-08-14T21:07:11.5828018Z 
2025-08-14T21:07:11.5828525Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"
2025-08-14T21:07:11.5834128Z shell: /usr/bin/bash -e {0}
2025-08-14T21:07:11.5834398Z env:
2025-08-14T21:07:11.5834624Z   GIT_DEFAULT_BRANCH: main
2025-08-14T21:07:11.5834948Z   BUILD_ENVIRONMENT: linux-jammy-py3.13-clang12
2025-08-14T21:07:11.5835282Z   PR_NUMBER: 
2025-08-14T21:07:11.5835537Z   GITHUB_REPOSITORY: pytorch/pytorch
2025-08-14T21:07:11.5835856Z   GITHUB_WORKFLOW: pull
2025-08-14T21:07:11.5836100Z   GITHUB_JOB: test
2025-08-14T21:07:11.5836359Z   GITHUB_RUN_ID: 16976255017
2025-08-14T21:07:11.5836640Z   GITHUB_RUN_NUMBER: 346100
2025-08-14T21:07:11.5836913Z   GITHUB_RUN_ATTEMPT: 1
2025-08-14T21:07:11.5837154Z   JOB_ID: 48127032084
2025-08-14T21:07:11.5837558Z   JOB_NAME: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:11.5838021Z   BRANCH: main
2025-08-14T21:07:11.5838271Z   SHA1: 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:11.5838651Z   BASE_SHA: 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:11.5839102Z   TEST_CONFIG: crossref
2025-08-14T21:07:11.5839343Z   SHARD_NUMBER: 1
2025-08-14T21:07:11.5839585Z   NUM_TEST_SHARDS: 2
2025-08-14T21:07:11.5839831Z   REENABLED_ISSUES: 
2025-08-14T21:07:11.5840081Z   CONTINUE_THROUGH_ERROR: True
2025-08-14T21:07:11.5840374Z   VERBOSE_TEST_LOGS: False
2025-08-14T21:07:11.5840653Z   TEST_SHOWLOCALS: False
2025-08-14T21:07:11.5840929Z   NO_TEST_TIMEOUT: False
2025-08-14T21:07:11.5841172Z   NO_TD: False
2025-08-14T21:07:11.5841421Z   TD_DISTRIBUTED: False
2025-08-14T21:07:11.5841748Z   SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
2025-08-14T21:07:11.5842109Z   SCCACHE_REGION: us-east-1
2025-08-14T21:07:11.5842381Z   SHM_SIZE: 1g
2025-08-14T21:07:11.5843116Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:07:11.5843908Z   XLA_CUDA: 
2025-08-14T21:07:11.5844280Z   XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
2025-08-14T21:07:11.5844754Z   PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0
2025-08-14T21:07:11.5845092Z   PYTORCH_TEST_RERUN_DISABLED_TESTS: 0
2025-08-14T21:07:11.5845394Z   DASHBOARD_TAG: 
2025-08-14T21:07:11.5845862Z   HUGGING_FACE_HUB_TOKEN: ***
2025-08-14T21:07:11.5846303Z   SCRIBE_GRAPHQL_ACCESS_TOKEN: ***
2025-08-14T21:07:11.5846750Z   ARTIFACTS_FILE_SUFFIX: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T21:07:11.5847188Z ##[endgroup]
2025-08-14T21:07:11.5869420Z + [[ crossref == \m\u\l\t\i\g\p\u ]]
2025-08-14T21:07:11.5869806Z + [[ linux-jammy-py3.13-clang12 == *onnx* ]]
2025-08-14T21:07:11.5870162Z + TEST_COMMAND=.ci/pytorch/test.sh
2025-08-14T21:07:11.5872765Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo
2025-08-14T21:07:11.5905070Z + TOTAL_AVAILABLE_MEMORY_IN_GB='14.244 '
2025-08-14T21:07:11.5905420Z + TOTAL_MEMORY_WITH_SWAP=17
2025-08-14T21:07:11.5905755Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]]
2025-08-14T21:07:11.5906121Z + SHM_OPTS=--shm-size=1g
2025-08-14T21:07:11.5906408Z + JENKINS_USER='--user jenkins'
2025-08-14T21:07:11.5906705Z + DOCKER_SHELL_CMD=
2025-08-14T21:07:11.5913838Z +++ nproc --ignore=2
2025-08-14T21:07:11.5941145Z ++ docker run -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=6 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=14g --memory-swap=17g --env-file=/tmp/github_env_16976255017 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=1g --tty --detach --name= --user jenkins -v /home/ec2-user/actions-runner/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T21:07:16.1774698Z + container_name=363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T21:07:16.1779276Z + grep download.pytorch.org /etc/hosts
2025-08-14T21:07:16.1781098Z + docker exec -i 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a sudo bash -c '/bin/cat >> /etc/hosts'
2025-08-14T21:07:16.3652383Z + echo DOCKER_CONTAINER_ID=363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T21:07:16.3653016Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]]
2025-08-14T21:07:16.3655287Z ++ echo dist/torch-2.9.0a0+git1fc683c-cp313-cp313-linux_x86_64.whl
2025-08-14T21:07:16.3657831Z + docker exec -t 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a sh -c 'python3 -m pip install dist/torch-2.9.0a0+git1fc683c-cp313-cp313-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh'
2025-08-14T21:07:16.9289565Z Processing ./dist/torch-2.9.0a0+git1fc683c-cp313-cp313-linux_x86_64.whl (from torch==2.9.0a0+git1fc683c)
2025-08-14T21:07:17.4320539Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (3.18.0)
2025-08-14T21:07:17.4324103Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (4.14.1)
2025-08-14T21:07:17.4331259Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (80.9.0)
2025-08-14T21:07:17.4336060Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (1.13.3)
2025-08-14T21:07:17.4341818Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (2.8.8)
2025-08-14T21:07:17.4344274Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (3.1.6)
2025-08-14T21:07:17.4348237Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (2025.5.1)
2025-08-14T21:07:17.4363106Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (3.3.0)
2025-08-14T21:07:17.4474637Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (2.1.2)
2025-08-14T21:07:17.4522168Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from sympy>=1.13.3->torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (1.3.0)
2025-08-14T21:07:17.4569713Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from jinja2->torch==2.9.0a0+git1fc683c->torch==2.9.0a0+git1fc683c) (3.0.2)
2025-08-14T21:07:17.6733864Z Installing collected packages: torch
2025-08-14T21:07:29.1093546Z Successfully installed torch-2.9.0a0+git1fc683c
2025-08-14T21:07:29.2017981Z + export TERM=vt100
2025-08-14T21:07:29.2018473Z + TERM=vt100
2025-08-14T21:07:29.2018854Z ++ dirname .ci/pytorch/test.sh
2025-08-14T21:07:29.2035445Z + source .ci/pytorch/common.sh
2025-08-14T21:07:29.2043251Z +++ dirname .ci/pytorch/common.sh
2025-08-14T21:07:29.2050270Z ++ source .ci/pytorch/common_utils.sh
2025-08-14T21:07:29.2056402Z +++ declare -f -t trap_add
2025-08-14T21:07:29.2061585Z ++ set -ex -o pipefail
2025-08-14T21:07:29.2061996Z ++ [[ linux-jammy-py3.13-clang12 == *rocm* ]]
2025-08-14T21:07:29.2062396Z ++ BUILD_TEST_LIBTORCH=0
2025-08-14T21:07:29.2066042Z ++ dirname .ci/pytorch/test.sh
2025-08-14T21:07:29.2073507Z + source .ci/pytorch/common-build.sh
2025-08-14T21:07:29.2079045Z ++ [[ linux-jammy-py3.13-clang12 != *win-* ]]
2025-08-14T21:07:29.2085276Z ++++ dirname .ci/pytorch/common-build.sh
2025-08-14T21:07:29.2093496Z +++ cd .ci/pytorch
2025-08-14T21:07:29.2094015Z +++ pwd -P
2025-08-14T21:07:29.2096203Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch
2025-08-14T21:07:29.2096959Z ++ [[ linux-jammy-py3.13-clang12 == *-pch* ]]
2025-08-14T21:07:29.2097297Z ++ which sccache
2025-08-14T21:07:29.2116124Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]]
2025-08-14T21:07:29.2116679Z ++ sccache --stop-server
2025-08-14T21:07:29.2164082Z ++ true
2025-08-14T21:07:29.2164644Z ++ rm -f /var/lib/jenkins/sccache_error.log
2025-08-14T21:07:29.2182905Z ++ trap_add sccache_epilogue EXIT
2025-08-14T21:07:29.2183605Z ++ trap_add_cmd=sccache_epilogue
2025-08-14T21:07:29.2184080Z ++ shift
2025-08-14T21:07:29.2184471Z ++ for trap_add_name in "$@"
2025-08-14T21:07:29.2189895Z ++++ trap -p EXIT
2025-08-14T21:07:29.2192365Z +++ eval 'extract_trap_cmd '
2025-08-14T21:07:29.2192765Z ++++ extract_trap_cmd
2025-08-14T21:07:29.2193136Z ++++ printf '%s\n' ''
2025-08-14T21:07:29.2193455Z +++ printf '%s\n' sccache_epilogue
2025-08-14T21:07:29.2195215Z ++ trap -- '
2025-08-14T21:07:29.2195528Z sccache_epilogue' EXIT
2025-08-14T21:07:29.2195928Z ++ [[ -n 1 ]]
2025-08-14T21:07:29.2196376Z ++ echo 'Skipping sccache server initialization, setting environment variables'
2025-08-14T21:07:29.2197008Z Skipping sccache server initialization, setting environment variables
2025-08-14T21:07:29.2197477Z ++ export SCCACHE_IDLE_TIMEOUT=0
2025-08-14T21:07:29.2197772Z ++ SCCACHE_IDLE_TIMEOUT=0
2025-08-14T21:07:29.2198175Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-08-14T21:07:29.2198645Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-08-14T21:07:29.2199056Z ++ export RUST_LOG=sccache::server=error
2025-08-14T21:07:29.2199397Z ++ RUST_LOG=sccache::server=error
2025-08-14T21:07:29.2199700Z ++ sccache --zero-stats
2025-08-14T21:07:29.3964258Z Statistics zeroed.
2025-08-14T21:07:29.3967081Z ++ which ccache
2025-08-14T21:07:29.3980356Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]]
2025-08-14T21:07:29.3981436Z + [[ linux-jammy-py3.13-clang12 != *s390x* ]]
2025-08-14T21:07:29.3982037Z + [[ -d /var/lib/jenkins/workspace ]]
2025-08-14T21:07:29.3984328Z ++ stat -c %u /var/lib/jenkins/workspace
2025-08-14T21:07:29.4031571Z + WORKSPACE_ORIGINAL_OWNER_ID=1000
2025-08-14T21:07:29.4031972Z + trap_add cleanup_workspace EXIT
2025-08-14T21:07:29.4032298Z + trap_add_cmd=cleanup_workspace
2025-08-14T21:07:29.4032595Z + shift
2025-08-14T21:07:29.4032824Z + for trap_add_name in "$@"
2025-08-14T21:07:29.4039022Z +++ trap -p EXIT
2025-08-14T21:07:29.4041180Z ++ eval 'extract_trap_cmd trap -- '\''
2025-08-14T21:07:29.4041654Z sccache_epilogue'\'' EXIT'
2025-08-14T21:07:29.4042000Z +++ extract_trap_cmd trap -- '
2025-08-14T21:07:29.4042339Z sccache_epilogue' EXIT
2025-08-14T21:07:29.4042672Z +++ printf '%s\n' '
2025-08-14T21:07:29.4042961Z sccache_epilogue'
2025-08-14T21:07:29.4043224Z ++ printf '%s\n' cleanup_workspace
2025-08-14T21:07:29.4044673Z + trap -- '
2025-08-14T21:07:29.4044906Z sccache_epilogue
2025-08-14T21:07:29.4045174Z cleanup_workspace' EXIT
2025-08-14T21:07:29.4045482Z + sudo chown -R jenkins /var/lib/jenkins/workspace
2025-08-14T21:07:30.0200782Z + git config --global --add safe.directory /var/lib/jenkins/workspace
2025-08-14T21:07:30.0359155Z + echo 'Environment variables:'
2025-08-14T21:07:30.0359505Z Environment variables:
2025-08-14T21:07:30.0359762Z + env
2025-08-14T21:07:30.0377100Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-08-14T21:07:30.0377869Z CONTINUE_THROUGH_ERROR=True
2025-08-14T21:07:30.0378399Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12
2025-08-14T21:07:30.0379092Z HOSTNAME=363edb3ac314
2025-08-14T21:07:30.0379916Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0380573Z GITHUB_ACTION=__run_2
2025-08-14T21:07:30.0380851Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0
2025-08-14T21:07:30.0381164Z GITHUB_RUN_NUMBER=346100
2025-08-14T21:07:30.0381424Z TEST_CONFIG=crossref
2025-08-14T21:07:30.0381713Z GITHUB_REPOSITORY_OWNER_ID=21003710
2025-08-14T21:07:30.0382054Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all
2025-08-14T21:07:30.0382372Z SCCACHE_IDLE_TIMEOUT=0
2025-08-14T21:07:30.0382904Z SCRIBE_GRAPHQL_ACCESS_TOKEN=***
2025-08-14T21:07:30.0383307Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot
2025-08-14T21:07:30.0383671Z GITHUB_REF_TYPE=branch
2025-08-14T21:07:30.0383950Z TORCH_CUDA_ARCH_LIST=Maxwell
2025-08-14T21:07:30.0384345Z BASE_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0385019Z XLA_CUDA=
2025-08-14T21:07:30.0385523Z NCCL_LIB_DIR=/usr/local/cuda/lib64/
2025-08-14T21:07:30.0385979Z HUGGING_FACE_HUB_TOKEN=***
2025-08-14T21:07:30.0387723Z ***
2025-08-14T21:07:30.0387948Z GITHUB_REPOSITORY_ID=65600975
2025-08-14T21:07:30.0388251Z GITHUB_ACTIONS=true
2025-08-14T21:07:30.0388556Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-08-14T21:07:30.0388964Z SHA1=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0389336Z GITHUB_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0389877Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main
2025-08-14T21:07:30.0390369Z UCC_HOME=/usr
2025-08-14T21:07:30.0390600Z VERBOSE_TEST_LOGS=False
2025-08-14T21:07:30.0390875Z GITHUB_REF=refs/heads/main
2025-08-14T21:07:30.0391143Z SHARD_NUMBER=1
2025-08-14T21:07:30.0391502Z GITHUB_REF_PROTECTED=true
2025-08-14T21:07:30.0391782Z HOME=/var/lib/jenkins
2025-08-14T21:07:30.0392069Z GITHUB_API_URL=https://api.github.com
2025-08-14T21:07:30.0392423Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0
2025-08-14T21:07:30.0392741Z UCX_COMMIT=
2025-08-14T21:07:30.0392953Z USE_SYSTEM_NCCL=1
2025-08-14T21:07:30.0393201Z NUM_TEST_SHARDS=2
2025-08-14T21:07:30.0393447Z UCX_HOME=/usr
2025-08-14T21:07:30.0394046Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0394891Z JOB_NAME=linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:30.0395701Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0396744Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json
2025-08-14T21:07:30.0397260Z GITHUB_EVENT_NAME=push
2025-08-14T21:07:30.0397533Z DASHBOARD_TAG=
2025-08-14T21:07:30.0397782Z GITHUB_RUN_ID=16976255017
2025-08-14T21:07:30.0398044Z INSTALLED_OPENBLAS=
2025-08-14T21:07:30.0398689Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0399415Z GITHUB_ACTOR=pytorchmergebot
2025-08-14T21:07:30.0399687Z PR_NUMBER=
2025-08-14T21:07:30.0399905Z DESIRED_CUDA=
2025-08-14T21:07:30.0400154Z GITHUB_RUN_ATTEMPT=1
2025-08-14T21:07:30.0400407Z ANACONDA_PYTHON_VERSION=3.13
2025-08-14T21:07:30.0400752Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql
2025-08-14T21:07:30.0401112Z TERM=vt100
2025-08-14T21:07:30.0401332Z INSTALLED_VISION=yes
2025-08-14T21:07:30.0401570Z BRANCH=main
2025-08-14T21:07:30.0401798Z SCCACHE_REGION=us-east-1
2025-08-14T21:07:30.0402077Z OPENSSL_ROOT_DIR=/opt/openssl
2025-08-14T21:07:30.0402358Z CUDA_PATH=/usr/local/cuda
2025-08-14T21:07:30.0402897Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux
2025-08-14T21:07:30.0403505Z GITHUB_SERVER_URL=https://github.com
2025-08-14T21:07:30.0403804Z UCC_COMMIT=
2025-08-14T21:07:30.0404028Z REENABLED_ISSUES=
2025-08-14T21:07:30.0404297Z DOCS=
2025-08-14T21:07:30.0404498Z SHLVL=1
2025-08-14T21:07:30.0404694Z MAX_JOBS=6
2025-08-14T21:07:30.0404922Z GITHUB_ACTOR_ID=97764156
2025-08-14T21:07:30.0405275Z GITHUB_WORKFLOW_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0405654Z GITHUB_REF_NAME=main
2025-08-14T21:07:30.0406045Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla
2025-08-14T21:07:30.0406492Z GITHUB_JOB=test
2025-08-14T21:07:30.0406721Z NO_TEST_TIMEOUT=False
2025-08-14T21:07:30.0406978Z TD_DISTRIBUTED=False
2025-08-14T21:07:30.0407262Z GITHUB_REPOSITORY=pytorch/pytorch
2025-08-14T21:07:30.0407568Z GITHUB_RETENTION_DAYS=90
2025-08-14T21:07:30.0407848Z OPENSSL_DIR=/opt/openssl
2025-08-14T21:07:30.0408122Z GITHUB_ACTION_REPOSITORY=
2025-08-14T21:07:30.0408914Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-08-14T21:07:30.0410030Z GITHUB_BASE_REF=
2025-08-14T21:07:30.0410273Z INSTALLED_ACL=
2025-08-14T21:07:30.0410793Z ARTIFACTS_FILE_SUFFIX=test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T21:07:30.0411222Z CI=true
2025-08-14T21:07:30.0411457Z GITHUB_REPOSITORY_OWNER=pytorch
2025-08-14T21:07:30.0411798Z RUST_LOG=sccache::server=error
2025-08-14T21:07:30.0412067Z JOB_ID=48127032084
2025-08-14T21:07:30.0412304Z GITHUB_HEAD_REF=
2025-08-14T21:07:30.0412545Z GITHUB_ACTION_REF=
2025-08-14T21:07:30.0412832Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
2025-08-14T21:07:30.0413227Z TEST_SHOWLOCALS=False
2025-08-14T21:07:30.0413496Z GITHUB_WORKFLOW=pull
2025-08-14T21:07:30.0413752Z DEBIAN_FRONTEND=noninteractive
2025-08-14T21:07:30.0414415Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0415077Z NO_TD=False
2025-08-14T21:07:30.0415306Z SKIP_SCCACHE_INITIALIZATION=1
2025-08-14T21:07:30.0415627Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/
2025-08-14T21:07:30.0415950Z _=/usr/bin/env
2025-08-14T21:07:30.0416279Z ++ python -c 'import site; print(site.getsitepackages()[0])'
2025-08-14T21:07:30.0527560Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch
2025-08-14T21:07:30.0528523Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T21:07:30.0529140Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib
2025-08-14T21:07:30.0529740Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/test
2025-08-14T21:07:30.0530431Z + BUILD_DIR=build
2025-08-14T21:07:30.0530692Z + BUILD_RENAMED_DIR=build_renamed
2025-08-14T21:07:30.0530998Z + BUILD_BIN_DIR=build/bin
2025-08-14T21:07:30.0531308Z + SHARD_NUMBER=1
2025-08-14T21:07:30.0531546Z + NUM_TEST_SHARDS=2
2025-08-14T21:07:30.0531812Z + export TORCH_SERIALIZATION_DEBUG=1
2025-08-14T21:07:30.0532228Z + TORCH_SERIALIZATION_DEBUG=1
2025-08-14T21:07:30.0532661Z + export VALGRIND=ON
2025-08-14T21:07:30.0532910Z + VALGRIND=ON
2025-08-14T21:07:30.0533228Z + [[ linux-jammy-py3.13-clang12 == *clang9* ]]
2025-08-14T21:07:30.0533647Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]]
2025-08-14T21:07:30.0534008Z + [[ linux-jammy-py3.13-clang12 == *s390x* ]]
2025-08-14T21:07:30.0534320Z + [[ 0 == \1 ]]
2025-08-14T21:07:30.0534548Z + [[ True == \1 ]]
2025-08-14T21:07:30.0534820Z + [[ linux-jammy-py3.13-clang12 != *bazel* ]]
2025-08-14T21:07:30.0535174Z ++ realpath build/custom_test_artifacts
2025-08-14T21:07:30.0551491Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts
2025-08-14T21:07:30.0552144Z + [[ -n '' ]]
2025-08-14T21:07:30.0552389Z + echo 'Environment variables'
2025-08-14T21:07:30.0552671Z Environment variables
2025-08-14T21:07:30.0552954Z + env
2025-08-14T21:07:30.0559397Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-08-14T21:07:30.0560244Z CONTINUE_THROUGH_ERROR=True
2025-08-14T21:07:30.0560806Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12
2025-08-14T21:07:30.0561243Z HOSTNAME=363edb3ac314
2025-08-14T21:07:30.0562322Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0563152Z GITHUB_ACTION=__run_2
2025-08-14T21:07:30.0563658Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0
2025-08-14T21:07:30.0564097Z GITHUB_RUN_NUMBER=346100
2025-08-14T21:07:30.0564374Z TEST_CONFIG=crossref
2025-08-14T21:07:30.0564635Z GITHUB_REPOSITORY_OWNER_ID=21003710
2025-08-14T21:07:30.0564978Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all
2025-08-14T21:07:30.0565320Z SCCACHE_IDLE_TIMEOUT=0
2025-08-14T21:07:30.0565841Z SCRIBE_GRAPHQL_ACCESS_TOKEN=***
2025-08-14T21:07:30.0566191Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot
2025-08-14T21:07:30.0566523Z GITHUB_REF_TYPE=branch
2025-08-14T21:07:30.0566795Z TORCH_CUDA_ARCH_LIST=Maxwell
2025-08-14T21:07:30.0567134Z BASE_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0567476Z XLA_CUDA=
2025-08-14T21:07:30.0567714Z NCCL_LIB_DIR=/usr/local/cuda/lib64/
2025-08-14T21:07:30.0568120Z HUGGING_FACE_HUB_TOKEN=***
2025-08-14T21:07:30.0568442Z ***
2025-08-14T21:07:30.0568868Z GITHUB_REPOSITORY_ID=65600975
2025-08-14T21:07:30.0569162Z GITHUB_ACTIONS=true
2025-08-14T21:07:30.0569454Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-08-14T21:07:30.0569901Z SHA1=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0570277Z GITHUB_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0570784Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main
2025-08-14T21:07:30.0571262Z UCC_HOME=/usr
2025-08-14T21:07:30.0571511Z TORCH_SERIALIZATION_DEBUG=1
2025-08-14T21:07:30.0571791Z VERBOSE_TEST_LOGS=False
2025-08-14T21:07:30.0572058Z GITHUB_REF=refs/heads/main
2025-08-14T21:07:30.0572327Z SHARD_NUMBER=1
2025-08-14T21:07:30.0572556Z GITHUB_REF_PROTECTED=true
2025-08-14T21:07:30.0572825Z HOME=/var/lib/jenkins
2025-08-14T21:07:30.0573112Z GITHUB_API_URL=https://api.github.com
2025-08-14T21:07:30.0573443Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0
2025-08-14T21:07:30.0573746Z UCX_COMMIT=
2025-08-14T21:07:30.0573967Z USE_SYSTEM_NCCL=1
2025-08-14T21:07:30.0574201Z NUM_TEST_SHARDS=2
2025-08-14T21:07:30.0574436Z UCX_HOME=/usr
2025-08-14T21:07:30.0575026Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0575844Z JOB_NAME=linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T21:07:30.0576627Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0577554Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json
2025-08-14T21:07:30.0578074Z GITHUB_EVENT_NAME=push
2025-08-14T21:07:30.0578319Z DASHBOARD_TAG=
2025-08-14T21:07:30.0578558Z GITHUB_RUN_ID=16976255017
2025-08-14T21:07:30.0578831Z INSTALLED_OPENBLAS=
2025-08-14T21:07:30.0579476Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0580184Z GITHUB_ACTOR=pytorchmergebot
2025-08-14T21:07:30.0580466Z PR_NUMBER=
2025-08-14T21:07:30.0580683Z DESIRED_CUDA=
2025-08-14T21:07:30.0580901Z GITHUB_RUN_ATTEMPT=1
2025-08-14T21:07:30.0581146Z VALGRIND=ON
2025-08-14T21:07:30.0581378Z ANACONDA_PYTHON_VERSION=3.13
2025-08-14T21:07:30.0581711Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql
2025-08-14T21:07:30.0582070Z TERM=vt100
2025-08-14T21:07:30.0582291Z INSTALLED_VISION=yes
2025-08-14T21:07:30.0582521Z BRANCH=main
2025-08-14T21:07:30.0582749Z SCCACHE_REGION=us-east-1
2025-08-14T21:07:30.0583027Z OPENSSL_ROOT_DIR=/opt/openssl
2025-08-14T21:07:30.0583306Z CUDA_PATH=/usr/local/cuda
2025-08-14T21:07:30.0583843Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux
2025-08-14T21:07:30.0584445Z GITHUB_SERVER_URL=https://github.com
2025-08-14T21:07:30.0584781Z UCC_COMMIT=
2025-08-14T21:07:30.0584989Z REENABLED_ISSUES=
2025-08-14T21:07:30.0585219Z DOCS=
2025-08-14T21:07:30.0585422Z SHLVL=1
2025-08-14T21:07:30.0585613Z MAX_JOBS=6
2025-08-14T21:07:30.0585842Z GITHUB_ACTOR_ID=97764156
2025-08-14T21:07:30.0586194Z GITHUB_WORKFLOW_SHA=1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T21:07:30.0586571Z GITHUB_REF_NAME=main
2025-08-14T21:07:30.0586965Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla
2025-08-14T21:07:30.0587410Z GITHUB_JOB=test
2025-08-14T21:07:30.0587676Z NO_TEST_TIMEOUT=False
2025-08-14T21:07:30.0587930Z TD_DISTRIBUTED=False
2025-08-14T21:07:30.0588202Z GITHUB_REPOSITORY=pytorch/pytorch
2025-08-14T21:07:30.0588502Z GITHUB_RETENTION_DAYS=90
2025-08-14T21:07:30.0588773Z OPENSSL_DIR=/opt/openssl
2025-08-14T21:07:30.0589049Z GITHUB_ACTION_REPOSITORY=
2025-08-14T21:07:30.0589838Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-08-14T21:07:30.0590668Z GITHUB_BASE_REF=
2025-08-14T21:07:30.0590904Z INSTALLED_ACL=
2025-08-14T21:07:30.0591466Z ARTIFACTS_FILE_SUFFIX=test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T21:07:30.0591910Z CI=true
2025-08-14T21:07:30.0592152Z GITHUB_REPOSITORY_OWNER=pytorch
2025-08-14T21:07:30.0592573Z RUST_LOG=sccache::server=error
2025-08-14T21:07:30.0592845Z JOB_ID=48127032084
2025-08-14T21:07:30.0593083Z GITHUB_HEAD_REF=
2025-08-14T21:07:30.0593321Z GITHUB_ACTION_REF=
2025-08-14T21:07:30.0593607Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
2025-08-14T21:07:30.0593974Z TEST_SHOWLOCALS=False
2025-08-14T21:07:30.0594241Z GITHUB_WORKFLOW=pull
2025-08-14T21:07:30.0594499Z DEBIAN_FRONTEND=noninteractive
2025-08-14T21:07:30.0595147Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_42e05d55-ad5d-45c7-a98b-320fc2e13fb1
2025-08-14T21:07:30.0595807Z NO_TD=False
2025-08-14T21:07:30.0596051Z SKIP_SCCACHE_INITIALIZATION=1
2025-08-14T21:07:30.0596369Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/
2025-08-14T21:07:30.0596691Z _=/usr/bin/env
2025-08-14T21:07:30.0596931Z + echo 'Testing pytorch'
2025-08-14T21:07:30.0597217Z Testing pytorch
2025-08-14T21:07:30.0597474Z + export LANG=C.UTF-8
2025-08-14T21:07:30.0597729Z + LANG=C.UTF-8
2025-08-14T21:07:30.0607729Z + PR_NUMBER=
2025-08-14T21:07:30.0608145Z + [[ crossref == \d\e\f\a\u\l\t ]]
2025-08-14T21:07:30.0608584Z + [[ crossref == \d\i\s\t\r\i\b\u\t\e\d ]]
2025-08-14T21:07:30.0609260Z + [[ crossref == \s\l\o\w ]]
2025-08-14T21:07:30.0609790Z + [[ linux-jammy-py3.13-clang12 == *slow-gradcheck* ]]
2025-08-14T21:07:30.0610396Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]]
2025-08-14T21:07:30.0611017Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]]
2025-08-14T21:07:30.0611369Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]]
2025-08-14T21:07:30.0611715Z + [[ crossref == *crossref* ]]
2025-08-14T21:07:30.0612042Z + export PYTORCH_TEST_WITH_CROSSREF=1
2025-08-14T21:07:30.0612365Z + PYTORCH_TEST_WITH_CROSSREF=1
2025-08-14T21:07:30.0612692Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]]
2025-08-14T21:07:30.0613050Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]]
2025-08-14T21:07:30.0613420Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]]
2025-08-14T21:07:30.0613769Z + pip_install ninja==1.10.2
2025-08-14T21:07:30.0614152Z + pip_install_pkg='python3 -m pip install --progress-bar off'
2025-08-14T21:07:30.0614620Z + python3 -m pip install --progress-bar off ninja==1.10.2
2025-08-14T21:07:30.5335426Z Collecting ninja==1.10.2
2025-08-14T21:07:30.5494620Z   Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB)
2025-08-14T21:07:30.5630231Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB)
2025-08-14T21:07:30.7533381Z Installing collected packages: ninja
2025-08-14T21:07:30.7533846Z   Attempting uninstall: ninja
2025-08-14T21:07:30.7571314Z     Found existing installation: ninja 1.11.1.3
2025-08-14T21:07:30.7594029Z     Uninstalling ninja-1.11.1.3:
2025-08-14T21:07:30.7652233Z       Successfully uninstalled ninja-1.11.1.3
2025-08-14T21:07:30.7906205Z Successfully installed ninja-1.10.2
2025-08-14T21:07:30.8778262Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-08-14T21:07:30.8779933Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-08-14T21:07:30.8781306Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]]
2025-08-14T21:07:30.8781802Z + [[ linux-jammy-py3.13-clang12 == *asan* ]]
2025-08-14T21:07:30.8782167Z + [[ linux-jammy-py3.13-clang12 == *-debug* ]]
2025-08-14T21:07:30.8782527Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]]
2025-08-14T21:07:30.8783063Z + echo 'We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass'
2025-08-14T21:07:30.8783730Z We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass
2025-08-14T21:07:30.8784213Z + cd test
2025-08-14T21:07:30.8784834Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)'
2025-08-14T21:07:32.4432091Z + [[ crossref == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]]
2025-08-14T21:07:32.4432513Z + [[ crossref == \n\o\g\p\u\_\A\V\X\5\1\2 ]]
2025-08-14T21:07:32.4432893Z + [[ crossref == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]]
2025-08-14T21:07:32.4437024Z + DYNAMO_BENCHMARK_FLAGS=()
2025-08-14T21:07:32.4437605Z + [[ crossref == *pr_time_benchmarks* ]]
2025-08-14T21:07:32.4438266Z + [[ crossref == *dynamo_eager* ]]
2025-08-14T21:07:32.4438625Z + [[ crossref == *aot_eager* ]]
2025-08-14T21:07:32.4438922Z + [[ crossref == *aot_inductor* ]]
2025-08-14T21:07:32.4439252Z + [[ crossref == *max_autotune_inductor* ]]
2025-08-14T21:07:32.4439573Z + [[ crossref == *inductor* ]]
2025-08-14T21:07:32.4439905Z + [[ crossref == *dynamic* ]]
2025-08-14T21:07:32.4440187Z + [[ crossref == *cpu* ]]
2025-08-14T21:07:32.4440484Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
2025-08-14T21:07:32.4461389Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]]
2025-08-14T21:07:32.4462007Z + [[ linux-jammy-py3.13-clang12 == *-bazel-* ]]
2025-08-14T21:07:32.4465310Z + cd test
2025-08-14T21:07:32.4465978Z + python -c 'import torch; print(torch.__config__.show())'
2025-08-14T21:07:33.6046796Z PyTorch built with:
2025-08-14T21:07:33.6047166Z   - GCC 4.2
2025-08-14T21:07:33.6047402Z   - C++ Version: 201703
2025-08-14T21:07:33.6047657Z   - clang 12.0.1
2025-08-14T21:07:33.6048231Z   - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications
2025-08-14T21:07:33.6049297Z   - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d)
2025-08-14T21:07:33.6049742Z   - OpenMP 201811
2025-08-14T21:07:33.6050016Z   - LAPACK is enabled (usually provided by MKL)
2025-08-14T21:07:33.6050364Z   - NNPACK is enabled
2025-08-14T21:07:33.6050639Z   - CPU capability usage: AVX512
2025-08-14T21:07:33.6056151Z   - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=1fc683cf17c8c673044538d10266c00f92987be2, CXX_COMPILER=/opt/cache/bin/clang++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=braced-scalar-init -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wvla-extension -Wsuggest-override -Wnewline-eof -Winconsistent-missing-override -Winconsistent-missing-destructor-override -Wno-pass-failed -Wno-error=old-style-cast -Wconstant-conversion -Qunused-arguments -faligned-new -Werror -fno-math-errno -fno-trapping-math -Werror=format, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_CUSPARSELT=OFF, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 
2025-08-14T21:07:33.6061802Z 
2025-08-14T21:07:33.9779854Z + cd test
2025-08-14T21:07:33.9780378Z + python -c 'import torch; print(torch.__config__.parallel_info())'
2025-08-14T21:07:35.1424447Z ATen/Parallel:
2025-08-14T21:07:35.1424830Z 	at::get_num_threads() : 4
2025-08-14T21:07:35.1425154Z 	at::get_num_interop_threads() : 4
2025-08-14T21:07:35.1425494Z OpenMP 201811
2025-08-14T21:07:35.1436941Z 	omp_get_max_threads() : 4
2025-08-14T21:07:35.1437711Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications
2025-08-14T21:07:35.1438343Z 	mkl_get_max_threads() : 4
2025-08-14T21:07:35.1438749Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d)
2025-08-14T21:07:35.1439238Z std::thread::hardware_concurrency() : 8
2025-08-14T21:07:35.1439558Z Environment variables:
2025-08-14T21:07:35.1440173Z 	OMP_NUM_THREADS : [not set]
2025-08-14T21:07:35.1440490Z 	MKL_NUM_THREADS : [not set]
2025-08-14T21:07:35.1440772Z ATen parallel backend: OpenMP
2025-08-14T21:07:35.1440976Z 
2025-08-14T21:07:35.5196787Z + [[ crossref == *numpy_2* ]]
2025-08-14T21:07:35.5197369Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]]
2025-08-14T21:07:35.5197772Z + [[ crossref == *backward* ]]
2025-08-14T21:07:35.5198118Z + [[ crossref == *xla* ]]
2025-08-14T21:07:35.5198386Z + [[ crossref == *executorch* ]]
2025-08-14T21:07:35.5198770Z + [[ crossref == \j\i\t\_\l\e\g\a\c\y ]]
2025-08-14T21:07:35.5199129Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]]
2025-08-14T21:07:35.5199476Z + [[ crossref == distributed ]]
2025-08-14T21:07:35.5199789Z + [[ crossref == *operator_benchmark* ]]
2025-08-14T21:07:35.5200138Z + [[ crossref == *inductor_distributed* ]]
2025-08-14T21:07:35.5200471Z + [[ crossref == *inductor-halide* ]]
2025-08-14T21:07:35.5200813Z + [[ crossref == *inductor-triton-cpu* ]]
2025-08-14T21:07:35.5201210Z + [[ crossref == *inductor-micro-benchmark* ]]
2025-08-14T21:07:35.5201562Z + [[ crossref == *huggingface* ]]
2025-08-14T21:07:35.5201852Z + [[ crossref == *timm* ]]
2025-08-14T21:07:35.5202130Z + [[ crossref == cachebench ]]
2025-08-14T21:07:35.5202428Z + [[ crossref == verify_cachebench ]]
2025-08-14T21:07:35.5202783Z + [[ crossref == *torchbench* ]]
2025-08-14T21:07:35.5203097Z + [[ crossref == *inductor_cpp_wrapper* ]]
2025-08-14T21:07:35.5203428Z + [[ crossref == *inductor* ]]
2025-08-14T21:07:35.5203976Z + [[ crossref == *einops* ]]
2025-08-14T21:07:35.5204272Z + [[ crossref == *dynamo_wrapped* ]]
2025-08-14T21:07:35.5204612Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]]
2025-08-14T21:07:35.5204933Z + [[ 1 == 1 ]]
2025-08-14T21:07:35.5205158Z + [[ 2 -gt 1 ]]
2025-08-14T21:07:35.5205425Z + test_lazy_tensor_meta_reference_disabled
2025-08-14T21:07:35.5205843Z + export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
2025-08-14T21:07:35.5206277Z + TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
2025-08-14T21:07:35.5206738Z + echo 'Testing lazy tensor operations without meta reference'
2025-08-14T21:07:35.5207207Z Testing lazy tensor operations without meta reference
2025-08-14T21:07:35.5207691Z + python test/run_test.py --include lazy/test_ts_opinfo.py --verbose
2025-08-14T21:07:38.0299518Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:07:38.0301094Z   import pkg_resources
2025-08-14T21:07:39.6299772Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json
2025-08-14T21:07:39.6857999Z Ignoring disabled issues:  ['']
2025-08-14T21:07:39.6985981Z Found test times from artifacts
2025-08-14T21:07:39.7490469Z Found test times from artifacts
2025-08-14T21:07:39.7507241Z Running all tests
2025-08-14T21:07:39.7511356Z Running parallel tests on 3 processes
2025-08-14T21:07:39.7512170Z Name: tests to run (est. time: 0.46min)
2025-08-14T21:07:39.7512664Z   Serial tests (0):
2025-08-14T21:07:39.7513083Z   Parallel tests (1):
2025-08-14T21:07:39.7513507Z     lazy/test_ts_opinfo 1/1
2025-08-14T21:07:39.7514021Z Name: excluded (est. time: 0.0min)
2025-08-14T21:07:39.7514537Z   Serial tests (0):
2025-08-14T21:07:39.7514905Z   Parallel tests (0):
2025-08-14T21:07:39.7515462Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-14 21:07:39.751261]
2025-08-14T21:07:39.7516109Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:07:39.7521177Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:07:39.751744]
2025-08-14T21:07:44.3732965Z 
2025-08-14T21:07:44.3734528Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_682664c1a8247246_.log
2025-08-14T21:07:44.3735319Z Running 0 items in this shard:
2025-08-14T21:07:44.3735531Z 
2025-08-14T21:07:44.6406330Z Uploading artifacts took 0.27 seconds
2025-08-14T21:07:47.1887781Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:07:47.1889360Z   import pkg_resources
2025-08-14T21:07:47.1929168Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:07:47.1930669Z   import pkg_resources
2025-08-14T21:07:47.2503808Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:07:47.2505304Z   import pkg_resources
2025-08-14T21:07:47.3145215Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-14 21:07:47.314123]
2025-08-14T21:07:47.3145682Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:07:47.3147948Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:07:47.314501]
2025-08-14T21:08:04.4041420Z 
2025-08-14T21:08:04.4042849Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_de1f5e4175636b99_.log
2025-08-14T21:08:04.4197794Z Running 292 items in this shard: test/lazy/test_ts_opinfo.py::TestLazyTensor::testConvolutionBackward, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_tensor_ctr, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_view_mark_step_preserved, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcdiv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bernoulli_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_pow_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_adaptiveavgpool3d_dynamic, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_nonzero_dynamic
2025-08-14T21:08:04.4312834Z 
2025-08-14T21:08:05.2765043Z Running test batch 'tests to run' cost 25.53 seconds
2025-08-14T21:08:06.2022240Z 
2025-08-14T21:08:06.2022669Z real	0m30.682s
2025-08-14T21:08:06.2022971Z user	1m1.295s
2025-08-14T21:08:06.2023215Z sys	0m3.551s
2025-08-14T21:08:06.2023548Z + export -n TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE
2025-08-14T21:08:06.2023952Z + test_without_numpy
2025-08-14T21:08:06.2027822Z ++ dirname .ci/pytorch/test.sh
2025-08-14T21:08:06.2038849Z + pushd .ci/pytorch
2025-08-14T21:08:06.2039235Z ~/workspace/.ci/pytorch ~/workspace
2025-08-14T21:08:06.2040142Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');from unittest import TestCase;import torch;x=torch.randn(3,3);TestCase().assertRaises(RuntimeError, lambda: x.numpy())'
2025-08-14T21:08:06.9194092Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:82.)
2025-08-14T21:08:06.9195559Z   cpu = _conversion_method_template(device=torch.device("cpu"))
2025-08-14T21:08:07.6622708Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch;print(torch.tensor([torch.tensor(0.), torch.tensor(1.)]))'
2025-08-14T21:08:08.3280328Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:82.)
2025-08-14T21:08:08.3281831Z   cpu = _conversion_method_template(device=torch.device("cpu"))
2025-08-14T21:08:08.7356194Z tensor([0., 1.])
2025-08-14T21:08:09.0585005Z + [[ crossref == *dynamo_wrapped* ]]
2025-08-14T21:08:09.0585616Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch; import torch.onnx'
2025-08-14T21:08:09.7433763Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:82.)
2025-08-14T21:08:09.7435269Z   cpu = _conversion_method_template(device=torch.device("cpu"))
2025-08-14T21:08:10.5304851Z + popd
2025-08-14T21:08:10.5305233Z ~/workspace
2025-08-14T21:08:10.5305544Z + install_torchvision
2025-08-14T21:08:10.5305923Z + local orig_preload
2025-08-14T21:08:10.5306198Z + local commit
2025-08-14T21:08:10.5306596Z ++ get_pinned_commit vision
2025-08-14T21:08:10.5307516Z ++ cat .github/ci_commit_pins/vision.txt
2025-08-14T21:08:10.5331122Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:10.5331848Z + orig_preload=
2025-08-14T21:08:10.5332176Z + '[' -n '' ']'
2025-08-14T21:08:10.5332517Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]]
2025-08-14T21:08:10.5333226Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision
2025-08-14T21:08:10.5334151Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:10.5334757Z + local wheel_dir=dist/vision
2025-08-14T21:08:10.5335088Z + local found_whl=0
2025-08-14T21:08:10.5335349Z + for file in "${wheel_dir}"/*.whl
2025-08-14T21:08:10.5335646Z + [[ -f dist/vision/*.whl ]]
2025-08-14T21:08:10.5335919Z + '[' 0 == 0 ']'
2025-08-14T21:08:10.5336680Z + python3 -m pip wheel --no-build-isolation --no-deps --no-use-pep517 -w dist/vision git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:10.8600869Z Collecting git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:10.8606140Z   Cloning https://github.com/pytorch/vision.git (to revision 966da7e46f65d6d49df3e31214470a4fe5cc8e66) to /tmp/pip-req-build-xjw164ep
2025-08-14T21:08:10.8627326Z   Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-xjw164ep
2025-08-14T21:08:12.6231965Z   Running command git rev-parse -q --verify 'sha^966da7e46f65d6d49df3e31214470a4fe5cc8e66'
2025-08-14T21:08:12.6253549Z   Running command git fetch -q https://github.com/pytorch/vision.git 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:12.7505340Z   Running command git checkout -q 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:13.0646267Z   Resolved https://github.com/pytorch/vision.git to commit 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-08-14T21:08:15.2524920Z   Preparing metadata (setup.py) ... [?25l- \ | done
2025-08-14T21:08:15.2526024Z [?25hBuilding wheels for collected packages: torchvision
2025-08-14T21:08:15.2530542Z   DEPRECATION: Building 'torchvision' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchvision'. Discussion can be found at https://github.com/pypa/pip/issues/6334
2025-08-14T21:09:54.2174343Z   Building wheel for torchvision (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | done
2025-08-14T21:09:54.2212954Z [?25h  Created wheel for torchvision: filename=torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl size=1201347 sha256=820868dd29ab5d19d2efa63a01817eb4abe83e07db175fcfee748c9857d9b515
2025-08-14T21:09:54.2214262Z   Stored in directory: /var/lib/jenkins/.cache/pip/wheels/89/53/07/16d05bff0990e585bfa232438657da6e5e4f6d0cea71bd3e09
2025-08-14T21:09:54.2249833Z Successfully built torchvision
2025-08-14T21:09:54.3188066Z + for file in "${wheel_dir}"/*.whl
2025-08-14T21:09:54.3188637Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl
2025-08-14T21:09:54.3196756Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl')
2025-08-14T21:09:54.3197460Z + local args
2025-08-14T21:09:54.3198018Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl == *\ * ]]
2025-08-14T21:09:54.3198951Z + for path in "${args[@]}"
2025-08-14T21:09:54.3199460Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl'
2025-08-14T21:09:54.3200180Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl
2025-08-14T21:09:54.3201359Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl
2025-08-14T21:09:54.6465808Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl
2025-08-14T21:09:54.6568262Z Installing collected packages: torchvision
2025-08-14T21:09:55.1202163Z Successfully installed torchvision-0.22.0a0+966da7e
2025-08-14T21:09:55.1690031Z + '[' -n '' ']'
2025-08-14T21:09:55.1690352Z + test_python_shard 1
2025-08-14T21:09:55.1690674Z + [[ -z 2 ]]
2025-08-14T21:09:55.1691305Z + python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --shard 1 2 --verbose --upload-artifacts-while-running
2025-08-14T21:09:57.5353398Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:09:57.5354963Z   import pkg_resources
2025-08-14T21:09:59.0487704Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json
2025-08-14T21:09:59.0612033Z Found test times from artifacts
2025-08-14T21:09:59.1115348Z Found test times from artifacts
2025-08-14T21:09:59.1131709Z Running all tests
2025-08-14T21:09:59.1401321Z Running parallel tests on 3 processes
2025-08-14T21:09:59.1416106Z Name: tests to run (est. time: 96.66min)
2025-08-14T21:09:59.1416622Z   Serial tests (47):
2025-08-14T21:09:59.1417059Z     inductor/test_distributed_patterns 1/1
2025-08-14T21:09:59.1417477Z     test_ci_sanity_check_fail 1/1
2025-08-14T21:09:59.1417870Z     test_cpp_extensions_mtia_backend 1/1
2025-08-14T21:09:59.1418217Z     test_tensor_creation_ops 1/1
2025-08-14T21:09:59.1418604Z     test_cpp_extensions_stream_and_event 1/1
2025-08-14T21:09:59.1418956Z     test_reductions 1/1
2025-08-14T21:09:59.1419297Z     test_nn 1/1
2025-08-14T21:09:59.1419689Z     test_overrides 1/1
2025-08-14T21:09:59.1420068Z     doctests 1/1
2025-08-14T21:09:59.1420439Z     inductor/test_max_autotune 1/1
2025-08-14T21:09:59.1420884Z     inductor/test_flex_attention 1/1
2025-08-14T21:09:59.1421407Z     inductor/test_benchmark_fusion 1/1
2025-08-14T21:09:59.1421883Z     inductor/test_cutlass_backend 1/1
2025-08-14T21:09:59.1422227Z     dynamo/test_fake_distributed 1/1
2025-08-14T21:09:59.1422683Z     test_cpp_api_parity 1/1
2025-08-14T21:09:59.1423114Z     test_transformers_privateuse1 1/1
2025-08-14T21:09:59.1423547Z     test_extension_utils 1/1
2025-08-14T21:09:59.1423915Z     test_fx 1/1
2025-08-14T21:09:59.1424247Z     test_fake_tensor 1/1
2025-08-14T21:09:59.1424609Z     test_openreg 1/1
2025-08-14T21:09:59.1424933Z     test_show_pickle 1/1
2025-08-14T21:09:59.1425259Z     test_tensorexpr 1/1
2025-08-14T21:09:59.1425519Z     test_torch 1/1
2025-08-14T21:09:59.1425746Z     test_utils 1/1
2025-08-14T21:09:59.1425996Z     test_python_dispatch 1/1
2025-08-14T21:09:59.1426302Z     test_dispatch 1/1
2025-08-14T21:09:59.1426560Z     test_namedtuple_return_api 1/1
2025-08-14T21:09:59.1426875Z     test_multiprocessing 1/1
2025-08-14T21:09:59.1427170Z     test_autograd_fallback 1/1
2025-08-14T21:09:59.1427445Z     test_jit_disabled 1/1
2025-08-14T21:09:59.1427711Z     test_autocast 1/1
2025-08-14T21:09:59.1427962Z     test_cuda_trace 1/1
2025-08-14T21:09:59.1428204Z     test_native_mha 1/1
2025-08-14T21:09:59.1428468Z     test_sort_and_select 1/1
2025-08-14T21:09:59.1428770Z     test_cuda_nvml_based_avail 1/1
2025-08-14T21:09:59.1429073Z     test_cpp_extensions_jit 1/1
2025-08-14T21:09:59.1429363Z     nn/test_pooling 1/1
2025-08-14T21:09:59.1429632Z     test_cuda_primary_ctx 1/1
2025-08-14T21:09:59.1429925Z     test_mobile_optimizer 1/1
2025-08-14T21:09:59.1430212Z     test_multiprocessing_spawn 1/1
2025-08-14T21:09:59.1430527Z     nn/test_convolution 1/1
2025-08-14T21:09:59.1430808Z     test_spectral_ops 1/1
2025-08-14T21:09:59.1431865Z     distributions/test_distributions 1/1
2025-08-14T21:09:59.1432226Z     test_autoload_enable 1/1
2025-08-14T21:09:59.1432532Z     test_cpp_extensions_aot_no_ninja 1/1
2025-08-14T21:09:59.1432851Z     test_autoload_disable 1/1
2025-08-14T21:09:59.1433158Z     test_cpp_extensions_aot_ninja 1/1
2025-08-14T21:09:59.1433478Z   Parallel tests (238):
2025-08-14T21:09:59.1433747Z     inductor/test_cudagraph_trees 1/1
2025-08-14T21:09:59.1434070Z     dynamo/test_repros 1/1
2025-08-14T21:09:59.1434369Z     inductor/test_compiled_optimizers 1/1
2025-08-14T21:09:59.1434694Z     dynamo/test_logging 1/1
2025-08-14T21:09:59.1434986Z     inductor/test_triton_kernels 1/1
2025-08-14T21:09:59.1435307Z     inductor/test_torchbind 1/1
2025-08-14T21:09:59.1435617Z     inductor/test_aot_inductor_package 1/1
2025-08-14T21:09:59.1435937Z     dynamo/test_utils 1/1
2025-08-14T21:09:59.1436216Z     dynamo/test_error_messages 1/1
2025-08-14T21:09:59.1436524Z     dynamo/test_exceptions 1/1
2025-08-14T21:09:59.1436811Z     dynamo/test_structured_trace 1/1
2025-08-14T21:09:59.1437197Z     inductor/test_cudagraph_trees_expandable_segments 1/1
2025-08-14T21:09:59.1437576Z     test_ops 6/8
2025-08-14T21:09:59.1437828Z     inductor/test_torchinductor 1/1
2025-08-14T21:09:59.1438224Z     inductor/test_torchinductor_codegen_dynamic_shapes 1/1
2025-08-14T21:09:59.1438620Z     inductor/test_cpu_repro 1/1
2025-08-14T21:09:59.1438918Z     inductor/test_kernel_benchmark 1/1
2025-08-14T21:09:59.1439251Z     inductor/test_pattern_matcher 1/1
2025-08-14T21:09:59.1439682Z     inductor/test_perf 1/1
2025-08-14T21:09:59.1439949Z     dynamo/test_modules 1/1
2025-08-14T21:09:59.1440263Z     inductor/test_coordinate_descent_tuner 1/1
2025-08-14T21:09:59.1440620Z     inductor/test_select_algorithm 1/1
2025-08-14T21:09:59.1440951Z     inductor/test_compiled_autograd 1/1
2025-08-14T21:09:59.1441278Z     inductor/test_group_batch_fusion 1/1
2025-08-14T21:09:59.1441622Z     inductor/test_split_cat_fx_passes 1/1
2025-08-14T21:09:59.1441957Z     inductor/test_snode_runtime 1/1
2025-08-14T21:09:59.1442262Z     inductor/test_config 1/1
2025-08-14T21:09:59.1442551Z     dynamo/test_after_aot 1/1
2025-08-14T21:09:59.1442851Z     inductor/test_binary_folding 1/1
2025-08-14T21:09:59.1443157Z     dynamo/test_cudagraphs 1/1
2025-08-14T21:09:59.1443454Z     dynamo/test_ctx_manager 1/1
2025-08-14T21:09:59.1443754Z     inductor/test_control_flow 1/1
2025-08-14T21:09:59.1444050Z     inductor/test_padding 1/1
2025-08-14T21:09:59.1444342Z     inductor/test_halide 1/1
2025-08-14T21:09:59.1444656Z     inductor/test_aot_inductor_custom_ops 1/1
2025-08-14T21:09:59.1445003Z     inductor/test_flex_decoding 1/1
2025-08-14T21:09:59.1445315Z     inductor/test_external_callables 1/1
2025-08-14T21:09:59.1445644Z     inductor/test_alignment 1/1
2025-08-14T21:09:59.1445947Z     inductor/test_subgraph_choice 1/1
2025-08-14T21:09:59.1446253Z     inductor/test_pad_mm 1/1
2025-08-14T21:09:59.1446549Z     dynamo/test_deque_reconstruct 1/1
2025-08-14T21:09:59.1446891Z     inductor/test_cooperative_reductions 1/1
2025-08-14T21:09:59.1447243Z     inductor/test_inductor_annotations 1/1
2025-08-14T21:09:59.1447581Z     inductor/test_inductor_utils 1/1
2025-08-14T21:09:59.1447906Z     inductor/test_op_completeness 1/1
2025-08-14T21:09:59.1448210Z     inductor/test_fp8 1/1
2025-08-14T21:09:59.1448488Z     inductor/test_debug_trace 1/1
2025-08-14T21:09:59.1448794Z     export/test_export_strict 1/1
2025-08-14T21:09:59.1449134Z     export/test_export_training_ir_to_run_decomp 1/1
2025-08-14T21:09:59.1449505Z     inductor/test_combo_kernels 1/1
2025-08-14T21:09:59.1449831Z     dynamo/test_skip_guard_eval_unsafe 1/1
2025-08-14T21:09:59.1450168Z     inductor/test_memory_planning 1/1
2025-08-14T21:09:59.1450479Z     inductor/test_compile_worker 1/1
2025-08-14T21:09:59.1450791Z     dynamo/test_frame_init 1/1
2025-08-14T21:09:59.1451091Z     dynamo/test_fx_passes_pre_grad 1/1
2025-08-14T21:09:59.1451397Z     inductor/test_metrics 1/1
2025-08-14T21:09:59.1451720Z     inductor/test_move_constructors_to_cuda 1/1
2025-08-14T21:09:59.1452162Z     dynamo/test_inline_and_install 1/1
2025-08-14T21:09:59.1452480Z     dynamo/test_skip_non_tensor 1/1
2025-08-14T21:09:59.1452796Z     inductor/test_cutlass_evt 1/1
2025-08-14T21:09:59.1453121Z     inductor/test_kernel_optimization 1/1
2025-08-14T21:09:59.1453478Z     export/test_export_with_inline_and_install 1/1
2025-08-14T21:09:59.1453855Z     inductor/test_static_cuda_launcher 1/1
2025-08-14T21:09:59.1454201Z     dynamo/test_pre_dispatch 1/1
2025-08-14T21:09:59.1454502Z     dynamo/test_sdpa 1/1
2025-08-14T21:09:59.1454777Z     inductor/test_inplacing_pass 1/1
2025-08-14T21:09:59.1455108Z     dynamo/test_graph_region_tracker 1/1
2025-08-14T21:09:59.1455436Z     inductor/test_fuzzer 1/1
2025-08-14T21:09:59.1455711Z     dynamo/test_subgraphs 1/1
2025-08-14T21:09:59.1456009Z     inductor/test_quantization 1/1
2025-08-14T21:09:59.1456333Z     inductor/test_compile_subprocess 1/1
2025-08-14T21:09:59.1456643Z     dynamo/test_view 1/1
2025-08-14T21:09:59.1456908Z     dynamo/test_list 1/1
2025-08-14T21:09:59.1457188Z     inductor/test_loop_ordering 1/1
2025-08-14T21:09:59.1457494Z     inductor/test_fxir_backend 1/1
2025-08-14T21:09:59.1457812Z     dynamo/test_install_free_tensors 1/1
2025-08-14T21:09:59.1458154Z     dynamo/test_autograd_function 1/1
2025-08-14T21:09:59.1458457Z     dynamo/test_config 1/1
2025-08-14T21:09:59.1458750Z     inductor/test_needs_exact_strides 1/1
2025-08-14T21:09:59.1459078Z     dynamo/test_compile 1/1
2025-08-14T21:09:59.1459387Z     inductor/test_graph_transform_observer 1/1
2025-08-14T21:09:59.1459796Z     dynamo/test_unittest 1/1
2025-08-14T21:09:59.1460078Z     dynamo/test_sources 1/1
2025-08-14T21:09:59.1460439Z     inductor/test_torchinductor_codegen_config_overrides 1/1
2025-08-14T21:09:59.1460846Z     dynamo/test_guard_serialization 1/1
2025-08-14T21:09:59.1461189Z     inductor/test_scatter_optimization 1/1
2025-08-14T21:09:59.1461523Z     export/test_upgrader 1/1
2025-08-14T21:09:59.1461800Z     dynamo/test_einops 1/1
2025-08-14T21:09:59.1462078Z     export/test_nativert 1/1
2025-08-14T21:09:59.1462388Z     inductor/test_auto_functionalize 1/1
2025-08-14T21:09:59.1462717Z     dynamo/test_export 1/1
2025-08-14T21:09:59.1462993Z     dynamo/test_sets 1/1
2025-08-14T21:09:59.1463267Z     dynamo/test_profiler 1/1
2025-08-14T21:09:59.1463550Z     dynamo/test_optimizers 1/1
2025-08-14T21:09:59.1463856Z     dynamo/test_python_dispatcher 1/1
2025-08-14T21:09:59.1464176Z     dynamo/test_package 1/1
2025-08-14T21:09:59.1464459Z     dynamo/test_input_attr_tracking 1/1
2025-08-14T21:09:59.1464792Z     dynamo/test_callback 1/1
2025-08-14T21:09:59.1465092Z     dynamo/test_aot_autograd_cache 1/1
2025-08-14T21:09:59.1465444Z     dynamo/test_cudagraphs_expandable_segments 1/1
2025-08-14T21:09:59.1465811Z     dynamo/test_torchrec 1/1
2025-08-14T21:09:59.1466106Z     dynamo/test_hooks 1/1
2025-08-14T21:09:59.1466375Z     dynamo/test_reorder_logs 1/1
2025-08-14T21:09:59.1466683Z     dynamo/test_comptime 1/1
2025-08-14T21:09:59.1466974Z     test_quantization 2/4
2025-08-14T21:09:59.1467237Z     test_quantization 3/4
2025-08-14T21:09:59.1467516Z     test_quantization 4/4
2025-08-14T21:09:59.1467815Z     dynamo/cpython/3_13/test_defaultdict 1/1
2025-08-14T21:09:59.1468149Z     test_transformers 2/3
2025-08-14T21:09:59.1468412Z     test_transformers 3/3
2025-08-14T21:09:59.1468680Z     test_ao_sparsity 1/1
2025-08-14T21:09:59.1468946Z     test_license 1/1
2025-08-14T21:09:59.1469194Z     torch_np/test_binary_ufuncs 1/1
2025-08-14T21:09:59.1469498Z     xpu/test_fusion 1/1
2025-08-14T21:09:59.1469769Z     torch_np/test_unary_ufuncs 1/1
2025-08-14T21:09:59.1470054Z     test_foreach 1/1
2025-08-14T21:09:59.1470313Z     test_expanded_weights 1/1
2025-08-14T21:09:59.1470616Z     typing/test_python_operators 1/1
2025-08-14T21:09:59.1470928Z     test_fx_experimental 1/1
2025-08-14T21:09:59.1471248Z     test_file_check 1/1
2025-08-14T21:09:59.1471509Z     torch_np/test_dtype 1/1
2025-08-14T21:09:59.1471898Z     higher_order_ops/test_with_effects 1/1
2025-08-14T21:09:59.1472219Z     test_native_functions 1/1
2025-08-14T21:09:59.1472610Z     functorch/test_minifier 1/1
2025-08-14T21:09:59.1472905Z     test_flop_counter 1/1
2025-08-14T21:09:59.1473180Z     torch_np/test_nep50_examples 1/1
2025-08-14T21:09:59.1473519Z     higher_order_ops/test_invoke_quant 1/1
2025-08-14T21:09:59.1473853Z     test_per_overload_api 1/1
2025-08-14T21:09:59.1474154Z     test_tensorexpr_pybind 1/1
2025-08-14T21:09:59.1474426Z     test_pytree 1/1
2025-08-14T21:09:59.1474675Z     test_fx_passes 1/1
2025-08-14T21:09:59.1474938Z     test_module_tracker 1/1
2025-08-14T21:09:59.1475202Z     test_typing 1/1
2025-08-14T21:09:59.1475441Z     test_openmp 1/1
2025-08-14T21:09:59.1475736Z     torch_np/numpy_tests/core/test_scalarinherit 1/1
2025-08-14T21:09:59.1476101Z     functorch/test_ac_knapsack 1/1
2025-08-14T21:09:59.1476417Z     backends/xeon/test_launch 1/1
2025-08-14T21:09:59.1476719Z     test_nestedtensor 1/4
2025-08-14T21:09:59.1476981Z     test_namedtensor 1/1
2025-08-14T21:09:59.1477263Z     torch_np/test_ufuncs_basic 1/1
2025-08-14T21:09:59.1477561Z     test_meta 1/1
2025-08-14T21:09:59.1477794Z     test_utils_filelock 1/1
2025-08-14T21:09:59.1478078Z     torch_np/test_random 1/1
2025-08-14T21:09:59.1478367Z     profiler/test_kineto 1/1
2025-08-14T21:09:59.1478650Z     test_compile_benchmark_util 1/1
2025-08-14T21:09:59.1478960Z     test_jiterator 1/1
2025-08-14T21:09:59.1479210Z     test_optim 1/1
2025-08-14T21:09:59.1479450Z     test_decomp 1/1
2025-08-14T21:09:59.1479686Z     torch_np/test_basic 1/1
2025-08-14T21:09:59.1480037Z     lazy/test_bindings 1/1
2025-08-14T21:09:59.1480310Z     test_legacy_vmap 1/1
2025-08-14T21:09:59.1480559Z     test_modules 1/2
2025-08-14T21:09:59.1480806Z     test_modules 2/2
2025-08-14T21:09:59.1481052Z     xpu/test_conv 1/1
2025-08-14T21:09:59.1481288Z     test_ops_jit 2/2
2025-08-14T21:09:59.1481545Z     test_fx_reinplace_pass 1/1
2025-08-14T21:09:59.1481849Z     nn/test_multihead_attention 1/1
2025-08-14T21:09:59.1482187Z     functorch/test_aot_joint_with_descriptors 1/1
2025-08-14T21:09:59.1482537Z     test_pruning_op 1/1
2025-08-14T21:09:59.1482819Z     lazy/test_functionalization 1/1
2025-08-14T21:09:59.1483123Z     functorch/test_ac 1/1
2025-08-14T21:09:59.1483399Z     test_ops_fwd_gradients 1/2
2025-08-14T21:09:59.1483690Z     test_ops_fwd_gradients 2/2
2025-08-14T21:09:59.1483955Z     test_hub 1/1
2025-08-14T21:09:59.1484222Z     test_set_default_mobile_cpu_allocator 1/1
2025-08-14T21:09:59.1484551Z     test_stateless 1/1
2025-08-14T21:09:59.1484818Z     distributions/test_constraints 1/1
2025-08-14T21:09:59.1485158Z     profiler/test_record_function 1/1
2025-08-14T21:09:59.1485480Z     nn/test_lazy_modules 1/1
2025-08-14T21:09:59.1485764Z     test_jit_fuser_te 1/1
2025-08-14T21:09:59.1486030Z     test_segment_reductions 1/1
2025-08-14T21:09:59.1486321Z     test_import_stats 1/1
2025-08-14T21:09:59.1486585Z     test_masked 1/1
2025-08-14T21:09:59.1486821Z     test_cuda_sanitizer 1/1
2025-08-14T21:09:59.1487094Z     test_monitor 1/1
2025-08-14T21:09:59.1487361Z     profiler/test_cpp_thread 1/1
2025-08-14T21:09:59.1487647Z     test_subclass 1/1
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2025-08-14T21:09:59.1498301Z     torch_np/test_ndarray_methods 1/1
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2025-08-14T21:09:59.1498920Z     torch_np/numpy_tests/lib/test_shape_base_ 1/1
2025-08-14T21:09:59.1499293Z     torch_np/numpy_tests/linalg/test_linalg 1/1
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2025-08-14T21:09:59.1500125Z     test_accelerator 1/1
2025-08-14T21:09:59.1500535Z     profiler/test_memory_profiler 1/1
2025-08-14T21:09:59.1501005Z     torch_np/numpy_tests/fft/test_pocketfft 1/1
2025-08-14T21:09:59.1501479Z     test_function_schema 1/1
2025-08-14T21:09:59.1501935Z     torch_np/numpy_tests/lib/test_index_tricks 1/1
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2025-08-14T21:09:59.1502838Z     test_serialization 1/1
2025-08-14T21:09:59.1503286Z     torch_np/numpy_tests/core/test_dlpack 1/1
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2025-08-14T21:09:59.1504324Z     torch_np/numpy_tests/fft/test_helper 1/1
2025-08-14T21:09:59.1504819Z     test_mkldnn 1/1
2025-08-14T21:09:59.1505158Z     test_unary_ufuncs 1/1
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2025-08-14T21:09:59.1505787Z     test_dlpack 1/1
2025-08-14T21:09:59.1506037Z     profiler/test_profiler_tree 1/1
2025-08-14T21:09:59.1506394Z     torch_np/numpy_tests/core/test_scalar_ctors 1/1
2025-08-14T21:09:59.1506770Z     profiler/test_torch_tidy 1/1
2025-08-14T21:09:59.1507095Z     torch_np/test_reductions 1/1
2025-08-14T21:09:59.1507382Z     lazy/test_reuse_ir 1/1
2025-08-14T21:09:59.1507684Z     test_functional_autograd_benchmark 1/1
2025-08-14T21:09:59.1508010Z     test_prims 1/1
2025-08-14T21:09:59.1508255Z     profiler/test_python_tracer 1/1
2025-08-14T21:09:59.1508575Z Name: excluded (est. time: 0.0min)
2025-08-14T21:09:59.1508874Z   Serial tests (0):
2025-08-14T21:09:59.1509504Z   Parallel tests (0):
2025-08-14T21:09:59.1509977Z Running inductor/test_distributed_patterns 1/1 ... [2025-08-14 21:09:59.149990]
2025-08-14T21:09:59.1510481Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:09:59.1511617Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_distributed_patterns.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:09:59.150383]
2025-08-14T21:10:09.4822228Z 
2025-08-14T21:10:09.4823612Z inductor/test_distributed_patterns 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_distributed_patterns_1.1_25e9a8ea4878faed_.log
2025-08-14T21:10:09.4824419Z 
2025-08-14T21:10:09.8953101Z Uploading artifacts took 0.41 seconds
2025-08-14T21:10:09.8956029Z Running test_ci_sanity_check_fail 1/1 ... [2025-08-14 21:10:09.895422]
2025-08-14T21:10:09.8956474Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:10:09.8960912Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ci_sanity_check_fail.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:10:09.895846]
2025-08-14T21:10:23.2011878Z Running test_cpp_extensions_mtia_backend 1/1 ... [2025-08-14 21:10:23.200786]
2025-08-14T21:10:23.2012519Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:10:23.2014274Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_mtia_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:10:23.201189]
2025-08-14T21:10:26.9710239Z 
2025-08-14T21:10:26.9712047Z test_cpp_extensions_mtia_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_mtia_backend_1.1_9551f6297a6aecd1_.log
2025-08-14T21:10:26.9716940Z Running 5 items in this shard: test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_device_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_get_device_module, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_basic, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context_different_device
2025-08-14T21:10:26.9720857Z 
2025-08-14T21:10:26.9721585Z Running test_tensor_creation_ops 1/1 ... [2025-08-14 21:10:26.971307]
2025-08-14T21:10:26.9722060Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:10:26.9723235Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensor_creation_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:10:26.971736]
2025-08-14T21:10:56.2774873Z 
2025-08-14T21:10:56.2776243Z test_tensor_creation_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensor_creation_ops_1.1_75ec0664949dfa1a_.log
2025-08-14T21:10:56.3017783Z Running 641 items in this shard: test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_strided_neg_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_scipy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cartesian_prod_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_all_dtypes_and_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_big_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_legacy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_in_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_mem_overlap_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_memory_format_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_preserve_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_stack_cross_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_combinations_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_complex_type_conversions_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_concat_empty_list_error_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_constructor_device_legacy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_constructor_dtypes_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_ctor_with_numpy_array_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_device_rounding_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_device_rounding_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_diag_embed_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_diagflat_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_full_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_overflow_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_strided_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_tensor_props_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_eye_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_fill_all_dtypes_and_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_from_file_shared_False_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_from_file_shared_True_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_large_linspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_large_linspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_like_fn_stride_proparation_vs_tensoriterator_unary_op_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linlogspace_mem_overlap_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_deduction_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_complex_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_base2_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_base2_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_deduction_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_special_steps_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_special_steps_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_complex_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_default_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_ij_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_ij_indexing_is_default_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_inconsistent_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_inconsistent_dtype_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_non_1d_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_unsupported_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_vs_numpy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_warns_if_no_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_xy_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_empty_strided_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_methods_requires_grad_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_tensor_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_offset_scalar_cast_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_ones_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_bool_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_bool_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_factories_64bit_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_warning_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_repeat_interleave_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_roll_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_simple_scalar_cast_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_storage_filename_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_strided_mismatched_stride_shape_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_ctor_device_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factories_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_copy_var_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_non_writable_numpy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_sequence_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_out_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_std_error_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_distribution_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_inference_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_bfloat16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_random_neg_values_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_device_compatibility_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_large_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float64, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_empty_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_full_like_inference_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_byte_to_int_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_astensor_consistency_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_default_device_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_device_without_index_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_numpy_scalars_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_mult_devices_cpu_float32
2025-08-14T21:10:56.3254527Z 
2025-08-14T21:10:56.3254804Z Running test_cpp_extensions_stream_and_event 1/1 ... [2025-08-14 21:10:56.278611]
2025-08-14T21:10:56.3255314Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:10:56.3256445Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_stream_and_event.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:10:56.278973]
2025-08-14T21:11:00.0986756Z 
2025-08-14T21:11:00.0988124Z test_cpp_extensions_stream_and_event 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_stream_and_event_1.1_c39230331b9822f6_.log
2025-08-14T21:11:00.0989405Z Running 1 items in this shard: test/test_cpp_extensions_stream_and_event.py::TestCppExtensionStreamAndEvent::test_stream_event
2025-08-14T21:11:00.0990144Z 
2025-08-14T21:11:00.0990704Z Running test_reductions 1/1 ... [2025-08-14 21:11:00.098896]
2025-08-14T21:11:00.0991414Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:11:00.0994686Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_reductions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:11:00.099223]
2025-08-14T21:14:27.7844261Z 
2025-08-14T21:14:27.7845777Z test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_1.1_780a2db777f96eba_.log
2025-08-14T21:14:27.9627192Z Running 4673 items in this shard: test/test_reductions.py::TestReductionsCPU::test_accreal_type_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int64, 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test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_all_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_all_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_sum_all_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_cpu_device_mismatch_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_reduction_uint8_overflow_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_out_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_parallel_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_argmax_argmix_kthvalue_dim_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_reduce_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_cpu, test/test_reductions.py::TestReductionsCPU::test_var_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_var_large_input_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_all_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability2_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability_cpu, test/test_reductions.py::TestReductionsCPU::test_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float64
2025-08-14T21:14:28.1371924Z 
2025-08-14T21:14:28.1372109Z Running test_nn 1/1 ... [2025-08-14 21:14:27.790065]
2025-08-14T21:14:28.1372537Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:14:28.1373534Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:14:27.790404]
2025-08-14T21:17:09.2347595Z 
2025-08-14T21:17:09.2348388Z test_nn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_1.1_6f3eb9392a44d24d_.log
2025-08-14T21:17:09.3561694Z Running 2230 items in this shard: test/test_nn.py::TestNN::test_AdaptiveLogSoftmax, test/test_nn.py::TestNN::test_AdaptiveLogSoftmax_cuda, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_reduce, test/test_nn.py::TestNN::test_BCELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_CELU_no_batch_dim, test/test_nn.py::TestNN::test_CELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_CTCLoss_critical_target_len, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cpu, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cuda, test/test_nn.py::TestNN::test_CTCLoss_long_targets, test/test_nn.py::TestNN::test_CTCLoss_typechecks, test/test_nn.py::TestNN::test_CTCLoss_zero_infinity, test/test_nn.py::TestNN::test_CTCLoss_zero_lengths, test/test_nn.py::TestNN::test_Conv1d, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_cuda, test/test_nn.py::TestNN::test_Conv1d_dilated, test/test_nn.py::TestNN::test_Conv1d_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_groups, test/test_nn.py::TestNN::test_Conv1d_groups_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1, test/test_nn.py::TestNN::test_Conv1d_pad1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1size1, test/test_nn.py::TestNN::test_Conv1d_pad1size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2, test/test_nn.py::TestNN::test_Conv1d_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2size1, test/test_nn.py::TestNN::test_Conv1d_pad2size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same, test/test_nn.py::TestNN::test_Conv1d_pad_same2, test/test_nn.py::TestNN::test_Conv1d_pad_same2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_valid, test/test_nn.py::TestNN::test_Conv1d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_stride, test/test_nn.py::TestNN::test_Conv1d_stride_cuda, test/test_nn.py::TestNN::test_Conv1d_zero_batch, test/test_nn.py::TestNN::test_Conv1d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise, test/test_nn.py::TestNN::test_Conv2d_depthwise_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated, test/test_nn.py::TestNN::test_Conv2d_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups, test/test_nn.py::TestNN::test_Conv2d_groups_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias, test/test_nn.py::TestNN::test_Conv2d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same, test/test_nn.py::TestNN::test_Conv2d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_valid, test/test_nn.py::TestNN::test_Conv2d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv2d_padding, test/test_nn.py::TestNN::test_Conv2d_padding_cuda, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_strided, test/test_nn.py::TestNN::test_Conv2d_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch, test/test_nn.py::TestNN::test_Conv2d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated, test/test_nn.py::TestNN::test_Conv3d_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated_strided, test/test_nn.py::TestNN::test_Conv3d_dilated_strided_cuda, test/test_nn.py::TestNN::test_Conv3d_groups, test/test_nn.py::TestNN::test_Conv3d_groups_cuda, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias, test/test_nn.py::TestNN::test_Conv3d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same, test/test_nn.py::TestNN::test_Conv3d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_valid, test/test_nn.py::TestNN::test_Conv3d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_stride, test/test_nn.py::TestNN::test_Conv3d_stride_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding, test/test_nn.py::TestNN::test_Conv3d_stride_padding_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch, test/test_nn.py::TestNN::test_Conv3d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d, test/test_nn.py::TestNN::test_ConvTranspose1d_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_groups, test/test_nn.py::TestNN::test_ConvTranspose1d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d, test/test_nn.py::TestNN::test_ConvTranspose2d_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d, test/test_nn.py::TestNN::test_ConvTranspose3d_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated_cuda, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_CrossMapLRN2d, test/test_nn.py::TestNN::test_CrossMapLRN2d_cuda, test/test_nn.py::TestNN::test_ELU_no_batch_dim, test/test_nn.py::TestNN::test_ELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Embedding, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max, test/test_nn.py::TestNN::test_EmbeddingBag_max_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean, test/test_nn.py::TestNN::test_EmbeddingBag_mean_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sparse, test/test_nn.py::TestNN::test_EmbeddingBag_sparse_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum, test/test_nn.py::TestNN::test_EmbeddingBag_sum_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx_cuda, test/test_nn.py::TestNN::test_Embedding_cuda, test/test_nn.py::TestNN::test_Embedding_discontiguous, test/test_nn.py::TestNN::test_Embedding_discontiguous_cuda, test/test_nn.py::TestNN::test_Embedding_sparse, test/test_nn.py::TestNN::test_Embedding_sparse_cuda, test/test_nn.py::TestNN::test_Flatten, test/test_nn.py::TestNN::test_Flatten_cuda, test/test_nn.py::TestNN::test_Flatten_no_batch_dim, test/test_nn.py::TestNN::test_Flatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Fold, test/test_nn.py::TestNN::test_Fold_cuda, test/test_nn.py::TestNN::test_Fold_int_input, test/test_nn.py::TestNN::test_Fold_int_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input_cuda, test/test_nn.py::TestNN::test_GELU_no_batch_dim, test/test_nn.py::TestNN::test_GELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_GLU_no_batch_dim, test/test_nn.py::TestNN::test_GLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_HuberLoss_delta, test/test_nn.py::TestNN::test_HuberLoss_delta_cuda, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_reduce, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_LSTM_cell, test/test_nn.py::TestNN::test_LSTM_cell_forward_hidden_size, test/test_nn.py::TestNN::test_LSTM_cell_forward_input_size, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_cuda, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval_cuda, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear, test/test_nn.py::TestNN::test_Linear_cuda, test/test_nn.py::TestNN::test_Linear_no_batch_dim, test/test_nn.py::TestNN::test_Linear_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear_no_bias, test/test_nn.py::TestNN::test_Linear_no_bias_cuda, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_reduce, test/test_nn.py::TestNN::test_MSELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MaxUnpool1d_net, test/test_nn.py::TestNN::test_MaxUnpool1d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net, test/test_nn.py::TestNN::test_MaxUnpool2d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net, test/test_nn.py::TestNN::test_MaxUnpool3d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Mish_no_batch_dim, test/test_nn.py::TestNN::test_Mish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ModuleDict, test/test_nn.py::TestNN::test_ModuleList, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_reduce, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg_cuda, test/test_nn.py::TestNN::test_PReLU_backward_requires_grad_false, test/test_nn.py::TestNN::test_PReLU_no_batch_dim, test/test_nn.py::TestNN::test_PReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args_cuda, test/test_nn.py::TestNN::test_ParameterDict, test/test_nn.py::TestNN::test_ParameterDict_replication, test/test_nn.py::TestNN::test_ParameterList, test/test_nn.py::TestNN::test_ParameterList_meta, test/test_nn.py::TestNN::test_ParameterList_replication, test/test_nn.py::TestNN::test_PixelShuffle, test/test_nn.py::TestNN::test_PixelShuffle_cuda, test/test_nn.py::TestNN::test_PixelUnshuffle, test/test_nn.py::TestNN::test_PixelUnshuffle_cuda, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_RNN_cell, test/test_nn.py::TestNN::test_RNN_cell_forward_zero_hidden_size, test/test_nn.py::TestNN::test_RNN_cell_no_broadcasting, test/test_nn.py::TestNN::test_RNN_change_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_no_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_with_dropout, test/test_nn.py::TestNN::test_RNN_cudnn_weight_norm, test/test_nn.py::TestNN::test_RNN_dropout, test/test_nn.py::TestNN::test_RNN_dropout_state, test/test_nn.py::TestNN::test_RNN_input_size_zero, test/test_nn.py::TestNN::test_RNN_nonlinearity, test/test_nn.py::TestNN::test_RNN_nonlinearity_passed_as_arg, test/test_nn.py::TestNN::test_RReLU, test/test_nn.py::TestNN::test_RReLU_cuda, test/test_nn.py::TestNN::test_RReLU_no_batch_dim, test/test_nn.py::TestNN::test_RReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down, test/test_nn.py::TestNN::test_RReLU_with_up_down_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar_cuda, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReLU_no_batch_dim, test/test_nn.py::TestNN::test_ReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d, test/test_nn.py::TestNN::test_ReplicationPad3d_complex, test/test_nn.py::TestNN::test_ReplicationPad3d_complex_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SELU_no_batch_dim, test/test_nn.py::TestNN::test_SELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sequential_add, test/test_nn.py::TestNN::test_Sequential_append, test/test_nn.py::TestNN::test_Sequential_delitem, test/test_nn.py::TestNN::test_Sequential_extend, test/test_nn.py::TestNN::test_Sequential_getitem, test/test_nn.py::TestNN::test_Sequential_iadd, test/test_nn.py::TestNN::test_Sequential_imul, test/test_nn.py::TestNN::test_Sequential_insert, test/test_nn.py::TestNN::test_Sequential_insert_fail_case, test/test_nn.py::TestNN::test_Sequential_mul, test/test_nn.py::TestNN::test_Sequential_pop, test/test_nn.py::TestNN::test_Sequential_rmul, test/test_nn.py::TestNN::test_Sequential_setitem, test/test_nn.py::TestNN::test_Sequential_setitem_named, test/test_nn.py::TestNN::test_SiLU_no_batch_dim, test/test_nn.py::TestNN::test_SiLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_beta_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta_cuda, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_Softplus_no_batch_dim, test/test_nn.py::TestNN::test_Softplus_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softsign_no_batch_dim, test/test_nn.py::TestNN::test_Softsign_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanh_no_batch_dim, test/test_nn.py::TestNN::test_Tanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Threshold_no_batch_dim, test/test_nn.py::TestNN::test_Threshold_no_batch_dim_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_Transformer_cell, test/test_nn.py::TestNN::test_Transformer_multilayer_coder, test/test_nn.py::TestNN::test_Transformer_multilayer_coder_cuda, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Unfold, test/test_nn.py::TestNN::test_Unfold_cuda, test/test_nn.py::TestNN::test_Unfold_int_input, test/test_nn.py::TestNN::test_Unfold_int_input_cuda, test/test_nn.py::TestNN::test_adaptive_log_softmax, test/test_nn.py::TestNN::test_add_module, test/test_nn.py::TestNN::test_add_module_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_affine_grid, test/test_nn.py::TestNN::test_affine_grid_3d, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_2, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_3, test/test_nn.py::TestNN::test_affine_grid_error_checking, test/test_nn.py::TestNN::test_assignment, test/test_nn.py::TestNN::test_batch_norm_update_stats, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_buffer_update_when_stats_are_not_tracked, test/test_nn.py::TestNN::test_batchnorm_cudnn_half, test/test_nn.py::TestNN::test_batchnorm_cudnn_nhwc, test/test_nn.py::TestNN::test_batchnorm_half_overflow, test/test_nn.py::TestNN::test_batchnorm_load_state_dict, test/test_nn.py::TestNN::test_batchnorm_nhwc_cpu, test/test_nn.py::TestNN::test_batchnorm_nhwc_cuda, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_BatchNorm2d, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_SyncBatchNorm, test/test_nn.py::TestNN::test_batchnorm_nonaffine_cuda_half_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_bias_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_less_than_one_value_per_channel, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_mean_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_or_running_mean_have_forward_grad, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_weight_is_not_same_size_as_input, test/test_nn.py::TestNN::test_bce_loss_always_nonnegative, test/test_nn.py::TestNN::test_bce_loss_broadcasts_weights, test/test_nn.py::TestNN::test_bce_loss_input_range, test/test_nn.py::TestNN::test_bce_loss_size_mismatch, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_pos_weights, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_weights, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss_large_tensors_with_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_forward_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bce_with_logits_ones_in_pos_weights_are_the_same_as_none, test/test_nn.py::TestNN::test_bce_with_logits_raises_if_target_and_input_are_different_size, test/test_nn.py::TestNN::test_bce_with_logits_stability, test/test_nn.py::TestNN::test_bce_with_logits_with_pos_weight_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bilinear, test/test_nn.py::TestNN::test_bilinear_broadcasting, test/test_nn.py::TestNN::test_bilinear_no_bias, test/test_nn.py::TestNN::test_bilinear_non_contiguous, test/test_nn.py::TestNN::test_bilinear_value_error, test/test_nn.py::TestNN::test_broadcast_double_backwards_gpu, test/test_nn.py::TestNN::test_broadcast_no_grad, test/test_nn.py::TestNN::test_broadcast_not_requiring_grad, test/test_nn.py::TestNN::test_buffer_bad_module_subclass, test/test_nn.py::TestNN::test_buffer_not_persistent, test/test_nn.py::TestNN::test_buffer_not_persistent_assign, test/test_nn.py::TestNN::test_buffer_not_persistent_del, test/test_nn.py::TestNN::test_buffer_not_persistent_load, test/test_nn.py::TestNN::test_buffer_not_persistent_overwrite, test/test_nn.py::TestNN::test_buffers_and_named_buffers, test/test_nn.py::TestNN::test_call_supports_python_dict_output, test/test_nn.py::TestNN::test_channel_shuffle_input_checks, test/test_nn.py::TestNN::test_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_children, test/test_nn.py::TestNN::test_container_copy, test/test_nn.py::TestNN::test_convert_sync_batchnorm, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_diff_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_nonexpandable_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_invalid_shape, test/test_nn.py::TestNN::test_cosine_embedding_loss_margin_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_with_diff_type, test/test_nn.py::TestNN::test_cosine_similarity, test/test_nn.py::TestNN::test_cross_entropy_loss, test/test_nn.py::TestNN::test_cross_entropy_loss_precision, test/test_nn.py::TestNN::test_cross_entropy_loss_zero_div, test/test_nn.py::TestNN::test_cudnn_forward_exception, test/test_nn.py::TestNN::test_cudnn_rnn_dropout_states_device, test/test_nn.py::TestNN::test_cudnn_weight_format, test/test_nn.py::TestNN::test_cudnn_weight_tying, test/test_nn.py::TestNN::test_dir, test/test_nn.py::TestNN::test_dir_digit, test/test_nn.py::TestNN::test_elu_inplace_gradgrad, test/test_nn.py::TestNN::test_elu_inplace_on_view, test/test_nn.py::TestNN::test_error_RNN_seq_len_zero, test/test_nn.py::TestNN::test_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_get_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_set_extra_state, test/test_nn.py::TestNN::test_extra_state_non_dict, test/test_nn.py::TestNN::test_fb_fc_packed, test/test_nn.py::TestNN::test_flatten, test/test_nn.py::TestNN::test_fold_invalid_arg, test/test_nn.py::TestNN::test_fractional_max_pool2d_invalid_output_ratio, test/test_nn.py::TestNN::test_gaussian_nll_loss_args, test/test_nn.py::TestNN::test_gaussian_nll_loss_broadcasting, test/test_nn.py::TestNN::test_gaussian_nll_loss_scalar_var, test/test_nn.py::TestNN::test_get_buffer, test/test_nn.py::TestNN::test_get_buffer_from_submodules, test/test_nn.py::TestNN::test_getattr_with_property, test/test_nn.py::TestNN::test_grid_sample, test/test_nn.py::TestNN::test_grid_sample_3d, test/test_nn.py::TestNN::test_grid_sample_error_checking, test/test_nn.py::TestNN::test_grid_sample_nearest_neighbor_rounding_mode_consistency, test/test_nn.py::TestNN::test_hardtanh_backward, test/test_nn.py::TestNN::test_hardtanh_inplace_gradgrad, test/test_nn.py::TestNN::test_huber_loss_invalid_delta, test/test_nn.py::TestNN::test_inplace_thnn, test/test_nn.py::TestNN::test_interpolate, test/test_nn.py::TestNN::test_interpolate_bicubic_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_buffer_overflow, test/test_nn.py::TestNN::test_interpolate_illegal_memory_access, test/test_nn.py::TestNN::test_interpolate_linear_1d, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d, test/test_nn.py::TestNN::test_interpolate_nearest_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d, test/test_nn.py::TestNN::test_interpolate_nearest_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d, test/test_nn.py::TestNN::test_interpolate_nearest_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_undefined_behavior_casting, test/test_nn.py::TestNN::test_kl_div_log_softmax_target, test/test_nn.py::TestNN::test_kl_div_with_diff_type, test/test_nn.py::TestNN::test_kl_div_with_diff_type_log_target, test/test_nn.py::TestNN::test_l1_loss_correct, test/test_nn.py::TestNN::test_layer_norm_backwards_eps, test/test_nn.py::TestNN::test_layer_norm_eps, test/test_nn.py::TestNN::test_layer_norm_grads_with_create_graph_flag, test/test_nn.py::TestNN::test_layer_norm_large_tensor, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightStrided, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightStrided, test/test_nn.py::TestNN::test_linear_broadcasting, test/test_nn.py::TestNN::test_linear_raise_on_scalar_input, test/test_nn.py::TestNN::test_log_softmax_dim0, test/test_nn.py::TestNN::test_log_softmax_dim0_cuda, test/test_nn.py::TestNN::test_log_softmax_dim3, test/test_nn.py::TestNN::test_log_softmax_dim3_cuda, test/test_nn.py::TestNN::test_log_softmax_lastdim, test/test_nn.py::TestNN::test_log_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_log_softmax_scalar, test/test_nn.py::TestNN::test_log_softmax_scalar_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial, test/test_nn.py::TestNN::test_log_softmax_spatial_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial_special, test/test_nn.py::TestNN::test_log_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_loss_equal_input_target_shape, test/test_nn.py::TestNN::test_margin_ranking_loss_margin_no_reduce, test/test_nn.py::TestNN::test_margin_ranking_loss_no_reduce, test/test_nn.py::TestNN::test_max_pool1d_invalid_output_size, test/test_nn.py::TestNN::test_module_apply_inplace_op, test/test_nn.py::TestNN::test_module_backcompat, test/test_nn.py::TestNN::test_module_super_init, test/test_nn.py::TestNN::test_module_to_argparse, test/test_nn.py::TestNN::test_modules, test/test_nn.py::TestNN::test_mse_loss_size_warning, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce_cuda, test/test_nn.py::TestNN::test_named_children, test/test_nn.py::TestNN::test_named_modules, test/test_nn.py::TestNN::test_named_parameters_remove_duplicate, test/test_nn.py::TestNN::test_native_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_nested_tensor_from_mask, test/test_nn.py::TestNN::test_nested_tensor_from_mask_error, test/test_nn.py::TestNN::test_no_grad, test/test_nn.py::TestNN::test_non_leaf_parameters, test/test_nn.py::TestNN::test_normalize, test/test_nn.py::TestNN::test_overwrite_module_params_on_conversion, test/test_nn.py::TestNN::test_pack_sequence_batch_sizes_throw, test/test_nn.py::TestNN::test_pad_scalar_error, test/test_nn.py::TestNN::test_padding_list, test/test_nn.py::TestNN::test_pairwise_distance, test/test_nn.py::TestNN::test_parameter_assignment, test/test_nn.py::TestNN::test_parameterlistdict_pickle, test/test_nn.py::TestNN::test_parameterlistdict_setting_attributes, test/test_nn.py::TestNN::test_parameters_and_named_parameters, test/test_nn.py::TestNN::test_parameters_to_vector, test/test_nn.py::TestNN::test_parse_to, test/test_nn.py::TestNN::test_partial_flat_weights, test/test_nn.py::TestNN::test_pdist, test/test_nn.py::TestNN::test_pdist_cpu_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_cuda_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_empty_col, test/test_nn.py::TestNN::test_pdist_empty_row, test/test_nn.py::TestNN::test_pdist_large, test/test_nn.py::TestNN::test_pdist_zeros, test/test_nn.py::TestNN::test_pickle_module_no_weights_only_warning, test/test_nn.py::TestNN::test_pixel_shuffle_nhwc_cpu, test/test_nn.py::TestNN::test_pixel_shuffle_unshuffle, test/test_nn.py::TestNN::test_pointwise_loss_broadcast, test/test_nn.py::TestNN::test_pointwise_loss_target_grad_none_reduction, test/test_nn.py::TestNN::test_projections_errors_on_gru_and_rnn, test/test_nn.py::TestNN::test_projections_lstm_args_check, test/test_nn.py::TestNN::test_projections_lstm_check_device, test/test_nn.py::TestNN::test_projections_lstm_initial_hidden_state, test/test_nn.py::TestNN::test_register_buffer_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_buffer_allows_tensor_like_object, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_not_tensor, test/test_nn.py::TestNN::test_register_parameter_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_relu_inplace_on_view, test/test_nn.py::TestNN::test_repr, test/test_nn.py::TestNN::test_requires_grad_, test/test_nn.py::TestNN::test_rnn_args_check, test/test_nn.py::TestNN::test_rnn_check_device, test/test_nn.py::TestNN::test_rnn_initial_hidden_state, test/test_nn.py::TestNN::test_rnn_weight_norm, test/test_nn.py::TestNN::test_set_submodule, test/test_nn.py::TestNN::test_share_memory, test/test_nn.py::TestNN::test_smoothl1loss_intergral_target, test/test_nn.py::TestNN::test_smoothl1loss_negative_beta_not_supported, test/test_nn.py::TestNN::test_softmax_functional_dim0, test/test_nn.py::TestNN::test_softmax_functional_dim0_cuda, test/test_nn.py::TestNN::test_softmax_functional_dim3, test/test_nn.py::TestNN::test_softmax_functional_dim3_cuda, test/test_nn.py::TestNN::test_softmax_functional_scalar, test/test_nn.py::TestNN::test_softmax_functional_scalar_cuda, test/test_nn.py::TestNN::test_softmax_lastdim, test/test_nn.py::TestNN::test_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_softmax_lastdim_dtype, test/test_nn.py::TestNN::test_softmax_lastdim_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial, test/test_nn.py::TestNN::test_softmax_spatial_cuda, test/test_nn.py::TestNN::test_softmax_spatial_dtype, test/test_nn.py::TestNN::test_softmax_spatial_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial_special, test/test_nn.py::TestNN::test_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_softmin, test/test_nn.py::TestNN::test_spectral_norm, test/test_nn.py::TestNN::test_spectral_norm_dim, test/test_nn.py::TestNN::test_spectral_norm_forward, test/test_nn.py::TestNN::test_spectral_norm_load_state_dict, test/test_nn.py::TestNN::test_spectral_norm_pickle, test/test_nn.py::TestNN::test_state_dict, test/test_nn.py::TestNN::test_swap_module_params_poisons_acc_grad, test/test_nn.py::TestNN::test_sync_batchnorm_accuracy_cuda, test/test_nn.py::TestNN::test_sync_batchnorm_backward_elemt, test/test_nn.py::TestNN::test_threshold_bfloat16_half, test/test_nn.py::TestNN::test_threshold_int, test/test_nn.py::TestNN::test_to, test/test_nn.py::TestNN::test_train_errors_for_invalid_mode, test/test_nn.py::TestNN::test_transformer_args_check, test/test_nn.py::TestNN::test_transformer_layer_args_check, test/test_nn.py::TestNN::test_transformerdecoder, test/test_nn.py::TestNN::test_transformerdecoderlayer, test/test_nn.py::TestNN::test_transformerdecoderlayer_gelu, test/test_nn.py::TestNN::test_triplet_margin_loss, test/test_nn.py::TestNN::test_triplet_margin_loss_no_reduce, test/test_nn.py::TestNN::test_triplet_margin_loss_swap, test/test_nn.py::TestNN::test_triplet_margin_loss_swap_no_reduce, test/test_nn.py::TestNN::test_type, test/test_nn.py::TestNN::test_unflatten, test/test_nn.py::TestNN::test_unflatten_invalid_arg, test/test_nn.py::TestNN::test_unfold_invalid_arg, test/test_nn.py::TestNN::test_upsamplingBilinear2d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingLinear1d, test/test_nn.py::TestNN::test_upsamplingLinear1d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingTrilinear3d_spatial_invariance, test/test_nn.py::TestNN::test_upsampling_bfloat16, test/test_nn.py::TestNN::test_upsampling_not_recompute_scale_factor, test/test_nn.py::TestNN::test_upsampling_small_scale, test/test_nn.py::TestNN::test_vector_to_parameters, test/test_nn.py::TestNN::test_weight_norm, test/test_nn.py::TestNN::test_weight_norm_pickle, test/test_nn.py::TestNN::test_weighted_huber_loss, test/test_nn.py::TestNN::test_weighted_l1_loss_with_weights, test/test_nn.py::TestNN::test_weighted_mse_loss, test/test_nn.py::TestNN::test_zero_grad, test/test_nn.py::TestFusionEval::test_fuse_module_eval_numerics, test/test_nn.py::TestConstantPadNd::test_constant_pad_nd, test/test_nn.py::TestConstantPadNd::test_preserves_memory_format, test/test_nn.py::TestAddRelu::test_add_relu, test/test_nn.py::TestAddRelu::test_add_relu_broadcasting, test/test_nn.py::TestFunctionalPickle::test_pickle_softsign, test/test_nn.py::TestFusionUtils::test_fuse_conv_bn_requires_grad, test/test_nn.py::TestFusionUtils::test_fuse_linear_bn_requires_grad, test/test_nn.py::TestUtils::test_consume_prefix_in_state_dict_if_present, test/test_nn.py::TestNNDeviceTypeCPU::test_BatchNorm_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_Bilinear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_empty_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GRU_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_memory_format_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_raises_error_if_one_value_per_group_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm1d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm2d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm3d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LocalResponseNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_race_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_race_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_warnings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_deterministic_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_fails_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad1d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Transformer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Unfold_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_adaptiveavg_pool1d_shmem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate45_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate90_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_3d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_update_stats_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_channel_shuffle_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_error_if_nonfinite_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_consistent_index_target_and_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_errors_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_weight_ignore_indices_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_with_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_index_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_one_hot_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_all_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cpu_length_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_device_mask_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_with_neg_alpha_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_fold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_glu_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_bfloat16_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_hardsigmoid_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_for_single_spatial_element_during_training_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_less_than_one_value_per_channel_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_invalid_reduction_strings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_weight_bias_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_neg_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_zero_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_linear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_big_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_logsigmoid_out_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_lstmcell_backward_only_one_output_grad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_TxT_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_devices_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_forward_with_nans_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_mask_types_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_transformer_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_non_recursive_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mse_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_all_ignored_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_byte_target_matches_long_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_mean_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_none_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_sum_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_target_dim_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_mismatched_batch_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_out_of_bounds_ignore_index_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_total_weight_is_zero_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nonlinearity_propagate_nan_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_one_hot_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_overwrite_module_params_on_conversion_cpu_device_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_prelu_backward_32bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_replicatepad_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_retain_variables_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_save_lstm_compatibility_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_silu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_skip_init_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_vs_huber_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smoothl1loss_backward_zero_beta_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_smem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_grad_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_without_fully_vectorized_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_double_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_forward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_results_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_low_threshold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_negative_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_threshold_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_fast_path_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_gelu_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_default_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_correctness_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_fail_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_rocm_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_rescale_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingnearest2d_backward_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_variable_sequence_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float32
2025-08-14T21:17:09.4745806Z 
2025-08-14T21:17:09.4746015Z Running test_overrides 1/1 ... [2025-08-14 21:17:09.238758]
2025-08-14T21:17:09.4746753Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:09.4747795Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_overrides.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:09.239077]
2025-08-14T21:17:16.7688695Z 
2025-08-14T21:17:16.7689657Z test_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_overrides_1.1_a766f141b0f1ebbe_.log
2025-08-14T21:17:16.8183367Z Running 1470 items in this shard: test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_H___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_T___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__backward_hooks___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__base___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__cdata___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad_fn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__post_accumulate_grad_hooks___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__version___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_data___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_device___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_dtype___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_grad___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_grad_fn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_imag___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_cpu___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_cuda___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_ipu___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_leaf___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_maia___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_meta___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_mkldnn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_mps___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_mtia___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_nested___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_quantized___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_sparse___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_sparse_csr___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_vulkan___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_xla___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_xpu___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_itemsize___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_layout___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_mH___get__, 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test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_histogram, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inner, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ipu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_coalesced, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_contiguous, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_pinned, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_set_to, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_shared, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_istft, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_item, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kron, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_long, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_max, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_median, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_min, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mode, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_module_load, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_msort, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mtia, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mv, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ndimension, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nelement, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_norm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numel, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numpy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_outer, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_permute, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pin_memory, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_positive, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prod, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_put, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_put_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_axis, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_scales, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_zero_points, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_scale, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_zero_point, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_qr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_qscheme, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_quantile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rad2deg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rad2deg_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_random_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ravel, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_record_stream, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_refine_names, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_post_accumulate_grad_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_renorm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_renorm_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_repeat, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_repeat_interleave, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_requires_grad_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reshape, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reshape_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as_sparse_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resolve_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resolve_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_retain_grad, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_roll, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rot90, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_round, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_round_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_row_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rsqrt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rsqrt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_add, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_add_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_reduce_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_select_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_set_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sgn, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sgn_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_share_memory_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_short, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sigmoid, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sigmoid_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sign, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sign_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_signbit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sin, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sin_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinc_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinh_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slice_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slice_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slogdet, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_smm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sort, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_dim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_mask, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_resize_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_resize_and_clear_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sqrt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_square, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_square_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_squeeze, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_squeeze_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sspaddmm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_std, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_stft, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage_offset, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage_type, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sub, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sub_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_subtract, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_subtract_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sum_to_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_svd, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapaxes, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapaxes_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapdims, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapdims_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_t, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_t_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_take, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_take_along_dim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tan, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tan_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tanh_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_to, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_to_dense, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_to_mkldnn, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_to_sparse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tolist, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_topk, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_trace, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_transpose_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_triangular_solve, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tril, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_tril_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_triu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_triu_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_true_divide, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_true_divide_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_trunc, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_trunc_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_type, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_type_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unbind, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unfold, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unique, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unique_consecutive, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unsafe_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unsafe_split, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unsafe_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unsqueeze, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_unsqueeze_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_untyped_storage, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_values, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_var, 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test/test_overrides.py::TestTorchFunctionOverride::test_torch__native_batch_norm_legit, test/test_overrides.py::TestTorchFunctionOverride::test_torch__neg_view_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__reshape_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__rowwise_prune, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sparse_broadcast_to_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_linear_prepack, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_quantized_linear_prepacked, test/test_overrides.py::TestTorchFunctionOverride::test_torch_abs, test/test_overrides.py::TestTorchFunctionOverride::test_torch_absolute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcdiv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adjoint, test/test_overrides.py::TestTorchFunctionOverride::test_torch_affine_grid_generator, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_all, test/test_overrides.py::TestTorchFunctionOverride::test_torch_allclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_aminmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_angle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_any, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argsort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argwhere, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_baddbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats_with_counts, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_update_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bernoulli, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bilinear, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bincount, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_left_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_right_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_broadcast_to, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bucketize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ccol_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ceil, test/test_overrides.py::TestTorchFunctionOverride::test_torch_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_choose_qparams_optimized, test/test_overrides.py::TestTorchFunctionOverride::test_torch_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clone, test/test_overrides.py::TestTorchFunctionOverride::test_torch_col_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_column_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_combinations, test/test_overrides.py::TestTorchFunctionOverride::test_torch_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concatenate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj_physical, test/test_overrides.py::TestTorchFunctionOverride::test_torch_constant_pad_nd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_tbc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_copysign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_corrcoef, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_similarity, test/test_overrides.py::TestTorchFunctionOverride::test_torch_count_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cov, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cross, test/test_overrides.py::TestTorchFunctionOverride::test_torch_crow_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumprod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumulative_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_deg2rad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dequantize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_det, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag_embed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagflat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diff, test/test_overrides.py::TestTorchFunctionOverride::test_torch_digamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_empty_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_eq, test/test_overrides.py::TestTorchFunctionOverride::test_torch_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfinv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expand_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expm1, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_channel_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_tensor_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_quantize_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_gemm_matrix_fp16, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_quantized_matrix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fliplr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flipud, test/test_overrides.py::TestTorchFunctionOverride::test_torch_float_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frobenius_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_full_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_block_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_broadcast_tensors, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cartesian_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_chain_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_einsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_lu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_meshgrid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_stft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_tensordot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique_consecutive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unravel_index, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fused_moving_avg_obs_fake_quant, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gather, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gcd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ge, test/test_overrides.py::TestTorchFunctionOverride::test_torch_geqrf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ger, test/test_overrides.py::TestTorchFunctionOverride::test_torch_get_device, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gradient, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hardshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hash_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_heaviside, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogram, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogramdd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_i0, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_imag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inner, test/test_overrides.py::TestTorchFunctionOverride::test_torch_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_istft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kron, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_torch_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_le, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log10, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_unpack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_median, test/test_overrides.py::TestTorchFunctionOverride::test_torch_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_add_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_depthwise_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_rnn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mode, test/test_overrides.py::TestTorchFunctionOverride::test_torch_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_msort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ne, test/test_overrides.py::TestTorchFunctionOverride::test_torch_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_negative, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional__threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_affine_grid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_elu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gaussian_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_glu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_grid_sample, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gumbel_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hardtanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_huber_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_interpolate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_leaky_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_local_response_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mish, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mse_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_head_attention_forward, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_normalize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_pad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu6, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_silu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_smooth_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softsign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_tanhshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_with_distance_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_unfold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_constant_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_kaiming_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_torch_norm_except_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nuclear_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_numel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ones_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_outer, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pairwise_distance, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_unshuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polar, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_positive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_axis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_scales, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_zero_points, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_scale, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_zero_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_qr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_channel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor_dynamic, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rad2deg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rand_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randint_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randn_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ravel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_torch_renorm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_repeat_interleave, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reshape, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_roll, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rot90, test/test_overrides.py::TestTorchFunctionOverride::test_torch_round, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_saddmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_searchsorted, test/test_overrides.py::TestTorchFunctionOverride::test_torch_segment_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sgn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sigmoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_signbit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slogdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_smm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_square, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_subtract, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_svd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapaxes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapdims, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_float, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_int, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_ite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take_along_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_topk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trace, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapz, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triangular_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tril, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_true_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trunc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unflatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unfold_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vdot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_where, test/test_overrides.py::TestTorchFunctionOverride::test_torch_xlogy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_zeros_like, test/test_overrides.py::TestTorchFunctionOverride::test_user_implementation_raises, test/test_overrides.py::TestEinsumOverride::test_wrapper, test/test_overrides.py::TestGradCheckOverride::test_gradcheck, test/test_overrides.py::TestNamedTuple::test_max, test/test_overrides.py::TestGradNewOnesOverride::test_newones, test/test_overrides.py::TestPickle::test_pickle, test/test_overrides.py::TestBroadcastAllOverride::test_broadcast_all, test/test_overrides.py::TestWrapTorchFunction::test_wrap_torch_function, test/test_overrides.py::TestIndexing::test_getitem, test/test_overrides.py::TestIndexing::test_getitem_subclass, test/test_overrides.py::TestIndexing::test_setitem, test/test_overrides.py::TestIndexing::test_setitem_subclass, test/test_overrides.py::TestIndexing::test_setitem_val, test/test_overrides.py::TestIterator::test_iterator, test/test_overrides.py::TestRNN::test_rnn, test/test_overrides.py::TestDisabledTorchFunction::test_parameter_does_not_prevent_dispatch, test/test_overrides.py::TestResolveName::test_resolve_name, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_standalone_class, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_tensor_subclass, test/test_overrides.py::TestDisabledUserWarnings::test_no_implicit_user_warning_for_deprecated_functions, test/test_overrides.py::TestTorchFunctionMode::test_all_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_basic, test/test_overrides.py::TestTorchFunctionMode::test_custom_device_type, test/test_overrides.py::TestTorchFunctionMode::test_device_context_semantics, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_subclass, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_torch_function_ctx, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_mode, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_not_mode, test/test_overrides.py::TestTorchFunctionMode::test_distributions_bernoulli, test/test_overrides.py::TestTorchFunctionMode::test_error_using_class_method_on_mode, test/test_overrides.py::TestTorchFunctionMode::test_factory_override, test/test_overrides.py::TestTorchFunctionMode::test_get_cur_mode, test/test_overrides.py::TestTorchFunctionMode::test_get_mode_stack, test/test_overrides.py::TestTorchFunctionMode::test_getitem_call, test/test_overrides.py::TestTorchFunctionMode::test_mode_notimplemented_loop, test/test_overrides.py::TestTorchFunctionMode::test_modes_handle_first, test/test_overrides.py::TestTorchFunctionMode::test_modes_return_notimplemented, test/test_overrides.py::TestTorchFunctionMode::test_nested_modes_with_python_has_torch_function, test/test_overrides.py::TestTorchFunctionMode::test_nested_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_nn_parse_to, test/test_overrides.py::TestTorchFunctionMode::test_reentrant_mode_idiom, test/test_overrides.py::TestTorchFunctionMode::test_restacking_with_ancestor, test/test_overrides.py::TestTorchFunctionMode::test_subclass_hash, test/test_overrides.py::TestTorchFunctionMode::test_torch_function_all_disabled_api, test/test_overrides.py::TestTorchFunctionMode::test_with_mode, test/test_overrides.py::TestTorchFunctionMode::test_with_mode_created_separately, test/test_overrides.py::TestTorchFunctionMode::test_with_nested_modes
2025-08-14T21:17:16.8665797Z 
2025-08-14T21:17:16.8665979Z Running doctests 1/1 ... [2025-08-14 21:17:16.770797]
2025-08-14T21:17:16.8844514Z Start doctest_module('/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch')
2025-08-14T21:17:16.8845037Z Listing tests
2025-08-14T21:17:17.2841655Z msg = Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493.
2025-08-14T21:17:17.2842702Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.2843096Z 
2025-08-14T21:17:17.2843244Z dim_order(ambiguity_check=False) -> tuple
2025-08-14T21:17:17.2843530Z 
2025-08-14T21:17:17.2843783Z Returns the uniquely determined tuple of int describing the dim order or
2025-08-14T21:17:17.2844312Z physical layout of :attr:`self`.
2025-08-14T21:17:17.2844527Z 
2025-08-14T21:17:17.2844785Z The dim order represents how dimensions are laid out in memory of dense tensors,
2025-08-14T21:17:17.2845400Z starting from the outermost to the innermost dimension.
2025-08-14T21:17:17.2845696Z 
2025-08-14T21:17:17.2845936Z Note that the dim order may not always be uniquely determined.
2025-08-14T21:17:17.2846677Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined;
2025-08-14T21:17:17.2847653Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted
2025-08-14T21:17:17.2848491Z into exactly one of the given memory formats, or it cannot be uniquely determined.
2025-08-14T21:17:17.2849253Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness.
2025-08-14T21:17:17.2849862Z Otherwise, it will raise TypeError.
2025-08-14T21:17:17.2850088Z 
2025-08-14T21:17:17.2850170Z Args:
2025-08-14T21:17:17.2850799Z     ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order.
2025-08-14T21:17:17.2851297Z 
2025-08-14T21:17:17.2851444Z Examples::
2025-08-14T21:17:17.2851569Z 
2025-08-14T21:17:17.2851681Z     >>> torch.empty((2, 3, 5, 7)).dim_order()
2025-08-14T21:17:17.2852054Z     (0, 1, 2, 3)
2025-08-14T21:17:17.2852358Z     >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order()
2025-08-14T21:17:17.2852776Z     (0, 2, 1, 3)
2025-08-14T21:17:17.2853119Z     >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order()
2025-08-14T21:17:17.2853588Z     (0, 2, 3, 1)
2025-08-14T21:17:17.2853844Z     >>> torch.empty((1, 2, 3, 4)).dim_order()
2025-08-14T21:17:17.2854193Z     (0, 1, 2, 3)
2025-08-14T21:17:17.2854425Z     >>> try:
2025-08-14T21:17:17.2854726Z     ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True)
2025-08-14T21:17:17.2855177Z     ... except RuntimeError as e:
2025-08-14T21:17:17.2855477Z     ...     print(e)
2025-08-14T21:17:17.2856005Z     The tensor does not have unique dim order, or cannot map to exact one of the given memory formats.
2025-08-14T21:17:17.2856610Z     >>> torch.empty((1, 2, 3, 4)).dim_order(
2025-08-14T21:17:17.2857035Z     ...     ambiguity_check=[torch.contiguous_format, torch.channels_last]
2025-08-14T21:17:17.2857560Z     ... )  # It can be mapped to contiguous format
2025-08-14T21:17:17.2857890Z     (0, 1, 2, 3)
2025-08-14T21:17:17.2858162Z     >>> try:
2025-08-14T21:17:17.2858486Z     ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL")
2025-08-14T21:17:17.2858950Z     ... except TypeError as e:
2025-08-14T21:17:17.2859220Z     ...     print(e)
2025-08-14T21:17:17.2859654Z     The ambiguity_check argument must be a bool or a list of memory formats.
2025-08-14T21:17:17.2860018Z 
2025-08-14T21:17:17.2860151Z .. warning::
2025-08-14T21:17:17.2860510Z     The dim_order tensor API is experimental and subject to change.
2025-08-14T21:17:17.2860818Z 
2025-08-14T21:17:17.2861068Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.2861454Z 
2025-08-14T21:17:17.3393412Z msg = Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=446.
2025-08-14T21:17:17.3394395Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3395079Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors.
2025-08-14T21:17:17.3395442Z 
2025-08-14T21:17:17.3395907Z         This is helpful when you want to visualize data over some
2025-08-14T21:17:17.3396367Z         range of inputs. See below for a plotting example.
2025-08-14T21:17:17.3396707Z 
2025-08-14T21:17:17.3396874Z         Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as
2025-08-14T21:17:17.3397405Z         inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`,
2025-08-14T21:17:17.3397890Z         this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots
2025-08-14T21:17:17.3398414Z         G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where
2025-08-14T21:17:17.3398951Z         the output :math:`G_i` is constructed by expanding :math:`T_i`
2025-08-14T21:17:17.3399357Z         to the result shape.
2025-08-14T21:17:17.3399592Z 
2025-08-14T21:17:17.3399715Z         .. note::
2025-08-14T21:17:17.3400024Z             0D inputs are treated equivalently to 1D inputs of a
2025-08-14T21:17:17.3400461Z             single element.
2025-08-14T21:17:17.3400637Z 
2025-08-14T21:17:17.3400728Z         .. warning::
2025-08-14T21:17:17.3401110Z             `torch.meshgrid(*tensors)` currently has the same behavior
2025-08-14T21:17:17.3401589Z             as calling `numpy.meshgrid(*arrays, indexing='ij')`.
2025-08-14T21:17:17.3401913Z 
2025-08-14T21:17:17.3402069Z             In the future `torch.meshgrid` will transition to
2025-08-14T21:17:17.3402454Z             `indexing='xy'` as the default.
2025-08-14T21:17:17.3402739Z 
2025-08-14T21:17:17.3402938Z             https://github.com/pytorch/pytorch/issues/50276 tracks
2025-08-14T21:17:17.3403594Z             this issue with the goal of migrating to NumPy's behavior.
2025-08-14T21:17:17.3403888Z 
2025-08-14T21:17:17.3403983Z         .. seealso::
2025-08-14T21:17:17.3404185Z 
2025-08-14T21:17:17.3404369Z             :func:`torch.cartesian_prod` has the same effect but it
2025-08-14T21:17:17.3404796Z             collects the data in a tensor of vectors.
2025-08-14T21:17:17.3405096Z 
2025-08-14T21:17:17.3405195Z         Args:
2025-08-14T21:17:17.3405583Z             tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be
2025-08-14T21:17:17.3406199Z                 treated as tensors of size :math:`(1,)` automatically
2025-08-14T21:17:17.3406526Z 
2025-08-14T21:17:17.3406718Z             indexing: (str, optional): the indexing mode, either "xy"
2025-08-14T21:17:17.3407188Z                 or "ij", defaults to "ij". See warning for future changes.
2025-08-14T21:17:17.3407520Z 
2025-08-14T21:17:17.3407677Z                 If "xy" is selected, the first dimension corresponds
2025-08-14T21:17:17.3408168Z                 to the cardinality of the second input and the second
2025-08-14T21:17:17.3408620Z                 dimension corresponds to the cardinality of the first
2025-08-14T21:17:17.3409213Z                 input.
2025-08-14T21:17:17.3409462Z 
2025-08-14T21:17:17.3409687Z                 If "ij" is selected, the dimensions are in the same
2025-08-14T21:17:17.3410285Z                 order as the cardinality of the inputs.
2025-08-14T21:17:17.3410651Z 
2025-08-14T21:17:17.3410814Z         Returns:
2025-08-14T21:17:17.3411216Z             seq (sequence of Tensors): If the input has :math:`N`
2025-08-14T21:17:17.3411754Z             tensors of size :math:`S_0 \ldots S_{N-1}``, then the
2025-08-14T21:17:17.3412381Z             output will also have :math:`N` tensors, where each tensor
2025-08-14T21:17:17.3412926Z             is of shape :math:`(S_0, ..., S_{N-1})`.
2025-08-14T21:17:17.3413258Z 
2025-08-14T21:17:17.3413469Z         Example::
2025-08-14T21:17:17.3413765Z 
2025-08-14T21:17:17.3414064Z             >>> x = torch.tensor([1, 2, 3])
2025-08-14T21:17:17.3414631Z             >>> y = torch.tensor([4, 5, 6])
2025-08-14T21:17:17.3415056Z 
2025-08-14T21:17:17.3415282Z             Observe the element-wise pairings across the grid, (1, 4),
2025-08-14T21:17:17.3415744Z             (1, 5), ..., (3, 6). This is the same thing as the
2025-08-14T21:17:17.3416101Z             cartesian product.
2025-08-14T21:17:17.3416620Z             >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij')
2025-08-14T21:17:17.3416999Z             >>> grid_x
2025-08-14T21:17:17.3417239Z             tensor([[1, 1, 1],
2025-08-14T21:17:17.3417513Z                     [2, 2, 2],
2025-08-14T21:17:17.3417779Z                     [3, 3, 3]])
2025-08-14T21:17:17.3418034Z             >>> grid_y
2025-08-14T21:17:17.3418283Z             tensor([[4, 5, 6],
2025-08-14T21:17:17.3418552Z                     [4, 5, 6],
2025-08-14T21:17:17.3418807Z                     [4, 5, 6]])
2025-08-14T21:17:17.3418998Z 
2025-08-14T21:17:17.3419165Z             This correspondence can be seen when these grids are
2025-08-14T21:17:17.3419553Z             stacked properly.
2025-08-14T21:17:17.3419941Z             >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))),
2025-08-14T21:17:17.3420378Z             ...             torch.cartesian_prod(x, y))
2025-08-14T21:17:17.3420710Z             True
2025-08-14T21:17:17.3420846Z 
2025-08-14T21:17:17.3421040Z             `torch.meshgrid` is commonly used to produce a grid for
2025-08-14T21:17:17.3421414Z             plotting.
2025-08-14T21:17:17.3421705Z             >>> # xdoctest: +REQUIRES(module:matplotlib)
2025-08-14T21:17:17.3422083Z             >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW)
2025-08-14T21:17:17.3422440Z             >>> import matplotlib.pyplot as plt
2025-08-14T21:17:17.3422804Z             >>> xs = torch.linspace(-5, 5, steps=100)
2025-08-14T21:17:17.3423178Z             >>> ys = torch.linspace(-5, 5, steps=100)
2025-08-14T21:17:17.3423648Z             >>> x, y = torch.meshgrid(xs, ys, indexing='xy')
2025-08-14T21:17:17.3424018Z             >>> z = torch.sin(torch.sqrt(x * x + y * y))
2025-08-14T21:17:17.3424385Z             >>> ax = plt.axes(projection='3d')
2025-08-14T21:17:17.3424775Z             >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy())
2025-08-14T21:17:17.3425130Z             >>> plt.show()
2025-08-14T21:17:17.3425312Z 
2025-08-14T21:17:17.3425442Z         .. image:: ../_static/img/meshgrid.png
2025-08-14T21:17:17.3425773Z             :width: 512
2025-08-14T21:17:17.3425926Z 
2025-08-14T21:17:17.3426022Z         
2025-08-14T21:17:17.3426386Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3426768Z 
2025-08-14T21:17:17.3427258Z msg = Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=842.
2025-08-14T21:17:17.3428134Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3428899Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor]
2025-08-14T21:17:17.3429408Z 
2025-08-14T21:17:17.3429558Z     Returns the unique elements of the input tensor.
2025-08-14T21:17:17.3429829Z 
2025-08-14T21:17:17.3430125Z     .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that
2025-08-14T21:17:17.3430777Z         this function also eliminates non-consecutive duplicate values.
2025-08-14T21:17:17.3431104Z 
2025-08-14T21:17:17.3431351Z     .. note:: Currently in the CUDA implementation and the CPU implementation,
2025-08-14T21:17:17.3432058Z         `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument.
2025-08-14T21:17:17.3432759Z         Sorting could be slow, so if your input tensor is already sorted, it is recommended to use
2025-08-14T21:17:17.3433345Z         :func:`torch.unique_consecutive` which avoids the sorting.
2025-08-14T21:17:17.3433661Z 
2025-08-14T21:17:17.3433784Z     Args:
2025-08-14T21:17:17.3434140Z         input (Tensor): the input tensor
2025-08-14T21:17:17.3434955Z         sorted (bool): Whether to sort the unique elements in ascending order
2025-08-14T21:17:17.3465668Z             before returning as output.
2025-08-14T21:17:17.3466237Z         return_inverse (bool): Whether to also return the indices for where
2025-08-14T21:17:17.3466802Z             elements in the original input ended up in the returned unique list.
2025-08-14T21:17:17.3467502Z         return_counts (bool): Whether to also return the counts for each unique
2025-08-14T21:17:17.3467947Z             element.
2025-08-14T21:17:17.3468305Z         dim (int, optional): the dimension to operate upon. If ``None``, the
2025-08-14T21:17:17.3468846Z             unique of the flattened input is returned. Otherwise, each of the
2025-08-14T21:17:17.3469372Z             tensors indexed by the given dimension is treated as one of the
2025-08-14T21:17:17.3469894Z             elements to apply the unique operation upon. See examples for more
2025-08-14T21:17:17.3470349Z             details. Default: ``None``
2025-08-14T21:17:17.3470573Z 
2025-08-14T21:17:17.3470661Z     Returns:
2025-08-14T21:17:17.3471084Z         (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing
2025-08-14T21:17:17.3471574Z 
2025-08-14T21:17:17.3471776Z             - **output** (*Tensor*): the output list of unique scalar elements.
2025-08-14T21:17:17.3472240Z             - **inverse_indices** (*Tensor*): (optional) if
2025-08-14T21:17:17.3472682Z               :attr:`return_inverse` is True, there will be an additional
2025-08-14T21:17:17.3473179Z               returned tensor (same shape as input) representing the indices
2025-08-14T21:17:17.3473699Z               for where elements in the original input map to in the output;
2025-08-14T21:17:17.3474204Z               otherwise, this function will only return a single tensor.
2025-08-14T21:17:17.3474638Z             - **counts** (*Tensor*): (optional) if
2025-08-14T21:17:17.3475109Z               :attr:`return_counts` is True, there will be an additional
2025-08-14T21:17:17.3475595Z               returned tensor (same shape as output or output.size(dim),
2025-08-14T21:17:17.3476090Z               if dim was specified) representing the number of occurrences
2025-08-14T21:17:17.3476504Z               for each unique value or tensor.
2025-08-14T21:17:17.3476738Z 
2025-08-14T21:17:17.3476836Z     Example::
2025-08-14T21:17:17.3476969Z 
2025-08-14T21:17:17.3477183Z         >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long))
2025-08-14T21:17:17.3477591Z         >>> output
2025-08-14T21:17:17.3477808Z         tensor([1, 2, 3])
2025-08-14T21:17:17.3477977Z 
2025-08-14T21:17:17.3478099Z         >>> output, inverse_indices = torch.unique(
2025-08-14T21:17:17.3478565Z         ...     torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True)
2025-08-14T21:17:17.3478984Z         >>> output
2025-08-14T21:17:17.3479211Z         tensor([1, 2, 3])
2025-08-14T21:17:17.3479460Z         >>> inverse_indices
2025-08-14T21:17:17.3479712Z         tensor([0, 2, 1, 2])
2025-08-14T21:17:17.3479882Z 
2025-08-14T21:17:17.3480000Z         >>> output, inverse_indices = torch.unique(
2025-08-14T21:17:17.3480471Z         ...     torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True)
2025-08-14T21:17:17.3480907Z         >>> output
2025-08-14T21:17:17.3481125Z         tensor([1, 2, 3])
2025-08-14T21:17:17.3481385Z         >>> inverse_indices
2025-08-14T21:17:17.3481637Z         tensor([[0, 2],
2025-08-14T21:17:17.3481862Z                 [1, 2]])
2025-08-14T21:17:17.3482020Z 
2025-08-14T21:17:17.3482115Z         >>> a = torch.tensor([
2025-08-14T21:17:17.3482373Z         ...     [
2025-08-14T21:17:17.3482585Z         ...         [1, 1, 0, 0],
2025-08-14T21:17:17.3482850Z         ...         [1, 1, 0, 0],
2025-08-14T21:17:17.3483111Z         ...         [0, 0, 1, 1],
2025-08-14T21:17:17.3483369Z         ...     ],
2025-08-14T21:17:17.3483572Z         ...     [
2025-08-14T21:17:17.3483786Z         ...         [0, 0, 1, 1],
2025-08-14T21:17:17.3484050Z         ...         [0, 0, 1, 1],
2025-08-14T21:17:17.3484300Z         ...         [1, 1, 1, 1],
2025-08-14T21:17:17.3484556Z         ...     ],
2025-08-14T21:17:17.3484768Z         ...     [
2025-08-14T21:17:17.3484976Z         ...         [1, 1, 0, 0],
2025-08-14T21:17:17.3485232Z         ...         [1, 1, 0, 0],
2025-08-14T21:17:17.3485552Z         ...         [0, 0, 1, 1],
2025-08-14T21:17:17.3485804Z         ...     ],
2025-08-14T21:17:17.3486015Z         ... ])
2025-08-14T21:17:17.3486137Z 
2025-08-14T21:17:17.3486348Z         >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]`
2025-08-14T21:17:17.3486878Z         >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match
2025-08-14T21:17:17.3487316Z         >>> # each other, so one of them will be removed.
2025-08-14T21:17:17.3487656Z         >>> (a[0, :, :] == a[2, :, :]).all()
2025-08-14T21:17:17.3487956Z         tensor(True)
2025-08-14T21:17:17.3488209Z         >>> a_unique_dim0 = torch.unique(a, dim=0)
2025-08-14T21:17:17.3488525Z         >>> a_unique_dim0
2025-08-14T21:17:17.3488772Z         tensor([[[0, 0, 1, 1],
2025-08-14T21:17:17.3489020Z                  [0, 0, 1, 1],
2025-08-14T21:17:17.3489277Z                  [1, 1, 1, 1]],
2025-08-14T21:17:17.3489537Z                 [[1, 1, 0, 0],
2025-08-14T21:17:17.3489778Z                  [1, 1, 0, 0],
2025-08-14T21:17:17.3490035Z                  [0, 0, 1, 1]]])
2025-08-14T21:17:17.3490206Z 
2025-08-14T21:17:17.3490425Z         >>> # Notice which sub-tensors from `a` match with the sub-tensors from
2025-08-14T21:17:17.3490842Z         >>> # `a_unique_dim0`:
2025-08-14T21:17:17.3491128Z         >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all()
2025-08-14T21:17:17.3491442Z         tensor(True)
2025-08-14T21:17:17.3491702Z         >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all()
2025-08-14T21:17:17.3492069Z         tensor(True)
2025-08-14T21:17:17.3492222Z 
2025-08-14T21:17:17.3492418Z         >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are
2025-08-14T21:17:17.3492911Z         >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of
2025-08-14T21:17:17.3493295Z         >>> # them will be removed.
2025-08-14T21:17:17.3493591Z         >>> (a[:, 0, :] == a[:, 1, :]).all()
2025-08-14T21:17:17.3493884Z         tensor(True)
2025-08-14T21:17:17.3494130Z         >>> torch.unique(a, dim=1)
2025-08-14T21:17:17.3494411Z         tensor([[[0, 0, 1, 1],
2025-08-14T21:17:17.3494674Z                  [1, 1, 0, 0]],
2025-08-14T21:17:17.3494931Z                 [[1, 1, 1, 1],
2025-08-14T21:17:17.3495178Z                  [0, 0, 1, 1]],
2025-08-14T21:17:17.3495432Z                 [[0, 0, 1, 1],
2025-08-14T21:17:17.3495685Z                  [1, 1, 0, 0]]])
2025-08-14T21:17:17.3495859Z 
2025-08-14T21:17:17.3496066Z         >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared.
2025-08-14T21:17:17.3496558Z         >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and
2025-08-14T21:17:17.3497005Z         >>> # `a[:, :, 3]` match each other as well. So in this case, two of the
2025-08-14T21:17:17.3497406Z         >>> # sub-tensors will be removed.
2025-08-14T21:17:17.3497714Z         >>> (a[:, :, 0] == a[:, :, 1]).all()
2025-08-14T21:17:17.3498000Z         tensor(True)
2025-08-14T21:17:17.3498237Z         >>> (a[:, :, 2] == a[:, :, 3]).all()
2025-08-14T21:17:17.3498547Z         tensor(True)
2025-08-14T21:17:17.3498790Z         >>> torch.unique(a, dim=2)
2025-08-14T21:17:17.3499077Z         tensor([[[0, 1],
2025-08-14T21:17:17.3499308Z                  [0, 1],
2025-08-14T21:17:17.3499541Z                  [1, 0]],
2025-08-14T21:17:17.3499777Z                 [[1, 0],
2025-08-14T21:17:17.3500000Z                  [1, 0],
2025-08-14T21:17:17.3500229Z                  [1, 1]],
2025-08-14T21:17:17.3500464Z                 [[0, 1],
2025-08-14T21:17:17.3500703Z                  [0, 1],
2025-08-14T21:17:17.3500928Z                  [1, 0]]])
2025-08-14T21:17:17.3501162Z     
2025-08-14T21:17:17.3501529Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3501889Z 
2025-08-14T21:17:17.3579517Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=565.
2025-08-14T21:17:17.3580707Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3581253Z 
2025-08-14T21:17:17.3581410Z Load a model from a github repo or a local directory.
2025-08-14T21:17:17.3581680Z 
2025-08-14T21:17:17.3581948Z Note: Loading a model is the typical use case, but this can also be used to
2025-08-14T21:17:17.3582497Z for loading other objects such as tokenizers, loss functions, etc.
2025-08-14T21:17:17.3583045Z 
2025-08-14T21:17:17.3583350Z If ``source`` is 'github', ``repo_or_dir`` is expected to be
2025-08-14T21:17:17.3583856Z of the form ``repo_owner/repo_name[:ref]`` with an optional
2025-08-14T21:17:17.3584235Z ref (a tag or a branch).
2025-08-14T21:17:17.3584396Z 
2025-08-14T21:17:17.3584567Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a
2025-08-14T21:17:17.3584933Z path to a local directory.
2025-08-14T21:17:17.3585110Z 
2025-08-14T21:17:17.3585187Z Args:
2025-08-14T21:17:17.3585426Z     repo_or_dir (str): If ``source`` is 'github',
2025-08-14T21:17:17.3585976Z         this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with
2025-08-14T21:17:17.3587110Z         an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified,
2025-08-14T21:17:17.3587791Z         the default branch is assumed to be ``main`` if it exists, and otherwise ``master``.
2025-08-14T21:17:17.3588378Z         If ``source`` is 'local'  then it should be a path to a local directory.
2025-08-14T21:17:17.3588879Z     model (str): the name of a callable (entrypoint) defined in the
2025-08-14T21:17:17.3589389Z         repo/dir's ``hubconf.py``.
2025-08-14T21:17:17.3589796Z     *args (optional): the corresponding args for callable ``model``.
2025-08-14T21:17:17.3590351Z     source (str, optional): 'github' or 'local'. Specifies how
2025-08-14T21:17:17.3590872Z         ``repo_or_dir`` is to be interpreted. Default is 'github'.
2025-08-14T21:17:17.3591849Z     trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``.
2025-08-14T21:17:17.3592421Z         This parameter was introduced in v1.12 and helps ensuring that users
2025-08-14T21:17:17.3592885Z         only run code from repos that they trust.
2025-08-14T21:17:17.3593137Z 
2025-08-14T21:17:17.3593329Z         - If ``False``, a prompt will ask the user whether the repo should
2025-08-14T21:17:17.3593736Z           be trusted.
2025-08-14T21:17:17.3594071Z         - If ``True``, the repo will be added to the trusted list and loaded
2025-08-14T21:17:17.3594515Z           without requiring explicit confirmation.
2025-08-14T21:17:17.3594943Z         - If ``"check"``, the repo will be checked against the list of
2025-08-14T21:17:17.3595428Z           trusted repos in the cache. If it is not present in that list, the
2025-08-14T21:17:17.3595953Z           behaviour will fall back onto the ``trust_repo=False`` option.
2025-08-14T21:17:17.3596452Z         - If ``None``: this will raise a warning, inviting the user to set
2025-08-14T21:17:17.3596943Z           ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This
2025-08-14T21:17:17.3597450Z           is only present for backward compatibility and will be removed in
2025-08-14T21:17:17.3597865Z           v2.0.
2025-08-14T21:17:17.3598003Z 
2025-08-14T21:17:17.3598220Z         Default is ``None`` and will eventually change to ``"check"`` in v2.0.
2025-08-14T21:17:17.3598757Z     force_reload (bool, optional): whether to force a fresh download of
2025-08-14T21:17:17.3599268Z         the github repo unconditionally. Does not have any effect if
2025-08-14T21:17:17.3599704Z         ``source = 'local'``. Default is ``False``.
2025-08-14T21:17:17.3600152Z     verbose (bool, optional): If ``False``, mute messages about hitting
2025-08-14T21:17:17.3600673Z         local caches. Note that the message about first download cannot be
2025-08-14T21:17:17.3601174Z         muted. Does not have any effect if ``source = 'local'``.
2025-08-14T21:17:17.3601563Z         Default is ``True``.
2025-08-14T21:17:17.3602030Z     skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit
2025-08-14T21:17:17.3602815Z         specified by the ``github`` argument properly belongs to the repo owner. This will make
2025-08-14T21:17:17.3603497Z         requests to the GitHub API; you can specify a non-default GitHub token by setting the
2025-08-14T21:17:17.3604075Z         ``GITHUB_TOKEN`` environment variable. Default is ``False``.
2025-08-14T21:17:17.3604578Z     **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-08-14T21:17:17.3604924Z 
2025-08-14T21:17:17.3605014Z Returns:
2025-08-14T21:17:17.3605329Z     The output of the ``model`` callable when called with the given
2025-08-14T21:17:17.3605736Z     ``*args`` and ``**kwargs``.
2025-08-14T21:17:17.3605922Z 
2025-08-14T21:17:17.3606010Z Example:
2025-08-14T21:17:17.3606275Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:17.3606628Z     >>> # from a github repo
2025-08-14T21:17:17.3606900Z     >>> repo = "pytorch/vision"
2025-08-14T21:17:17.3607189Z     >>> model = torch.hub.load(
2025-08-14T21:17:17.3607563Z     ...     repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1"
2025-08-14T21:17:17.3607936Z     ... )
2025-08-14T21:17:17.3608164Z     >>> # from a local directory
2025-08-14T21:17:17.3608486Z     >>> path = "/some/local/path/pytorch/vision"
2025-08-14T21:17:17.3608811Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:17.3609414Z     >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT")
2025-08-14T21:17:17.3609792Z 
2025-08-14T21:17:17.3610045Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3610524Z 
2025-08-14T21:17:17.3611012Z msg = Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=657.
2025-08-14T21:17:17.3611841Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3612220Z 
2025-08-14T21:17:17.3612394Z Load a model from a local directory with a ``hubconf.py``.
2025-08-14T21:17:17.3612690Z 
2025-08-14T21:17:17.3612774Z Args:
2025-08-14T21:17:17.3613084Z     hubconf_dir (str): path to a local directory that contains a
2025-08-14T21:17:17.3613494Z         ``hubconf.py``.
2025-08-14T21:17:17.3613845Z     model (str): name of an entrypoint defined in the directory's
2025-08-14T21:17:17.3614226Z         ``hubconf.py``.
2025-08-14T21:17:17.3614591Z     *args (optional): the corresponding args for callable ``model``.
2025-08-14T21:17:17.3615124Z     **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-08-14T21:17:17.3615455Z 
2025-08-14T21:17:17.3615541Z Returns:
2025-08-14T21:17:17.3615832Z     a single model with corresponding pretrained weights.
2025-08-14T21:17:17.3616108Z 
2025-08-14T21:17:17.3616202Z Example:
2025-08-14T21:17:17.3616445Z     >>> # xdoctest: +SKIP("stub local path")
2025-08-14T21:17:17.3616787Z     >>> path = "/some/local/path/pytorch/vision"
2025-08-14T21:17:17.3617130Z     >>> model = _load_local(
2025-08-14T21:17:17.3617400Z     ...     path,
2025-08-14T21:17:17.3617624Z     ...     "resnet50",
2025-08-14T21:17:17.3617927Z     ...     weights="ResNet50_Weights.IMAGENET1K_V1",
2025-08-14T21:17:17.3618266Z     ... )
2025-08-14T21:17:17.3618384Z 
2025-08-14T21:17:17.3618633Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3619014Z 
2025-08-14T21:17:17.3619496Z msg = Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=696.
2025-08-14T21:17:17.3620352Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3620880Z Download object at the given URL to a local path.
2025-08-14T21:17:17.3621133Z 
2025-08-14T21:17:17.3621216Z     Args:
2025-08-14T21:17:17.3621459Z         url (str): URL of the object to download
2025-08-14T21:17:17.3621926Z         dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file``
2025-08-14T21:17:17.3622681Z         hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``.
2025-08-14T21:17:17.3623237Z             Default: None
2025-08-14T21:17:17.3623658Z         progress (bool, optional): whether or not to display a progress bar to stderr
2025-08-14T21:17:17.3624136Z             Default: True
2025-08-14T21:17:17.3624299Z 
2025-08-14T21:17:17.3624387Z     Example:
2025-08-14T21:17:17.3624657Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:17.3625026Z         >>> # xdoctest: +REQUIRES(POSIX)
2025-08-14T21:17:17.3625361Z         >>> torch.hub.download_url_to_file(
2025-08-14T21:17:17.3625823Z         ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth",
2025-08-14T21:17:17.3626270Z         ...     "/tmp/temporary_file",
2025-08-14T21:17:17.3626554Z         ... )
2025-08-14T21:17:17.3626693Z 
2025-08-14T21:17:17.3626771Z     
2025-08-14T21:17:17.3627136Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3627501Z 
2025-08-14T21:17:17.3628008Z msg = Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=821.
2025-08-14T21:17:17.3628867Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3629402Z Loads the Torch serialized object at the given URL.
2025-08-14T21:17:17.3629674Z 
2025-08-14T21:17:17.3629852Z     If downloaded file is a zip file, it will be automatically
2025-08-14T21:17:17.3630238Z     decompressed.
2025-08-14T21:17:17.3630433Z 
2025-08-14T21:17:17.3630647Z     If the object is already present in `model_dir`, it's deserialized and
2025-08-14T21:17:17.3631069Z     returned.
2025-08-14T21:17:17.3631485Z     The default value of ``model_dir`` is ``<hub_dir>/checkpoints`` where
2025-08-14T21:17:17.3632006Z     ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`.
2025-08-14T21:17:17.3632329Z 
2025-08-14T21:17:17.3632414Z     Args:
2025-08-14T21:17:17.3632670Z         url (str): URL of the object to download
2025-08-14T21:17:17.3633115Z         model_dir (str, optional): directory in which to save the object
2025-08-14T21:17:17.3633767Z         map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load)
2025-08-14T21:17:17.3634492Z         progress (bool, optional): whether or not to display a progress bar to stderr.
2025-08-14T21:17:17.3634962Z             Default: True
2025-08-14T21:17:17.3635441Z         check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention
2025-08-14T21:17:17.3636104Z             ``filename-<sha256>.ext`` where ``<sha256>`` is the first eight or more
2025-08-14T21:17:17.3636667Z             digits of the SHA256 hash of the contents of the file. The hash is used to
2025-08-14T21:17:17.3637211Z             ensure unique names and to verify the contents of the file.
2025-08-14T21:17:17.3637605Z             Default: False
2025-08-14T21:17:17.3638113Z         file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set.
2025-08-14T21:17:17.3638887Z         weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects.
2025-08-14T21:17:17.3639574Z             Recommended for untrusted sources. See :func:`~torch.load` for more details.
2025-08-14T21:17:17.3639961Z 
2025-08-14T21:17:17.3640045Z     Example:
2025-08-14T21:17:17.3640313Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:17.3640715Z         >>> state_dict = torch.hub.load_state_dict_from_url(
2025-08-14T21:17:17.3641182Z         ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth"
2025-08-14T21:17:17.3641596Z         ... )
2025-08-14T21:17:17.3641722Z 
2025-08-14T21:17:17.3641811Z     
2025-08-14T21:17:17.3642159Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3642534Z 
2025-08-14T21:17:17.3674574Z msg = Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=375.
2025-08-14T21:17:17.3675446Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.3676054Z Registers the function implementation as the fallback for the given key.
2025-08-14T21:17:17.3676409Z 
2025-08-14T21:17:17.3676638Z         This function only works for a library with global namespace ("_").
2025-08-14T21:17:17.3676970Z 
2025-08-14T21:17:17.3677057Z         Args:
2025-08-14T21:17:17.3677477Z             fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel`
2025-08-14T21:17:17.3677992Z                 to register a fallthrough.
2025-08-14T21:17:17.3678530Z             dispatch_key: dispatch key that the input function should be registered for. By default, it uses
2025-08-14T21:17:17.3679145Z                           the dispatch key that the library was created with.
2025-08-14T21:17:17.3679810Z             with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument
2025-08-14T21:17:17.3680633Z                          to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls.
2025-08-14T21:17:17.3681072Z 
2025-08-14T21:17:17.3681180Z         Example::
2025-08-14T21:17:17.3681332Z 
2025-08-14T21:17:17.3681443Z             >>> my_lib = Library("_", "IMPL")
2025-08-14T21:17:17.3681802Z             >>> def fallback_kernel(op, *args, **kwargs):
2025-08-14T21:17:17.3682181Z             >>>     # Handle all autocast ops generically
2025-08-14T21:17:17.3682566Z             >>>     # ...
2025-08-14T21:17:17.3682872Z             >>> my_lib.fallback(fallback_kernel, "Autocast")
2025-08-14T21:17:17.3683222Z         
2025-08-14T21:17:17.3683964Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('<source_block>', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7))
2025-08-14T21:17:17.3684716Z 
2025-08-14T21:17:17.3684851Z my_lib.fallback(fallback_kernel, "Autocast")
2025-08-14T21:17:17.3685179Z ^
2025-08-14T21:17:17.3753794Z msg = Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=948.
2025-08-14T21:17:17.3754900Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.3755503Z Register a FakeTensor implementation ("fake impl") for this operator.
2025-08-14T21:17:17.3755861Z 
2025-08-14T21:17:17.3756038Z     Also sometimes known as a "meta kernel", "abstract impl".
2025-08-14T21:17:17.3756347Z 
2025-08-14T21:17:17.3756602Z     An "FakeTensor implementation" specifies the behavior of this operator on
2025-08-14T21:17:17.3757177Z     Tensors that carry no data ("FakeTensor"). Given some input Tensors with
2025-08-14T21:17:17.3757756Z     certain properties (sizes/strides/storage_offset/device), it specifies
2025-08-14T21:17:17.3758253Z     what the properties of the output Tensors are.
2025-08-14T21:17:17.3758507Z 
2025-08-14T21:17:17.3758757Z     The FakeTensor implementation has the same signature as the operator.
2025-08-14T21:17:17.3759305Z     It is run for both FakeTensors and meta tensors. To write a FakeTensor
2025-08-14T21:17:17.3759849Z     implementation, assume that all Tensor inputs to the operator are
2025-08-14T21:17:17.3760398Z     regular CPU/CUDA/Meta tensors, but they do not have storage, and
2025-08-14T21:17:17.3760914Z     you are trying to return regular CPU/CUDA/Meta tensor(s) as output.
2025-08-14T21:17:17.3761476Z     The FakeTensor implementation must consist of only PyTorch operations
2025-08-14T21:17:17.3762023Z     (and may not directly access the storage or data of any input or
2025-08-14T21:17:17.3762437Z     intermediate Tensors).
2025-08-14T21:17:17.3762613Z 
2025-08-14T21:17:17.3762763Z     This API may be used as a decorator (see examples).
2025-08-14T21:17:17.3763054Z 
2025-08-14T21:17:17.3763265Z     For a detailed guide on custom ops, please see
2025-08-14T21:17:17.3764148Z     https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html
2025-08-14T21:17:17.3764534Z 
2025-08-14T21:17:17.3764657Z     Args:
2025-08-14T21:17:17.3765012Z         op_name: Operator name (along with the overload) or OpOverload object.
2025-08-14T21:17:17.3765509Z         func: Fake tensor implementation.
2025-08-14T21:17:17.3765942Z         lib (Optional[Library]): Library to register the fake tensor to.
2025-08-14T21:17:17.3766447Z         allow_override: Flag controlling if we want to override an
2025-08-14T21:17:17.3766929Z                         existing registered fake impl. This is by default off,
2025-08-14T21:17:17.3767384Z                         and will error you're trying to register a fake impl to
2025-08-14T21:17:17.3767850Z                         an operator that already has a fake impl. This also only
2025-08-14T21:17:17.3768306Z                         applies if the custom operator was not created via
2025-08-14T21:17:17.3768766Z                         torch.library.custom_op, as overriding and existing fake
2025-08-14T21:17:17.3769190Z                         impl is already allowed.
2025-08-14T21:17:17.3769411Z 
2025-08-14T21:17:17.3769510Z     Examples:
2025-08-14T21:17:17.3769739Z         >>> import torch
2025-08-14T21:17:17.3769996Z         >>> import numpy as np
2025-08-14T21:17:17.3770290Z         >>> from torch import Tensor
2025-08-14T21:17:17.3770580Z         >>>
2025-08-14T21:17:17.3770884Z         >>> # Example 1: an operator without data-dependent output shape
2025-08-14T21:17:17.3771507Z         >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=())
2025-08-14T21:17:17.3772059Z         >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-08-14T21:17:17.3772566Z         >>>     raise NotImplementedError("Implementation goes here")
2025-08-14T21:17:17.3772946Z         >>>
2025-08-14T21:17:17.3773241Z         >>> @torch.library.register_fake("mylib::custom_linear")
2025-08-14T21:17:17.3773624Z         >>> def _(x, weight, bias):
2025-08-14T21:17:17.3773923Z         >>>     assert x.dim() == 2
2025-08-14T21:17:17.3774230Z         >>>     assert weight.dim() == 2
2025-08-14T21:17:17.3774558Z         >>>     assert bias.dim() == 1
2025-08-14T21:17:17.3774884Z         >>>     assert x.shape[1] == weight.shape[1]
2025-08-14T21:17:17.3775254Z         >>>     assert weight.shape[0] == bias.shape[0]
2025-08-14T21:17:17.3775618Z         >>>     assert x.device == weight.device
2025-08-14T21:17:17.3775924Z         >>>
2025-08-14T21:17:17.3776161Z         >>>     return (x @ weight.t()) + bias
2025-08-14T21:17:17.3776473Z         >>>
2025-08-14T21:17:17.3776763Z         >>> with torch._subclasses.fake_tensor.FakeTensorMode():
2025-08-14T21:17:17.3777157Z         >>>     x = torch.randn(2, 3)
2025-08-14T21:17:17.3777465Z         >>>     w = torch.randn(3, 3)
2025-08-14T21:17:17.3777770Z         >>>     b = torch.randn(3)
2025-08-14T21:17:17.3778093Z         >>>     y = torch.ops.mylib.custom_linear(x, w, b)
2025-08-14T21:17:17.3778427Z         >>>
2025-08-14T21:17:17.3778656Z         >>> assert y.shape == (2, 3)
2025-08-14T21:17:17.3778932Z         >>>
2025-08-14T21:17:17.3779228Z         >>> # Example 2: an operator with data-dependent output shape
2025-08-14T21:17:17.3779736Z         >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=())
2025-08-14T21:17:17.3780188Z         >>> def custom_nonzero(x: Tensor) -> Tensor:
2025-08-14T21:17:17.3780540Z         >>>     x_np = x.numpy(force=True)
2025-08-14T21:17:17.3780891Z         >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-08-14T21:17:17.3781273Z         >>>     return torch.tensor(res, device=x.device)
2025-08-14T21:17:17.3781591Z         >>>
2025-08-14T21:17:17.3781889Z         >>> @torch.library.register_fake("mylib::custom_nonzero")
2025-08-14T21:17:17.3782262Z         >>> def _(x):
2025-08-14T21:17:17.3782550Z         >>> # Number of nonzero-elements is data-dependent.
2025-08-14T21:17:17.3782968Z         >>> # Since we cannot peek at the data in an fake impl,
2025-08-14T21:17:17.3783470Z         >>> # we use the ctx object to construct a new symint that
2025-08-14T21:17:17.3783860Z         >>> # represents the data-dependent size.
2025-08-14T21:17:17.3784220Z         >>>     ctx = torch.library.get_ctx()
2025-08-14T21:17:17.3784563Z         >>>     nnz = ctx.new_dynamic_size()
2025-08-14T21:17:17.3784889Z         >>>     shape = [nnz, x.dim()]
2025-08-14T21:17:17.3785234Z         >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-08-14T21:17:17.3785596Z         >>>     return result
2025-08-14T21:17:17.3785868Z         >>>
2025-08-14T21:17:17.3786159Z         >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-08-14T21:17:17.3786544Z         >>>
2025-08-14T21:17:17.3786783Z         >>> x = torch.tensor([0, 1, 2, 3, 4, 0])
2025-08-14T21:17:17.3787240Z         >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x)
2025-08-14T21:17:17.3787721Z         >>> trace.print_readable()
2025-08-14T21:17:17.3788015Z         >>>
2025-08-14T21:17:17.3788350Z         >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x))
2025-08-14T21:17:17.3788705Z 
2025-08-14T21:17:17.3788785Z     
2025-08-14T21:17:17.3789429Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('<source_block>', 38, 1, '_._ = None\n', 38, 2))
2025-08-14T21:17:17.3790064Z 
2025-08-14T21:17:17.3790157Z _._ = None
2025-08-14T21:17:17.3790350Z ^
2025-08-14T21:17:17.3790967Z msg = Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1083.
2025-08-14T21:17:17.3791995Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3792509Z Register a backward formula for this custom op.
2025-08-14T21:17:17.3792774Z 
2025-08-14T21:17:17.3792980Z     In order for an operator to work with autograd, you need to register
2025-08-14T21:17:17.3793405Z     a backward formula:
2025-08-14T21:17:17.3793783Z     1. You must tell us how to compute gradients during the backward pass
2025-08-14T21:17:17.3794216Z     by providing us a "backward" function.
2025-08-14T21:17:17.3794657Z     2. If you need any values from the forward to compute gradients, you can
2025-08-14T21:17:17.3795133Z     use `setup_context` to save values for backward.
2025-08-14T21:17:17.3795383Z 
2025-08-14T21:17:17.3795618Z     ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``:
2025-08-14T21:17:17.3796147Z     - ``grads`` is one or more gradients. The number of gradients matches
2025-08-14T21:17:17.3796588Z     the number of outputs of the operator.
2025-08-14T21:17:17.3797027Z     The ``ctx`` object is `the same ctx object <context_method_mixins>`_ used by
2025-08-14T21:17:17.3797596Z     :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the
2025-08-14T21:17:17.3798115Z     same as :meth:`torch.autograd.Function.backward`.
2025-08-14T21:17:17.3798391Z 
2025-08-14T21:17:17.3798600Z     ``setup_context(ctx, inputs, output)`` runs during the forward pass.
2025-08-14T21:17:17.3799161Z     Please save quantities needed for backward onto the ``ctx`` object via
2025-08-14T21:17:17.3799727Z     either :meth:`torch.autograd.function.FunctionCtx.save_for_backward`
2025-08-14T21:17:17.3800278Z     or assigning them as attributes of ``ctx``. If your custom op has
2025-08-14T21:17:17.3800808Z     kwarg-only arguments, we expect the signature of ``setup_context``
2025-08-14T21:17:17.3801336Z     to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``.
2025-08-14T21:17:17.3801658Z 
2025-08-14T21:17:17.3801873Z     Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is,
2025-08-14T21:17:17.3802439Z     they may not directly access :meth:`torch.Tensor.data_ptr` and they must
2025-08-14T21:17:17.3803007Z     not depend on or mutate global state. If you need a non-traceable backward,
2025-08-14T21:17:17.3803586Z     you can make it a separate custom_op that you call inside ``backward_fn``.
2025-08-14T21:17:17.3803941Z 
2025-08-14T21:17:17.3804217Z     If you need different autograd behavior on different devices, then we
2025-08-14T21:17:17.3804795Z     recommend creating two different custom operators, one for each device
2025-08-14T21:17:17.3805364Z     that needs different behavior, and switching between them at runtime.
2025-08-14T21:17:17.3805716Z 
2025-08-14T21:17:17.3805804Z     Examples:
2025-08-14T21:17:17.3806039Z         >>> import torch
2025-08-14T21:17:17.3806303Z         >>> import numpy as np
2025-08-14T21:17:17.3806609Z         >>> from torch import Tensor
2025-08-14T21:17:17.3806910Z         >>>
2025-08-14T21:17:17.3807349Z         >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=())
2025-08-14T21:17:17.3807796Z         >>> def numpy_sin(x: Tensor) -> Tensor:
2025-08-14T21:17:17.3808136Z         >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:17.3808453Z         >>>     y_np = np.sin(x_np)
2025-08-14T21:17:17.3808800Z         >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-08-14T21:17:17.3809323Z         >>>
2025-08-14T21:17:17.3809610Z         >>> def setup_context(ctx, inputs, output) -> Tensor:
2025-08-14T21:17:17.3809960Z         >>>     x, = inputs
2025-08-14T21:17:17.3810245Z         >>>     ctx.save_for_backward(x)
2025-08-14T21:17:17.3810549Z         >>>
2025-08-14T21:17:17.3810761Z         >>> def backward(ctx, grad):
2025-08-14T21:17:17.3811067Z         >>>     x, = ctx.saved_tensors
2025-08-14T21:17:17.3811381Z         >>>     return grad * x.cos()
2025-08-14T21:17:17.3811655Z         >>>
2025-08-14T21:17:17.3811997Z         >>> torch.library.register_autograd(
2025-08-14T21:17:17.3812416Z         ...     "mylib::numpy_sin", backward, setup_context=setup_context
2025-08-14T21:17:17.3812798Z         ... )
2025-08-14T21:17:17.3812997Z         >>>
2025-08-14T21:17:17.3813242Z         >>> x = torch.randn(3, requires_grad=True)
2025-08-14T21:17:17.3813579Z         >>> y = numpy_sin(x)
2025-08-14T21:17:17.3813919Z         >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-08-14T21:17:17.3814340Z         >>> assert torch.allclose(grad_x, x.cos())
2025-08-14T21:17:17.3814667Z         >>>
2025-08-14T21:17:17.3814897Z         >>> # Example with a keyword-only arg
2025-08-14T21:17:17.3815331Z         >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-08-14T21:17:17.3815803Z         >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor:
2025-08-14T21:17:17.3816265Z         >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:17.3816564Z         >>>     y_np = x_np * val
2025-08-14T21:17:17.3816925Z         >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-08-14T21:17:17.3817506Z         >>>
2025-08-14T21:17:17.3818107Z         >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor:
2025-08-14T21:17:17.3818587Z         >>>     ctx.val = keyword_only_inputs["val"]
2025-08-14T21:17:17.3818912Z         >>>
2025-08-14T21:17:17.3819128Z         >>> def backward(ctx, grad):
2025-08-14T21:17:17.3819439Z         >>>     return grad * ctx.val
2025-08-14T21:17:17.3819733Z         >>>
2025-08-14T21:17:17.3819968Z         >>> torch.library.register_autograd(
2025-08-14T21:17:17.3820383Z         ...     "mylib::numpy_mul", backward, setup_context=setup_context
2025-08-14T21:17:17.3820769Z         ... )
2025-08-14T21:17:17.3820982Z         >>>
2025-08-14T21:17:17.3821215Z         >>> x = torch.randn(3, requires_grad=True)
2025-08-14T21:17:17.3821561Z         >>> y = numpy_mul(x, val=3.14)
2025-08-14T21:17:17.3821941Z         >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-08-14T21:17:17.3822392Z         >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14))
2025-08-14T21:17:17.3822692Z 
2025-08-14T21:17:17.3822772Z     
2025-08-14T21:17:17.3823139Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3823505Z 
2025-08-14T21:17:17.3824011Z msg = Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482.
2025-08-14T21:17:17.3824939Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.3825522Z Returns the computed kernel for a given operator and dispatch key.
2025-08-14T21:17:17.3825859Z 
2025-08-14T21:17:17.3826083Z     This function retrieves the kernel that would be executed for a given
2025-08-14T21:17:17.3826663Z     operator and dispatch key combination. The returned SafeKernelFunction
2025-08-14T21:17:17.3827197Z     can be used to call the kernel in a boxed fashion. The intended use
2025-08-14T21:17:17.3827729Z     case for this function is to retrieve the original kernel for a given
2025-08-14T21:17:17.3828280Z     dispatch key and then register another kernel to the same dispatch key
2025-08-14T21:17:17.3828902Z     that calls into the original kernel for certain cases.
2025-08-14T21:17:17.3829297Z 
2025-08-14T21:17:17.3829435Z     Args:
2025-08-14T21:17:17.3829947Z         op: Operator name (along with the overload) or OpOverload object
2025-08-14T21:17:17.3830893Z             Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef.
2025-08-14T21:17:17.3831823Z         dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for.
2025-08-14T21:17:17.3832396Z             Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value.
2025-08-14T21:17:17.3832716Z 
2025-08-14T21:17:17.3832801Z     Returns:
2025-08-14T21:17:17.3833174Z         torch._C._SafeKernelFunction: A safe kernel function that can be used to
2025-08-14T21:17:17.3833712Z             call the kernel.
2025-08-14T21:17:17.3833902Z 
2025-08-14T21:17:17.3833985Z     Raises:
2025-08-14T21:17:17.3834259Z         RuntimeError: If the operator does not exist.
2025-08-14T21:17:17.3834509Z 
2025-08-14T21:17:17.3834595Z     Example:
2025-08-14T21:17:17.3834845Z         >>> # Get the CPU kernel for torch.add
2025-08-14T21:17:17.3835279Z         >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU")
2025-08-14T21:17:17.3835664Z         >>>
2025-08-14T21:17:17.3835916Z         >>> # You can also use DispatchKey enum
2025-08-14T21:17:17.3836415Z         >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU)
2025-08-14T21:17:17.3836879Z         >>>
2025-08-14T21:17:17.3837102Z         >>> # Or use an OpOverload directly
2025-08-14T21:17:17.3837554Z         >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU")
2025-08-14T21:17:17.3837983Z         >>>
2025-08-14T21:17:17.3838305Z         >>> # Example: Using get_kernel in a custom op with conditional dispatch
2025-08-14T21:17:17.3838764Z         >>> # Get the original kernel for torch.sin
2025-08-14T21:17:17.3839218Z         >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU")
2025-08-14T21:17:17.3839633Z         >>>
2025-08-14T21:17:17.3839970Z         >>> # If input has negative values, use original sin, otherwise return zeros
2025-08-14T21:17:17.3840457Z         >>> def conditional_sin_impl(dispatch_keys, x):
2025-08-14T21:17:17.3840810Z         >>>     if (x < 0).any():
2025-08-14T21:17:17.3841177Z         >>>         return original_sin_kernel.call_boxed(dispatch_keys, x)
2025-08-14T21:17:17.3841569Z         >>>     else:
2025-08-14T21:17:17.3841841Z         >>>         return torch.zeros_like(x)
2025-08-14T21:17:17.3842141Z         >>>
2025-08-14T21:17:17.3842405Z         >>> lib = torch.library.Library("aten", "IMPL")
2025-08-14T21:17:17.3842919Z         >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet
2025-08-14T21:17:17.3843494Z         >>> which needs to be the first argument to ``kernel.call_boxed``
2025-08-14T21:17:17.3843983Z         >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True)
2025-08-14T21:17:17.3844386Z         >>>
2025-08-14T21:17:17.3844630Z         >>> # Test the conditional behavior
2025-08-14T21:17:17.3844967Z         >>> x_positive = torch.tensor([1.0, 2.0])
2025-08-14T21:17:17.3845327Z         >>> x_mixed = torch.tensor([-1.0, 2.0])
2025-08-14T21:17:17.3845667Z         >>> torch.sin(x_positive)
2025-08-14T21:17:17.3846008Z         tensor([0., 0.])
2025-08-14T21:17:17.3846280Z         >>> torch.sin(x_mixed)
2025-08-14T21:17:17.3846568Z         tensor([-0.8415, 0.9093])
2025-08-14T21:17:17.3846832Z     
2025-08-14T21:17:17.3847435Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12))
2025-08-14T21:17:17.3848039Z 
2025-08-14T21:17:17.3848219Z which needs to be the first argument to ``kernel.call_boxed``
2025-08-14T21:17:17.3848609Z       ^
2025-08-14T21:17:17.3849223Z msg = Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1571.
2025-08-14T21:17:17.3850043Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.3850638Z Given an operator and some sample arguments, tests if the operator is
2025-08-14T21:17:17.3851073Z     registered correctly.
2025-08-14T21:17:17.3851243Z 
2025-08-14T21:17:17.3851466Z     That is, when you use the torch.library/TORCH_LIBRARY APIs to create a
2025-08-14T21:17:17.3852026Z     custom op, you specified metadata (e.g. mutability info) about the custom op
2025-08-14T21:17:17.3852608Z     and these APIs require that the functions you pass them satisfy certain
2025-08-14T21:17:17.3853181Z     properties (e.g. no data pointer access in the fake/meta/abstract kernel)
2025-08-14T21:17:17.3853669Z     ``opcheck`` tests these metadata and properties.
2025-08-14T21:17:17.3853933Z 
2025-08-14T21:17:17.3854100Z     Concretely, we test the following:
2025-08-14T21:17:17.3854327Z 
2025-08-14T21:17:17.3854504Z     - test_schema: If the schema matches the implementation of
2025-08-14T21:17:17.3855024Z       the operator. For example: if the schema specifies a Tensor is mutated,
2025-08-14T21:17:17.3855563Z       then we check the implementation mutates the Tensor. If the schema
2025-08-14T21:17:17.3856083Z       specifies that we return a new Tensor, then we check that the
2025-08-14T21:17:17.3856619Z       implementation returns a new Tensor (instead of an existing one or
2025-08-14T21:17:17.3857052Z       a view of an existing one).
2025-08-14T21:17:17.3857457Z     - test_autograd_registration: If the operator supports training
2025-08-14T21:17:17.3857970Z       (autograd): we check that its autograd formula is registered via
2025-08-14T21:17:17.3858493Z       torch.library.register_autograd or a manual registration to one
2025-08-14T21:17:17.3859014Z       or more DispatchKey::Autograd keys. Any other DispatchKey-based
2025-08-14T21:17:17.3859474Z       registrations may lead to undefined behavior.
2025-08-14T21:17:17.3859908Z     - test_faketensor: If the operator has a FakeTensor kernel
2025-08-14T21:17:17.3860364Z       (and if it is correct). The FakeTensor kernel is necessary (
2025-08-14T21:17:17.3860877Z       but not sufficient) for the operator to work with PyTorch compilation
2025-08-14T21:17:17.3861429Z       APIs (torch.compile/export/FX). We check that a FakeTensor kernel
2025-08-14T21:17:17.3861961Z       (also sometimes known as a meta kernel) was registered for the
2025-08-14T21:17:17.3862455Z       operator and that it is correct. This test takes the result of
2025-08-14T21:17:17.3862960Z       running the operator on real tensors and the result of running
2025-08-14T21:17:17.3863468Z       the operator on FakeTensors and checks that they have the same
2025-08-14T21:17:17.3863919Z       Tensor metadata (sizes/strides/dtype/device/etc).
2025-08-14T21:17:17.3864382Z     - test_aot_dispatch_dynamic: If the operator has correct behavior
2025-08-14T21:17:17.3864883Z       with PyTorch compilation APIs (torch.compile/export/FX).
2025-08-14T21:17:17.3865390Z       This checks that the outputs (and gradients, if applicable) are the
2025-08-14T21:17:17.3865857Z       same under eager-mode PyTorch and torch.compile.
2025-08-14T21:17:17.3866313Z       This test is a superset of ``test_faketensor`` and is an e2e test;
2025-08-14T21:17:17.3866785Z       other things it tests are that the operator supports
2025-08-14T21:17:17.3867335Z       functionalization and that the backward pass (if it exists) also
2025-08-14T21:17:17.3867806Z       supports FakeTensor and functionalization.
2025-08-14T21:17:17.3868049Z 
2025-08-14T21:17:17.3868259Z     For best results, please call ``opcheck`` multiple times with a
2025-08-14T21:17:17.3868756Z     representative set of inputs. If your operator supports
2025-08-14T21:17:17.3869269Z     autograd, please use ``opcheck`` with inputs with ``requires_grad = True``;
2025-08-14T21:17:17.3869858Z     if your operator supports multiple devices (e.g. CPU and CUDA), please
2025-08-14T21:17:17.3870357Z     use ``opcheck`` with inputs on all supported devices.
2025-08-14T21:17:17.3870619Z 
2025-08-14T21:17:17.3870703Z     Args:
2025-08-14T21:17:17.3871004Z         op: The operator. Must either be a function decorated with
2025-08-14T21:17:17.3871591Z             :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket
2025-08-14T21:17:17.3872150Z             found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo)
2025-08-14T21:17:17.3872581Z         args: The args to the operator
2025-08-14T21:17:17.3872914Z         kwargs: The kwargs to the operator
2025-08-14T21:17:17.3873321Z         test_utils: Tests that we should run. Default: all of them.
2025-08-14T21:17:17.3873743Z             Example: ("test_schema", "test_faketensor")
2025-08-14T21:17:17.3874183Z         raise_exception: If we should raise an exception on the first
2025-08-14T21:17:17.3874720Z             error. If False, we will return a dict with information
2025-08-14T21:17:17.3875105Z             on if each test passed or not.
2025-08-14T21:17:17.3875571Z         rtol (Optional[float]): Relative tolerance for floating point comparisons.
2025-08-14T21:17:17.3876073Z             If specified ``atol`` must also be specified.
2025-08-14T21:17:17.3876517Z             If omitted, default values based on the ``dtype`` are selected
2025-08-14T21:17:17.3876981Z             (see the table in :func:`torch.testing.assert_close`).
2025-08-14T21:17:17.3877505Z         atol (Optional[float]): Absolute tolerance for floating point comparisons.
2025-08-14T21:17:17.3878006Z             If specified ``rtol`` must also be specified.
2025-08-14T21:17:17.3878439Z             If omitted, default values based on the ``dtype`` are selected
2025-08-14T21:17:17.3878915Z             (see the table in :func:`torch.testing.assert_close`).
2025-08-14T21:17:17.3879205Z 
2025-08-14T21:17:17.3879300Z     .. warning::
2025-08-14T21:17:17.3879439Z 
2025-08-14T21:17:17.3879665Z         opcheck and :func:`torch.autograd.gradcheck` test different things;
2025-08-14T21:17:17.3880199Z         opcheck tests if your usage of torch.library APIs is correct while
2025-08-14T21:17:17.3880740Z         :func:`torch.autograd.gradcheck` tests if your autograd formula is
2025-08-14T21:17:17.3881290Z         mathematically correct. Use both to test custom ops that support
2025-08-14T21:17:17.3881733Z         gradient computation.
2025-08-14T21:17:17.3881916Z 
2025-08-14T21:17:17.3882003Z     Example:
2025-08-14T21:17:17.3882143Z 
2025-08-14T21:17:17.3882278Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:17.3882736Z         >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-08-14T21:17:17.3883187Z         >>> def numpy_mul(x: Tensor, y: float) -> Tensor:
2025-08-14T21:17:17.3883559Z         >>>     x_np = x.numpy(force=True)
2025-08-14T21:17:17.3883881Z         >>>     z_np = x_np * y
2025-08-14T21:17:17.3884209Z         >>>     return torch.from_numpy(z_np).to(x.device)
2025-08-14T21:17:17.3884535Z         >>>
2025-08-14T21:17:17.3884775Z         >>> @numpy_mul.register_fake
2025-08-14T21:17:17.3885082Z         >>> def _(x, y):
2025-08-14T21:17:17.3885347Z         >>>     return torch.empty_like(x)
2025-08-14T21:17:17.3885657Z         >>>
2025-08-14T21:17:17.3885919Z         >>> def setup_context(ctx, inputs, output):
2025-08-14T21:17:17.3886247Z         >>>     y, = inputs
2025-08-14T21:17:17.3886516Z         >>>     ctx.y = y
2025-08-14T21:17:17.3886835Z         >>>
2025-08-14T21:17:17.3887055Z         >>> def backward(ctx, grad):
2025-08-14T21:17:17.3887374Z         >>>     return grad * ctx.y, None
2025-08-14T21:17:17.3887682Z         >>>
2025-08-14T21:17:17.3888018Z         >>> numpy_mul.register_autograd(backward, setup_context=setup_context)
2025-08-14T21:17:17.3888448Z         >>>
2025-08-14T21:17:17.3888680Z         >>> sample_inputs = [
2025-08-14T21:17:17.3888960Z         >>>     (torch.randn(3), 3.14),
2025-08-14T21:17:17.3889309Z         >>>     (torch.randn(2, 3, device='cuda'), 2.718),
2025-08-14T21:17:17.3889701Z         >>>     (torch.randn(1, 10, requires_grad=True), 1.234),
2025-08-14T21:17:17.3890158Z         >>>     (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18),
2025-08-14T21:17:17.3890537Z         >>> ]
2025-08-14T21:17:17.3890751Z         >>>
2025-08-14T21:17:17.3890979Z         >>> for args in sample_inputs:
2025-08-14T21:17:17.3891316Z         >>>     torch.library.opcheck(numpy_mul, args)
2025-08-14T21:17:17.3891570Z 
2025-08-14T21:17:17.3891648Z     
2025-08-14T21:17:17.3892012Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.3892380Z 
2025-08-14T21:17:17.4256377Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285.
2025-08-14T21:17:17.4257570Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.4258578Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args)
2025-08-14T21:17:17.4259033Z 
2025-08-14T21:17:17.4259212Z     Loads an object saved with :func:`torch.save` from a file.
2025-08-14T21:17:17.4259516Z 
2025-08-14T21:17:17.4259748Z     :func:`torch.load` uses Python's unpickling facilities but treats storages,
2025-08-14T21:17:17.4260335Z     which underlie tensors, specially. They are first deserialized on the
2025-08-14T21:17:17.4260894Z     CPU and are then moved to the device they were saved from. If this fails
2025-08-14T21:17:17.4261470Z     (e.g. because the run time system doesn't have certain devices), an exception
2025-08-14T21:17:17.4262060Z     is raised. However, storages can be dynamically remapped to an alternative
2025-08-14T21:17:17.4262571Z     set of devices using the :attr:`map_location` argument.
2025-08-14T21:17:17.4262861Z 
2025-08-14T21:17:17.4263099Z     If :attr:`map_location` is a callable, it will be called once for each serialized
2025-08-14T21:17:17.4263695Z     storage with two arguments: storage and location. The storage argument
2025-08-14T21:17:17.4264263Z     will be the initial deserialization of the storage, residing on the CPU.
2025-08-14T21:17:17.4264822Z     Each serialized storage has a location tag associated with it which
2025-08-14T21:17:17.4265367Z     identifies the device it was saved from, and this tag is the second
2025-08-14T21:17:17.4265952Z     argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'``
2025-08-14T21:17:17.4266555Z     for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors.
2025-08-14T21:17:17.4267088Z     :attr:`map_location` should return either ``None`` or a storage. If
2025-08-14T21:17:17.4267663Z     :attr:`map_location` returns a storage, it will be used as the final deserialized
2025-08-14T21:17:17.4268285Z     object, already moved to the right device. Otherwise, :func:`torch.load` will
2025-08-14T21:17:17.4268887Z     fall back to the default behavior, as if :attr:`map_location` wasn't specified.
2025-08-14T21:17:17.4269265Z 
2025-08-14T21:17:17.4269498Z     If :attr:`map_location` is a :class:`torch.device` object or a string containing
2025-08-14T21:17:17.4270088Z     a device tag, it indicates the location where all tensors should be loaded.
2025-08-14T21:17:17.4270435Z 
2025-08-14T21:17:17.4270703Z     Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags
2025-08-14T21:17:17.4271508Z     appearing in the file (keys), to ones that specify where to put the
2025-08-14T21:17:17.4271947Z     storages (values).
2025-08-14T21:17:17.4272105Z 
2025-08-14T21:17:17.4272340Z     User extensions can register their own location tags and tagging and
2025-08-14T21:17:17.4272956Z     deserialization methods using :func:`torch.serialization.register_package`.
2025-08-14T21:17:17.4273337Z 
2025-08-14T21:17:17.4273581Z     See :ref:`layout-control` for more advanced tools to manipulate a checkpoint.
2025-08-14T21:17:17.4273959Z 
2025-08-14T21:17:17.4274044Z     Args:
2025-08-14T21:17:17.4274487Z         f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`),
2025-08-14T21:17:17.4275087Z             or a string or os.PathLike object containing a file name
2025-08-14T21:17:17.4275699Z         map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage
2025-08-14T21:17:17.4276233Z             locations
2025-08-14T21:17:17.4276619Z         pickle_module: module used for unpickling metadata and objects (has to
2025-08-14T21:17:17.4277125Z             match the :attr:`pickle_module` used to serialize file)
2025-08-14T21:17:17.4277624Z         weights_only: Indicates whether unpickler should be restricted to
2025-08-14T21:17:17.4278121Z             loading only tensors, primitive types, dictionaries
2025-08-14T21:17:17.4278606Z             and any types added via :func:`torch.serialization.add_safe_globals`.
2025-08-14T21:17:17.4279080Z             See :ref:`weights-only` for more details.
2025-08-14T21:17:17.4279735Z         mmap: Indicates whether the file should be mapped rather than loading all the storages into memory.
2025-08-14T21:17:17.4280523Z             Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they
2025-08-14T21:17:17.4281308Z             are moved to the location that they were tagged with when saving, or specified by ``map_location``. This
2025-08-14T21:17:17.4282102Z             second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the
2025-08-14T21:17:17.4282876Z             tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages
2025-08-14T21:17:17.4283481Z             will be lazily loaded when their data is accessed.
2025-08-14T21:17:17.4283979Z         pickle_load_args: (Python 3 only) optional keyword arguments passed over to
2025-08-14T21:17:17.4284568Z             :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g.,
2025-08-14T21:17:17.4285018Z             :attr:`errors=...`.
2025-08-14T21:17:17.4285200Z 
2025-08-14T21:17:17.4285332Z     .. warning::
2025-08-14T21:17:17.4285674Z         :func:`torch.load()` unless `weights_only` parameter is set to `True`,
2025-08-14T21:17:17.4286209Z         uses ``pickle`` module implicitly, which is known to be insecure.
2025-08-14T21:17:17.4286808Z         It is possible to construct malicious pickle data which will execute arbitrary code
2025-08-14T21:17:17.4287438Z         during unpickling. Never load data that could have come from an untrusted
2025-08-14T21:17:17.4288091Z         source in an unsafe mode, or that could have been tampered with. **Only load data you trust**.
2025-08-14T21:17:17.4288514Z 
2025-08-14T21:17:17.4288600Z     .. note::
2025-08-14T21:17:17.4288995Z         When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors
2025-08-14T21:17:17.4289620Z         will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')``
2025-08-14T21:17:17.4290271Z         and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint.
2025-08-14T21:17:17.4290659Z 
2025-08-14T21:17:17.4290754Z     .. note::
2025-08-14T21:17:17.4291122Z         By default, we decode byte strings as ``utf-8``.  This is to avoid a common error
2025-08-14T21:17:17.4291714Z         case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...``
2025-08-14T21:17:17.4292334Z         when loading files saved by Python 2 in Python 3.  If this default
2025-08-14T21:17:17.4292924Z         is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how
2025-08-14T21:17:17.4293527Z         these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them
2025-08-14T21:17:17.4294136Z         to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them
2025-08-14T21:17:17.4294733Z         as byte arrays which can be decoded later with ``byte_array.decode(...)``.
2025-08-14T21:17:17.4295084Z 
2025-08-14T21:17:17.4295187Z     Example:
2025-08-14T21:17:17.4295445Z         >>> # xdoctest: +SKIP("undefined filepaths")
2025-08-14T21:17:17.4295838Z         >>> torch.load("tensors.pt", weights_only=True)
2025-08-14T21:17:17.4296211Z         # Load all tensors onto the CPU
2025-08-14T21:17:17.4296511Z         >>> torch.load(
2025-08-14T21:17:17.4296777Z         ...     "tensors.pt",
2025-08-14T21:17:17.4297093Z         ...     map_location=torch.device("cpu"),
2025-08-14T21:17:17.4297433Z         ...     weights_only=True,
2025-08-14T21:17:17.4297728Z         ... )
2025-08-14T21:17:17.4298025Z         # Load all tensors onto the CPU, using a function
2025-08-14T21:17:17.4298373Z         >>> torch.load(
2025-08-14T21:17:17.4298641Z         ...     "tensors.pt",
2025-08-14T21:17:17.4298969Z         ...     map_location=lambda storage, loc: storage,
2025-08-14T21:17:17.4299330Z         ...     weights_only=True,
2025-08-14T21:17:17.4299629Z         ... )
2025-08-14T21:17:17.4299968Z         # Load all tensors onto GPU 1
2025-08-14T21:17:17.4300275Z         >>> torch.load(
2025-08-14T21:17:17.4300520Z         ...     "tensors.pt",
2025-08-14T21:17:17.4300869Z         ...     map_location=lambda storage, loc: storage.cuda(1),
2025-08-14T21:17:17.4301252Z         ...     weights_only=True,
2025-08-14T21:17:17.4301549Z         ... )  # type: ignore[attr-defined]
2025-08-14T21:17:17.4301884Z         # Map tensors from GPU 1 to GPU 0
2025-08-14T21:17:17.4302195Z         >>> torch.load(
2025-08-14T21:17:17.4302444Z         ...     "tensors.pt",
2025-08-14T21:17:17.4302744Z         ...     map_location={"cuda:1": "cuda:0"},
2025-08-14T21:17:17.4303080Z         ...     weights_only=True,
2025-08-14T21:17:17.4303360Z         ... )
2025-08-14T21:17:17.4303598Z         # Load tensor from io.BytesIO object
2025-08-14T21:17:17.4304079Z         # Loading from a buffer setting weights_only=False, warning this can be unsafe
2025-08-14T21:17:17.4304569Z         >>> with open("tensor.pt", "rb") as f:
2025-08-14T21:17:17.4304907Z         ...     buffer = io.BytesIO(f.read())
2025-08-14T21:17:17.4305261Z         >>> torch.load(buffer, weights_only=False)
2025-08-14T21:17:17.4305654Z         # Load a module with 'ascii' encoding for unpickling
2025-08-14T21:17:17.4306193Z         # Loading from a module setting weights_only=False, warning this can be unsafe
2025-08-14T21:17:17.4306760Z         >>> torch.load("module.pt", encoding="ascii", weights_only=False)
2025-08-14T21:17:17.4307155Z     
2025-08-14T21:17:17.4307533Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.4307900Z 
2025-08-14T21:17:17.4837766Z msg = Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1851.
2025-08-14T21:17:17.4838784Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.4839385Z Computes the minimum storage size to hold the given tensor geometry.
2025-08-14T21:17:17.4839754Z 
2025-08-14T21:17:17.4839856Z     Example
2025-08-14T21:17:17.4840054Z     =======
2025-08-14T21:17:17.4840188Z 
2025-08-14T21:17:17.4840416Z     This is the size of a newly allocated tensor's storage, in units of elements
2025-08-14T21:17:17.4840754Z 
2025-08-14T21:17:17.4840867Z     >>> t = torch.empty((10, 20))
2025-08-14T21:17:17.4841309Z     >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset())
2025-08-14T21:17:17.4841745Z     200
2025-08-14T21:17:17.4842110Z 
2025-08-14T21:17:17.4842218Z     >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:17.4842562Z     >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11))
2025-08-14T21:17:17.4842925Z     >>> size = compute_required_storage_length(
2025-08-14T21:17:17.4843308Z     ...     t2.shape, t2.stride(), t2.storage_offset()
2025-08-14T21:17:17.4843644Z     ... )
2025-08-14T21:17:17.4843861Z     >>> size == t.storage().size()
2025-08-14T21:17:17.4844147Z     True
2025-08-14T21:17:17.4844266Z 
2025-08-14T21:17:17.4844473Z     A valid tensor may have a larger storage size, but never smaller
2025-08-14T21:17:17.4844783Z 
2025-08-14T21:17:17.4844901Z     >>> slice = torch.empty(100)[20:40]
2025-08-14T21:17:17.4845208Z     >>> slice.storage().size()
2025-08-14T21:17:17.4845481Z     100
2025-08-14T21:17:17.4845594Z 
2025-08-14T21:17:17.4845717Z     >>> compute_required_storage_length(
2025-08-14T21:17:17.4846088Z     ...     slice.shape, slice.stride(), slice.storage_offset()
2025-08-14T21:17:17.4846451Z     ... )
2025-08-14T21:17:17.4846660Z     40
2025-08-14T21:17:17.4846771Z 
2025-08-14T21:17:17.4846851Z     
2025-08-14T21:17:17.4847216Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.4847583Z 
2025-08-14T21:17:17.5456820Z msg = Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66.
2025-08-14T21:17:17.5457739Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.5458588Z Check if the current accelerator is available at runtime: it was build, all the
2025-08-14T21:17:17.5459183Z     required drivers are available and at least one device is visible.
2025-08-14T21:17:17.5459673Z     See :ref:`accelerator<accelerators>` for details.
2025-08-14T21:17:17.5459931Z 
2025-08-14T21:17:17.5460021Z     Returns:
2025-08-14T21:17:17.5460432Z         bool: A boolean indicating if there is an available :ref:`accelerator<accelerators>`.
2025-08-14T21:17:17.5460837Z 
2025-08-14T21:17:17.5461122Z     .. note:: This API delegates to the device-specific version of `is_available`.
2025-08-14T21:17:17.5461731Z         On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set,
2025-08-14T21:17:17.5462366Z         this function will NOT poison fork. Otherwise, it will. For more details, see
2025-08-14T21:17:17.5462884Z         :ref:`multiprocessing-poison-fork-note`.
2025-08-14T21:17:17.5463134Z 
2025-08-14T21:17:17.5463245Z     Example::
2025-08-14T21:17:17.5463375Z 
2025-08-14T21:17:17.5463640Z         >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:17.5464110Z     
2025-08-14T21:17:17.5464786Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78))
2025-08-14T21:17:17.5465453Z 
2025-08-14T21:17:17.5465722Z assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:17.5466191Z                                         ^
2025-08-14T21:17:17.5474086Z msg = Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212.
2025-08-14T21:17:17.5475002Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.5475575Z Wait for all kernels in all streams on the given device to complete.
2025-08-14T21:17:17.5475912Z 
2025-08-14T21:17:17.5476012Z     Args:
2025-08-14T21:17:17.5476456Z         device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match
2025-08-14T21:17:17.5477117Z             the current :ref:`accelerator<accelerators>` device type. If not given,
2025-08-14T21:17:17.5477674Z             use :func:`torch.accelerator.current_device_index` by default.
2025-08-14T21:17:17.5478000Z 
2025-08-14T21:17:17.5478491Z     .. note:: This function is a no-op if the current :ref:`accelerator<accelerators>` is not initialized.
2025-08-14T21:17:17.5478921Z 
2025-08-14T21:17:17.5479028Z     Example::
2025-08-14T21:17:17.5479162Z 
2025-08-14T21:17:17.5479304Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:17.5479837Z         >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:17.5480379Z         >>> start_event = torch.Event(enable_timing=True)
2025-08-14T21:17:17.5480783Z         >>> end_event = torch.Event(enable_timing=True)
2025-08-14T21:17:17.5481136Z         >>> start_event.record()
2025-08-14T21:17:17.5481575Z         >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator())
2025-08-14T21:17:17.5482045Z         >>> sum = torch.sum(tensor)
2025-08-14T21:17:17.5482349Z         >>> end_event.record()
2025-08-14T21:17:17.5482665Z         >>> torch.accelerator.synchronize()
2025-08-14T21:17:17.5483075Z         >>> elapsed_time_ms = start_event.elapsed_time(end_event)
2025-08-14T21:17:17.5483451Z     
2025-08-14T21:17:17.5484119Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78))
2025-08-14T21:17:17.5484798Z 
2025-08-14T21:17:17.5485055Z assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:17.5485533Z                                         ^
2025-08-14T21:17:17.5777563Z msg = Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434.
2025-08-14T21:17:17.5778601Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:17.5779092Z Retrieves the CUDA runtime API module.
2025-08-14T21:17:17.5779310Z 
2025-08-14T21:17:17.5779314Z 
2025-08-14T21:17:17.5779581Z     This function initializes the CUDA runtime environment if it is not already
2025-08-14T21:17:17.5780182Z     initialized and returns the CUDA runtime API module (_cudart). The CUDA
2025-08-14T21:17:17.5780750Z     runtime API module provides access to various CUDA runtime functions.
2025-08-14T21:17:17.5781099Z 
2025-08-14T21:17:17.5781183Z     Args:
2025-08-14T21:17:17.5781397Z         ``None``
2025-08-14T21:17:17.5781532Z 
2025-08-14T21:17:17.5781615Z     Returns:
2025-08-14T21:17:17.5781893Z         module: The CUDA runtime API module (_cudart).
2025-08-14T21:17:17.5782145Z 
2025-08-14T21:17:17.5782242Z     Raises:
2025-08-14T21:17:17.5782590Z         RuntimeError: If CUDA cannot be re-initialized in a forked subprocess.
2025-08-14T21:17:17.5783330Z         AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable.
2025-08-14T21:17:17.5783817Z 
2025-08-14T21:17:17.5783950Z     Example of CUDA operations with profiling:
2025-08-14T21:17:17.5784298Z         >>> import torch
2025-08-14T21:17:17.5784587Z         >>> from torch.cuda import cudart, check_error
2025-08-14T21:17:17.5784933Z         >>> import os
2025-08-14T21:17:17.5785177Z         >>>
2025-08-14T21:17:17.5785422Z         >>> os.environ["CUDA_PROFILE"] = "1"
2025-08-14T21:17:17.5785723Z         >>>
2025-08-14T21:17:17.5785989Z         >>> def perform_cuda_operations_with_streams():
2025-08-14T21:17:17.5786359Z         >>>     stream = torch.cuda.Stream()
2025-08-14T21:17:17.5786691Z         >>>     with torch.cuda.stream(stream):
2025-08-14T21:17:17.5787052Z         >>>         x = torch.randn(100, 100, device='cuda')
2025-08-14T21:17:17.5787425Z         >>>         y = torch.randn(100, 100, device='cuda')
2025-08-14T21:17:17.5787765Z         >>>         z = torch.mul(x, y)
2025-08-14T21:17:17.5788070Z         >>>     return z
2025-08-14T21:17:17.5788316Z         >>>
2025-08-14T21:17:17.5788539Z         >>> torch.cuda.synchronize()
2025-08-14T21:17:17.5788889Z         >>> print("====== Start nsys profiling ======")
2025-08-14T21:17:17.5789279Z         >>> check_error(cudart().cudaProfilerStart())
2025-08-14T21:17:17.5789670Z         >>> with torch.autograd.profiler.emit_nvtx():
2025-08-14T21:17:17.5790172Z         >>>     result = perform_cuda_operations_with_streams()
2025-08-14T21:17:17.5790579Z         >>>     print("CUDA operations completed.")
2025-08-14T21:17:17.5790992Z         >>> check_error(torch.cuda.cudart().cudaProfilerStop())
2025-08-14T21:17:17.5791460Z         >>> print("====== End nsys profiling ======")
2025-08-14T21:17:17.5791716Z 
2025-08-14T21:17:17.5791915Z     To run this example and save the profiling information, execute:
2025-08-14T21:17:17.5792606Z         >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-08-14T21:17:17.5793085Z 
2025-08-14T21:17:17.5793347Z     This command profiles the CUDA operations in the provided script and saves
2025-08-14T21:17:17.5793905Z     the profiling information to a file named `trace_name.prof`.
2025-08-14T21:17:17.5794452Z     The `--profile-from-start off` option ensures that profiling starts only
2025-08-14T21:17:17.5794957Z     after the `cudaProfilerStart` call in the script.
2025-08-14T21:17:17.5795440Z     The `--csv` and `--print-summary` options format the profiling output as a
2025-08-14T21:17:17.5795918Z     CSV file and print a summary, respectively.
2025-08-14T21:17:17.5796414Z     The `-o` option specifies the output file name, and the `-f` option forces the
2025-08-14T21:17:17.5796932Z     overwrite of the output file if it already exists.
2025-08-14T21:17:17.5797265Z     
2025-08-14T21:17:17.5798027Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2))
2025-08-14T21:17:17.5798862Z 
2025-08-14T21:17:17.5799219Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-08-14T21:17:17.5799770Z ^
2025-08-14T21:17:17.5955354Z msg = Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101.
2025-08-14T21:17:17.5956293Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.5956687Z 
2025-08-14T21:17:17.5956915Z Append the given callback function to this ``Future``, which will be run
2025-08-14T21:17:17.5957474Z when the ``Future`` is completed.  Multiple callbacks can be added to
2025-08-14T21:17:17.5958007Z the same ``Future``, but the order in which they will be executed cannot
2025-08-14T21:17:17.5958506Z be guaranteed (to enforce a certain order consider chaining:
2025-08-14T21:17:17.5959022Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which
2025-08-14T21:17:17.5959556Z is the reference to this ``Future``. The callback function can use the
2025-08-14T21:17:17.5960083Z :meth:`value` method to get the value. Note that if this ``Future`` is
2025-08-14T21:17:17.5960632Z already completed, the given callback will be run immediately inline.
2025-08-14T21:17:17.5960975Z 
2025-08-14T21:17:17.5961183Z If the ``Future``'s value contains tensors that reside on GPUs, the
2025-08-14T21:17:17.5961724Z callback might be invoked while the async kernels that are populating
2025-08-14T21:17:17.5962278Z those tensors haven't yet finished executing on the device. However, the
2025-08-14T21:17:17.5972956Z callback will be invoked with some dedicated streams set as current
2025-08-14T21:17:17.5973643Z (fetched from a global pool) which will be synchronized with those
2025-08-14T21:17:17.5974194Z kernels. Hence any operation performed by the callback on these tensors
2025-08-14T21:17:17.5974771Z will be scheduled on the device after the kernels complete. In other
2025-08-14T21:17:17.5975304Z words, as long as the callback doesn't switch streams, it can safely
2025-08-14T21:17:17.5975843Z manipulate the result without any additional synchronization. This is
2025-08-14T21:17:17.5976358Z similar to the non-blocking behavior of :meth:`wait`.
2025-08-14T21:17:17.5976630Z 
2025-08-14T21:17:17.5976860Z Similarly, if the callback returns a value that contains tensors that
2025-08-14T21:17:17.5977648Z reside on a GPU, it can do so even if the kernels that are producing
2025-08-14T21:17:17.5978180Z these tensors are still running on the device, as long as the callback
2025-08-14T21:17:17.5978732Z didn't change streams during its execution. If one wants to change
2025-08-14T21:17:17.5979512Z streams, one must be careful to re-synchronize them with the original
2025-08-14T21:17:17.5980057Z streams, that is, those that were current when the callback was invoked.
2025-08-14T21:17:17.5980406Z 
2025-08-14T21:17:17.5980502Z Args:
2025-08-14T21:17:17.5980835Z     callback(``Callable``): a ``Callable`` that takes this ``Future`` as
2025-08-14T21:17:17.5981277Z                             the only argument.
2025-08-14T21:17:17.5981497Z 
2025-08-14T21:17:17.5981580Z Returns:
2025-08-14T21:17:17.5981875Z     A new ``Future`` object that holds the return value of the
2025-08-14T21:17:17.5982344Z     ``callback`` and will be marked as completed when the given
2025-08-14T21:17:17.5982733Z     ``callback`` finishes.
2025-08-14T21:17:17.5982923Z 
2025-08-14T21:17:17.5983130Z .. note:: Note that if the callback function throws, either
2025-08-14T21:17:17.5983632Z     through the original future being completed with an exception and
2025-08-14T21:17:17.5984164Z     calling ``fut.wait()``, or through other code in the callback, the
2025-08-14T21:17:17.5984669Z     future returned by ``then`` will be marked appropriately with the
2025-08-14T21:17:17.5985191Z     encountered error. However, if this callback later completes
2025-08-14T21:17:17.5985857Z     additional futures, those futures are not marked as completed with
2025-08-14T21:17:17.5986391Z     an error and the user is responsible for handling completion/waiting
2025-08-14T21:17:17.5986830Z     on those futures independently.
2025-08-14T21:17:17.5987037Z 
2025-08-14T21:17:17.5987141Z Example::
2025-08-14T21:17:17.5987262Z 
2025-08-14T21:17:17.5987425Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-08-14T21:17:17.5987775Z     >>> def callback(fut):
2025-08-14T21:17:17.5988092Z     ...     print(f"RPC return value is {fut.wait()}.")
2025-08-14T21:17:17.5988459Z     >>> fut = torch.futures.Future()
2025-08-14T21:17:17.5988831Z     >>> # The inserted callback will print the return value when
2025-08-14T21:17:17.5989244Z     >>> # receiving the response from "worker1"
2025-08-14T21:17:17.5989589Z     >>> cb_fut = fut.then(callback)
2025-08-14T21:17:17.5989889Z     >>> chain_cb_fut = cb_fut.then(
2025-08-14T21:17:17.5990245Z     ...     lambda x : print(f"Chained cb done. {x.wait()}")
2025-08-14T21:17:17.5990604Z     ... )
2025-08-14T21:17:17.5990816Z     >>> fut.set_result(5)
2025-08-14T21:17:17.5991092Z     RPC return value is 5.
2025-08-14T21:17:17.5991371Z     Chained cb done. None
2025-08-14T21:17:17.5991623Z 
2025-08-14T21:17:17.5991891Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.5992261Z 
2025-08-14T21:17:17.5992856Z msg = Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211.
2025-08-14T21:17:17.5993753Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.5994152Z 
2025-08-14T21:17:17.5994361Z Set the result for this ``Future``, which will mark this ``Future`` as
2025-08-14T21:17:17.5994911Z completed and trigger all attached callbacks. Note that a ``Future``
2025-08-14T21:17:17.5995353Z cannot be marked completed twice.
2025-08-14T21:17:17.5995571Z 
2025-08-14T21:17:17.5995797Z If the result contains tensors that reside on GPUs, this method can be
2025-08-14T21:17:17.5996343Z called even if the asynchronous kernels that are populating those
2025-08-14T21:17:17.5996890Z tensors haven't yet completed running on the device, provided that the
2025-08-14T21:17:17.5997442Z streams on which those kernels were enqueued are set as the current ones
2025-08-14T21:17:17.5998000Z when this method is called. Put simply, it's safe to call this method
2025-08-14T21:17:17.5998640Z immediately after launching those kernels, without any additional
2025-08-14T21:17:17.5999197Z synchronization, as long as one doesn't change streams in between. This
2025-08-14T21:17:17.5999765Z method will record events on all the relevant current streams and will
2025-08-14T21:17:17.6000308Z use them to ensure proper scheduling for all the consumers of this
2025-08-14T21:17:17.6000719Z ``Future``.
2025-08-14T21:17:17.6000844Z 
2025-08-14T21:17:17.6000925Z Args:
2025-08-14T21:17:17.6001211Z     result (object): the result object of this ``Future``.
2025-08-14T21:17:17.6001486Z 
2025-08-14T21:17:17.6001598Z Example::
2025-08-14T21:17:17.6001720Z 
2025-08-14T21:17:17.6001865Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-08-14T21:17:17.6002224Z     >>> import threading
2025-08-14T21:17:17.6002490Z     >>> import time
2025-08-14T21:17:17.6002751Z     >>> def slow_set_future(fut, value):
2025-08-14T21:17:17.6003065Z     ...     time.sleep(0.5)
2025-08-14T21:17:17.6003353Z     ...     fut.set_result(value)
2025-08-14T21:17:17.6003673Z     >>> fut = torch.futures.Future()
2025-08-14T21:17:17.6003976Z     >>> t = threading.Thread(
2025-08-14T21:17:17.6004270Z     ...     target=slow_set_future,
2025-08-14T21:17:17.6004587Z     ...     args=(fut, torch.ones(2) * 3)
2025-08-14T21:17:17.6004877Z     ... )
2025-08-14T21:17:17.6005086Z     >>> t.start()
2025-08-14T21:17:17.6005329Z     >>> print(fut.wait())
2025-08-14T21:17:17.6005579Z     tensor([3., 3.])
2025-08-14T21:17:17.6005819Z     >>> t.join()
2025-08-14T21:17:17.6006036Z 
2025-08-14T21:17:17.6006305Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.6006674Z 
2025-08-14T21:17:17.6108801Z msg = Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145.
2025-08-14T21:17:17.6109891Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.6110501Z Compiles compute shader from source and allows one to invoke kernels
2025-08-14T21:17:17.6111007Z     defined there from the comfort of Python runtime
2025-08-14T21:17:17.6111445Z     Example::
2025-08-14T21:17:17.6111584Z 
2025-08-14T21:17:17.6111723Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS)
2025-08-14T21:17:17.6112095Z         >>> lib = torch.mps.compile_shader(
2025-08-14T21:17:17.6112731Z         ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }"
2025-08-14T21:17:17.6113314Z         ...  )
2025-08-14T21:17:17.6113571Z         >>> x = torch.zeros(16, device="mps")
2025-08-14T21:17:17.6113899Z         >>> lib.full(x, 3.14)
2025-08-14T21:17:17.6114156Z     
2025-08-14T21:17:17.6114524Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.6114905Z 
2025-08-14T21:17:17.6344073Z msg = Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202.
2025-08-14T21:17:17.6345023Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.6345643Z Return the sum of each row of the given sparse tensor.
2025-08-14T21:17:17.6345923Z 
2025-08-14T21:17:17.6346201Z     Returns the sum of each row of the sparse tensor :attr:`input` in the given
2025-08-14T21:17:17.6346793Z     dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions,
2025-08-14T21:17:17.6347335Z     reduce over all of them. When sum over all ``sparse_dim``, this method
2025-08-14T21:17:17.6347883Z     returns a dense tensor instead of a sparse tensor.
2025-08-14T21:17:17.6348156Z 
2025-08-14T21:17:17.6348476Z     All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output
2025-08-14T21:17:17.6349074Z     tensor having :attr:`dim` fewer dimensions than :attr:`input`.
2025-08-14T21:17:17.6349422Z 
2025-08-14T21:17:17.6349657Z     During backward, only gradients at ``nnz`` locations of :attr:`input`
2025-08-14T21:17:17.6350508Z     will propagate back. Note that the gradients of :attr:`input` is coalesced.
2025-08-14T21:17:17.6350952Z 
2025-08-14T21:17:17.6351041Z     Args:
2025-08-14T21:17:17.6351296Z         input (Tensor): the input sparse tensor
2025-08-14T21:17:17.6351948Z         dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce
2025-08-14T21:17:17.6352503Z             over all dims.
2025-08-14T21:17:17.6353113Z         dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor.
2025-08-14T21:17:17.6353732Z             Default: dtype of :attr:`input`.
2025-08-14T21:17:17.6353970Z 
2025-08-14T21:17:17.6354075Z     Example::
2025-08-14T21:17:17.6354218Z 
2025-08-14T21:17:17.6354303Z         >>> nnz = 3
2025-08-14T21:17:17.6354546Z         >>> dims = [5, 5, 2, 3]
2025-08-14T21:17:17.6354879Z         >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)),
2025-08-14T21:17:17.6355340Z                            torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz)
2025-08-14T21:17:17.6355783Z         >>> V = torch.randn(nnz, dims[2], dims[3])
2025-08-14T21:17:17.6356129Z         >>> size = torch.Size(dims)
2025-08-14T21:17:17.6356468Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:17.6356853Z         >>> S = torch.sparse_coo_tensor(I, V, size)
2025-08-14T21:17:17.6357179Z         >>> S
2025-08-14T21:17:17.6357445Z         tensor(indices=tensor([[2, 0, 3],
2025-08-14T21:17:17.6357751Z                                [2, 4, 1]]),
2025-08-14T21:17:17.6358104Z                values=tensor([[[-0.6438, -1.6467,  1.4004],
2025-08-14T21:17:17.6358589Z                                [ 0.3411,  0.0918, -0.2312]],
2025-08-14T21:17:17.6358810Z 
2025-08-14T21:17:17.6358918Z                               [[ 0.5348,  0.0634, -2.0494],
2025-08-14T21:17:17.6359256Z                                [-0.7125, -1.0646,  2.1844]],
2025-08-14T21:17:17.6359477Z 
2025-08-14T21:17:17.6359600Z                               [[ 0.1276,  0.1874, -0.6334],
2025-08-14T21:17:17.6359942Z                                [-1.9682, -0.5340,  0.7483]]]),
2025-08-14T21:17:17.6360304Z                size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo)
2025-08-14T21:17:17.6360568Z 
2025-08-14T21:17:17.6360761Z         # when sum over only part of sparse_dims, return a sparse tensor
2025-08-14T21:17:17.6361190Z         >>> torch.sparse.sum(S, [1, 3])
2025-08-14T21:17:17.6361512Z         tensor(indices=tensor([[0, 2, 3]]),
2025-08-14T21:17:17.6361851Z                values=tensor([[-1.4512,  0.4073],
2025-08-14T21:17:17.6362184Z                               [-0.8901,  0.2017],
2025-08-14T21:17:17.6362506Z                               [-0.3183, -1.7539]]),
2025-08-14T21:17:17.6362853Z                size=(5, 2), nnz=3, layout=torch.sparse_coo)
2025-08-14T21:17:17.6363114Z 
2025-08-14T21:17:17.6363267Z         # when sum over all sparse dim, return a dense tensor
2025-08-14T21:17:17.6363645Z         # with summed dims squeezed
2025-08-14T21:17:17.6363951Z         >>> torch.sparse.sum(S, [0, 1, 3])
2025-08-14T21:17:17.6364277Z         tensor([-2.6596, -1.1450])
2025-08-14T21:17:17.6364558Z     
2025-08-14T21:17:17.6364914Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.6365295Z 
2025-08-14T21:17:17.6365826Z msg = Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=550.
2025-08-14T21:17:17.6366730Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:17.6367303Z Decorate function, to extend gradcheck for sparse tensors.
2025-08-14T21:17:17.6367596Z 
2025-08-14T21:17:17.6367811Z     Decorator for torch.autograd.gradcheck or its functools.partial
2025-08-14T21:17:17.6368360Z     variants that extends the gradcheck function with support to input
2025-08-14T21:17:17.6368867Z     functions that operate on or/and return sparse tensors.
2025-08-14T21:17:17.6369149Z 
2025-08-14T21:17:17.6369372Z     The specified gradcheck function itself is guaranteed to operate
2025-08-14T21:17:17.6369857Z     on strided tensors only.
2025-08-14T21:17:17.6370051Z 
2025-08-14T21:17:17.6370139Z     For example:
2025-08-14T21:17:17.6370276Z 
2025-08-14T21:17:17.6370528Z     >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck)
2025-08-14T21:17:17.6370961Z     >>> x = (
2025-08-14T21:17:17.6371256Z     ...     torch.tensor([[0, 1], [2, 3]], dtype=torch.float64)
2025-08-14T21:17:17.6371630Z     ...     .to_sparse_coo()
2025-08-14T21:17:17.6371917Z     ...     .requires_grad_(True)
2025-08-14T21:17:17.6372192Z     ... )
2025-08-14T21:17:17.6372451Z     >>> gradcheck(lambda x: x.to_sparse_csr(), x)
2025-08-14T21:17:17.6372779Z     True
2025-08-14T21:17:17.6372970Z     
2025-08-14T21:17:17.6373339Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:17.6373708Z 
2025-08-14T21:17:18.4939656Z msg = Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39.
2025-08-14T21:17:18.4940577Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:18.4940960Z 
2025-08-14T21:17:18.4941232Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that
2025-08-14T21:17:18.4941779Z maps ``func`` over some dimension of the inputs. Semantically, vmap
2025-08-14T21:17:18.4942323Z pushes the map into PyTorch operations called by ``func``, effectively
2025-08-14T21:17:18.4942782Z vectorizing those operations.
2025-08-14T21:17:18.4943246Z 
2025-08-14T21:17:18.4943479Z vmap is useful for handling batch dimensions: one can write a function
2025-08-14T21:17:18.4944008Z ``func`` that runs on examples and then lift it to a function that can
2025-08-14T21:17:18.4944550Z take batches of examples with ``vmap(func)``. vmap can also be used to
2025-08-14T21:17:18.4945063Z compute batched gradients when composed with autograd.
2025-08-14T21:17:18.4945343Z 
2025-08-14T21:17:18.4945476Z .. note::
2025-08-14T21:17:18.4945785Z     :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for
2025-08-14T21:17:18.4946222Z     convenience. Use whichever one you'd like.
2025-08-14T21:17:18.4946462Z 
2025-08-14T21:17:18.4946558Z Args:
2025-08-14T21:17:18.4946883Z     func (function): A Python function that takes one or more arguments.
2025-08-14T21:17:18.4947332Z         Must return one or more Tensors.
2025-08-14T21:17:18.4947763Z     in_dims (int or nested structure): Specifies which dimension of the
2025-08-14T21:17:18.4948253Z         inputs should be mapped over. ``in_dims`` should have a
2025-08-14T21:17:18.4948744Z         structure like the inputs. If the ``in_dim`` for a particular
2025-08-14T21:17:18.4949283Z         input is None, then that indicates there is no map dimension.
2025-08-14T21:17:18.4949683Z         Default: 0.
2025-08-14T21:17:18.4950152Z     out_dims (int or Tuple[int]): Specifies where the mapped dimension
2025-08-14T21:17:18.4950835Z         should appear in the outputs. If ``out_dims`` is a Tuple, then
2025-08-14T21:17:18.4951630Z         it should have one element per output. Default: 0.
2025-08-14T21:17:18.4952497Z     randomness (str): Specifies whether the randomness in this
2025-08-14T21:17:18.4953073Z         vmap should be the same or different across batches. If 'different',
2025-08-14T21:17:18.4953597Z         the randomness for each batch will be different. If 'same', the
2025-08-14T21:17:18.4954142Z         randomness will be the same across batches. If 'error', any calls to
2025-08-14T21:17:18.4954691Z         random functions will error. Default: 'error'. WARNING: this flag
2025-08-14T21:17:18.4955238Z         only applies to random PyTorch operations and does not apply to
2025-08-14T21:17:18.4955687Z         Python's random module or numpy randomness.
2025-08-14T21:17:18.4956168Z     chunk_size (None or int): If None (default), apply a single vmap over inputs.
2025-08-14T21:17:18.4956735Z         If not None, then compute the vmap :attr:`chunk_size` samples at a time.
2025-08-14T21:17:18.4957496Z         Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop.
2025-08-14T21:17:18.4958151Z         If you run into memory issues computing the vmap, please try a non-None chunk_size.
2025-08-14T21:17:18.4958548Z 
2025-08-14T21:17:18.4958634Z Returns:
2025-08-14T21:17:18.4958954Z     Returns a new "batched" function. It takes the same inputs as
2025-08-14T21:17:18.4959431Z     ``func``, except each input has an extra dimension at the index
2025-08-14T21:17:18.4959933Z     specified by ``in_dims``. It takes returns the same outputs as
2025-08-14T21:17:18.4960433Z     ``func``, except each output has an extra dimension at the index
2025-08-14T21:17:18.4960833Z     specified by ``out_dims``.
2025-08-14T21:17:18.4961032Z 
2025-08-14T21:17:18.4961116Z .. warning:
2025-08-14T21:17:18.4961452Z     :func:`vmap` works best with functional-style code. Please do not
2025-08-14T21:17:18.4961962Z     perform any side-effects in ``func``, with the exception of
2025-08-14T21:17:18.4962496Z     in-place PyTorch operations. Examples of side-effects include mutating
2025-08-14T21:17:18.4963082Z     Python data structures and assigning values to variables not captured
2025-08-14T21:17:18.4963518Z     in ``func``.
2025-08-14T21:17:18.4963655Z 
2025-08-14T21:17:18.4963889Z One example of using :func:`vmap` is to compute batched dot products. PyTorch
2025-08-14T21:17:18.4964465Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully
2025-08-14T21:17:18.4965113Z rummaging through docs, use :func:`vmap` to construct a new function.
2025-08-14T21:17:18.4965524Z 
2025-08-14T21:17:18.4965658Z     >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:18.4966065Z     >>> batched_dot = torch.func.vmap(torch.dot)  # [N, D], [N, D] -> [N]
2025-08-14T21:17:18.4966521Z     >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-08-14T21:17:18.4966864Z     >>> batched_dot(x, y)
2025-08-14T21:17:18.4967033Z 
2025-08-14T21:17:18.4967260Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler
2025-08-14T21:17:18.4967722Z model authoring experience.
2025-08-14T21:17:18.4967917Z 
2025-08-14T21:17:18.4968027Z     >>> batch_size, feature_size = 3, 5
2025-08-14T21:17:18.4968424Z     >>> weights = torch.randn(feature_size, requires_grad=True)
2025-08-14T21:17:18.4968789Z     >>>
2025-08-14T21:17:18.4969013Z     >>> def model(feature_vec):
2025-08-14T21:17:18.4969336Z     >>> # Very simple linear model with activation
2025-08-14T21:17:18.4969694Z     >>>     return feature_vec.dot(weights).relu()
2025-08-14T21:17:18.4970023Z     >>>
2025-08-14T21:17:18.4970293Z     >>> examples = torch.randn(batch_size, feature_size)
2025-08-14T21:17:18.4970665Z     >>> result = torch.vmap(model)(examples)
2025-08-14T21:17:18.4970902Z 
2025-08-14T21:17:18.4971148Z :func:`vmap` can also help vectorize computations that were previously difficult
2025-08-14T21:17:18.4971753Z or impossible to batch. One example is higher-order gradient computation.
2025-08-14T21:17:18.4972339Z The PyTorch autograd engine computes vjps (vector-Jacobian products).
2025-08-14T21:17:18.4972912Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually
2025-08-14T21:17:18.4973510Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`,
2025-08-14T21:17:18.4974115Z we can vectorize the whole computation, computing the Jacobian in a single
2025-08-14T21:17:18.4974567Z call to ``autograd.grad``.
2025-08-14T21:17:18.4974756Z 
2025-08-14T21:17:18.4974842Z     >>> # Setup
2025-08-14T21:17:18.4975066Z     >>> N = 5
2025-08-14T21:17:18.4975299Z     >>> f = lambda x: x**2
2025-08-14T21:17:18.4975583Z     >>> x = torch.randn(N, requires_grad=True)
2025-08-14T21:17:18.4975907Z     >>> y = f(x)
2025-08-14T21:17:18.4976146Z     >>> I_N = torch.eye(N)
2025-08-14T21:17:18.4976391Z     >>>
2025-08-14T21:17:18.4976612Z     >>> # Sequential approach
2025-08-14T21:17:18.4977017Z     >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0]
2025-08-14T21:17:18.4977454Z     >>>                  for v in I_N.unbind()]
2025-08-14T21:17:18.4977883Z     >>> jacobian = torch.stack(jacobian_rows)
2025-08-14T21:17:18.4978208Z     >>>
2025-08-14T21:17:18.4978433Z     >>> # vectorized gradient computation
2025-08-14T21:17:18.4978758Z     >>> def get_vjp(v):
2025-08-14T21:17:18.4979044Z     >>>     return torch.autograd.grad(y, x, v)
2025-08-14T21:17:18.4979389Z     >>> jacobian = torch.vmap(get_vjp)(I_N)
2025-08-14T21:17:18.4979627Z 
2025-08-14T21:17:18.4979890Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions
2025-08-14T21:17:18.4980288Z 
2025-08-14T21:17:18.4980392Z     >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:18.4980706Z     >>> batched_dot = torch.vmap(
2025-08-14T21:17:18.4981001Z     ...     torch.vmap(torch.dot)
2025-08-14T21:17:18.4981322Z     ... )  # [N1, N0, D], [N1, N0, D] -> [N1, N0]
2025-08-14T21:17:18.4981692Z     >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5)
2025-08-14T21:17:18.4982060Z     >>> batched_dot(x, y)  # tensor of size [2, 3]
2025-08-14T21:17:18.4982309Z 
2025-08-14T21:17:18.4982555Z If the inputs are not batched along the first dimension, ``in_dims`` specifies
2025-08-14T21:17:18.4983074Z the dimension that each inputs are batched along as
2025-08-14T21:17:18.4983336Z 
2025-08-14T21:17:18.4983452Z     >>> torch.dot  # [N], [N] -> []
2025-08-14T21:17:18.4983867Z     >>> batched_dot = torch.vmap(torch.dot, in_dims=1)  # [N, D], [N, D] -> [D]
2025-08-14T21:17:18.4984336Z     >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-08-14T21:17:18.4984672Z     >>> batched_dot(
2025-08-14T21:17:18.4984968Z     ...     x, y
2025-08-14T21:17:18.4985304Z     ... )  # output is [5] instead of [2] if batched along the 0th dimension
2025-08-14T21:17:18.4985627Z 
2025-08-14T21:17:18.4985888Z If there are multiple inputs each of which is batched along different dimensions,
2025-08-14T21:17:18.4986478Z ``in_dims`` must be a tuple with the batch dimension for each input as
2025-08-14T21:17:18.4986793Z 
2025-08-14T21:17:18.4986901Z     >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:18.4987353Z     >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None))  # [N, D], [D] -> [N]
2025-08-14T21:17:18.4987838Z     >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-08-14T21:17:18.4988152Z     >>> batched_dot(
2025-08-14T21:17:18.4988397Z     ...     x, y
2025-08-14T21:17:18.4988729Z     ... )  # second arg doesn't have a batch dim because in_dim[1] was None
2025-08-14T21:17:18.4989038Z 
2025-08-14T21:17:18.4989284Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct
2025-08-14T21:17:18.4989741Z matching the shape of the input:
2025-08-14T21:17:18.4989952Z 
2025-08-14T21:17:18.4990090Z     >>> f = lambda dict: torch.dot(dict["x"], dict["y"])
2025-08-14T21:17:18.4990464Z     >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-08-14T21:17:18.4990787Z     >>> input = {"x": x, "y": y}
2025-08-14T21:17:18.4991158Z     >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},))
2025-08-14T21:17:18.4991652Z     >>> batched_dot(input)
2025-08-14T21:17:18.4991825Z 
2025-08-14T21:17:18.4992116Z By default, the output is batched along the first dimension. However, it can be batched
2025-08-14T21:17:18.4992624Z along any dimension by using ``out_dims``
2025-08-14T21:17:18.4992868Z 
2025-08-14T21:17:18.4992964Z     >>> f = lambda x: x**2
2025-08-14T21:17:18.4993238Z     >>> x = torch.randn(2, 5)
2025-08-14T21:17:18.4993541Z     >>> batched_pow = torch.vmap(f, out_dims=1)
2025-08-14T21:17:18.4993884Z     >>> batched_pow(x)  # [5, 2]
2025-08-14T21:17:18.4994070Z 
2025-08-14T21:17:18.4994376Z For any function that uses kwargs, the returned function will not batch the kwargs but will
2025-08-14T21:17:18.4994880Z accept kwargs
2025-08-14T21:17:18.4995012Z 
2025-08-14T21:17:18.4995109Z     >>> x = torch.randn([2, 5])
2025-08-14T21:17:18.4995396Z     >>> def fn(x, scale=4.):
2025-08-14T21:17:18.4995677Z     >>>   return x * scale
2025-08-14T21:17:18.4995924Z     >>>
2025-08-14T21:17:18.4996149Z     >>> batched_pow = torch.vmap(fn)
2025-08-14T21:17:18.4996501Z     >>> assert torch.allclose(batched_pow(x), x * 4)
2025-08-14T21:17:18.4997071Z     >>> batched_pow(x, scale=x)  # scale is not batched, output has shape [2, 2, 5]
2025-08-14T21:17:18.4997431Z 
2025-08-14T21:17:18.4997531Z .. note::
2025-08-14T21:17:18.4997882Z     vmap does not provide general autobatching or handle variable-length
2025-08-14T21:17:18.4998319Z     sequences out of the box.
2025-08-14T21:17:18.4998518Z 
2025-08-14T21:17:18.4998771Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:18.4999159Z 
2025-08-14T21:17:18.4999667Z msg = Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306.
2025-08-14T21:17:18.5000524Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:18.5001154Z ``grad`` operator helps computing gradients of ``func`` with respect to the
2025-08-14T21:17:18.5001703Z     input(s) specified by ``argnums``. This operator can be nested to
2025-08-14T21:17:18.5002144Z     compute higher-order gradients.
2025-08-14T21:17:18.5002369Z 
2025-08-14T21:17:18.5002456Z     Args:
2025-08-14T21:17:18.5002799Z         func (Callable): A Python function that takes one or more arguments.
2025-08-14T21:17:18.5003386Z             Must return a single-element Tensor. If specified ``has_aux`` equals ``True``,
2025-08-14T21:17:18.5004040Z             function can return a tuple of single-element Tensor and other auxiliary objects:
2025-08-14T21:17:18.5004529Z             ``(output, aux)``.
2025-08-14T21:17:18.5005043Z         argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to.
2025-08-14T21:17:18.5005651Z             ``argnums`` can be single integer or tuple of integers. Default: 0.
2025-08-14T21:17:18.5006195Z         has_aux (bool): Flag indicating that ``func`` returns a tensor and other
2025-08-14T21:17:18.5006704Z             auxiliary objects: ``(output, aux)``. Default: False.
2025-08-14T21:17:18.5006979Z 
2025-08-14T21:17:18.5007067Z     Returns:
2025-08-14T21:17:18.5007489Z         Function to compute gradients with respect to its inputs. By default, the output of
2025-08-14T21:17:18.5008143Z         the function is the gradient tensor(s) with respect to the first argument.
2025-08-14T21:17:18.5008773Z         If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects
2025-08-14T21:17:18.5009644Z         is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with
2025-08-14T21:17:18.5010175Z         respect to each ``argnums`` value is returned.
2025-08-14T21:17:18.5010430Z 
2025-08-14T21:17:18.5010553Z     Example of using ``grad``:
2025-08-14T21:17:18.5010739Z 
2025-08-14T21:17:18.5010840Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:18.5011144Z         >>> from torch.func import grad
2025-08-14T21:17:18.5011469Z         >>> x = torch.randn([])
2025-08-14T21:17:18.5011782Z         >>> cos_x = grad(lambda x: torch.sin(x))(x)
2025-08-14T21:17:18.5012134Z         >>> assert torch.allclose(cos_x, x.cos())
2025-08-14T21:17:18.5012465Z         >>>
2025-08-14T21:17:18.5012698Z         >>> # Second-order gradients
2025-08-14T21:17:18.5013045Z         >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x)
2025-08-14T21:17:18.5013455Z         >>> assert torch.allclose(neg_sin_x, -x.sin())
2025-08-14T21:17:18.5013699Z 
2025-08-14T21:17:18.5013958Z     When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients:
2025-08-14T21:17:18.5014325Z 
2025-08-14T21:17:18.5014425Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:18.5014737Z         >>> from torch.func import grad, vmap
2025-08-14T21:17:18.5015084Z         >>> batch_size, feature_size = 3, 5
2025-08-14T21:17:18.5015392Z         >>>
2025-08-14T21:17:18.5015621Z         >>> def model(weights, feature_vec):
2025-08-14T21:17:18.5015981Z         >>> # Very simple linear model with activation
2025-08-14T21:17:18.5016341Z         >>>     assert feature_vec.dim() == 1
2025-08-14T21:17:18.5016685Z         >>>     return feature_vec.dot(weights).relu()
2025-08-14T21:17:18.5017125Z         >>>
2025-08-14T21:17:18.5017390Z         >>> def compute_loss(weights, example, target):
2025-08-14T21:17:18.5017740Z         >>>     y = model(weights, example)
2025-08-14T21:17:18.5018101Z         >>>     return ((y - target) ** 2).mean()  # MSELoss
2025-08-14T21:17:18.5018437Z         >>>
2025-08-14T21:17:18.5018728Z         >>> weights = torch.randn(feature_size, requires_grad=True)
2025-08-14T21:17:18.5019177Z         >>> examples = torch.randn(batch_size, feature_size)
2025-08-14T21:17:18.5019570Z         >>> targets = torch.randn(batch_size)
2025-08-14T21:17:18.5019927Z         >>> inputs = (weights, examples, targets)
2025-08-14T21:17:18.5020389Z         >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))(
2025-08-14T21:17:18.5020841Z         ...     *inputs
2025-08-14T21:17:18.5021086Z         ... )
2025-08-14T21:17:18.5021211Z 
2025-08-14T21:17:18.5021386Z     Example of using ``grad`` with ``has_aux`` and ``argnums``:
2025-08-14T21:17:18.5021686Z 
2025-08-14T21:17:18.5021787Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:18.5022083Z         >>> from torch.func import grad
2025-08-14T21:17:18.5022402Z         >>> def my_loss_func(y, y_pred):
2025-08-14T21:17:18.5022751Z         >>>    loss_per_sample = (0.5 * y_pred - y) ** 2
2025-08-14T21:17:18.5023113Z         >>>    loss = loss_per_sample.mean()
2025-08-14T21:17:18.5023471Z         >>>    return loss, (y_pred, loss_per_sample)
2025-08-14T21:17:18.5023799Z         >>>
2025-08-14T21:17:18.5024155Z         >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True)
2025-08-14T21:17:18.5024518Z         >>> y_true = torch.rand(4)
2025-08-14T21:17:18.5024859Z         >>> y_preds = torch.rand(4, requires_grad=True)
2025-08-14T21:17:18.5025225Z         >>> out = fn(y_true, y_preds)
2025-08-14T21:17:18.5025674Z         >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample))
2025-08-14T21:17:18.5026050Z 
2025-08-14T21:17:18.5026144Z     .. note::
2025-08-14T21:17:18.5026461Z         Using PyTorch ``torch.no_grad`` together with ``grad``.
2025-08-14T21:17:18.5026747Z 
2025-08-14T21:17:18.5026908Z         Case 1: Using ``torch.no_grad`` inside a function:
2025-08-14T21:17:18.5027167Z 
2025-08-14T21:17:18.5027272Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:18.5027572Z             >>> def f(x):
2025-08-14T21:17:18.5027861Z             >>>     with torch.no_grad():
2025-08-14T21:17:18.5028169Z             >>>         c = x ** 2
2025-08-14T21:17:18.5028471Z             >>>     return x - c
2025-08-14T21:17:18.5028676Z 
2025-08-14T21:17:18.5028873Z         In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``.
2025-08-14T21:17:18.5029223Z 
2025-08-14T21:17:18.5029474Z         Case 2: Using ``grad`` inside ``torch.no_grad`` context manager:
2025-08-14T21:17:18.5029831Z 
2025-08-14T21:17:18.5029934Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:18.5030297Z             >>> with torch.no_grad():
2025-08-14T21:17:18.5030611Z             >>>     grad(f)(x)
2025-08-14T21:17:18.5030822Z 
2025-08-14T21:17:18.5031069Z         In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the
2025-08-14T21:17:18.5031744Z         outer one. This is because ``grad`` is a "function transform": its result
2025-08-14T21:17:18.5032312Z         should not depend on the result of a context manager outside of ``f``.
2025-08-14T21:17:18.5032661Z 
2025-08-14T21:17:18.5032743Z     
2025-08-14T21:17:18.5033114Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:18.5033487Z 
2025-08-14T21:17:20.1113063Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=397.
2025-08-14T21:17:20.1114068Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:20.1114632Z Register a FakeTensor implementation for this custom op.
2025-08-14T21:17:20.1114927Z 
2025-08-14T21:17:20.1115451Z         This is necessary to get the operator to work efficiently with torch.compile.
2025-08-14T21:17:20.1115843Z 
2025-08-14T21:17:20.1116071Z         The Fake impl (sometimes also known as a meta kernel or abstract impl)
2025-08-14T21:17:20.1116651Z         specifies the behavior of this operator on Tensors that carry no data.
2025-08-14T21:17:20.1117161Z         Given some input Tensors with certain properties
2025-08-14T21:17:20.1117678Z         (sizes/strides/storage_offset/device), it specifies what the properties of
2025-08-14T21:17:20.1118177Z         the output Tensors are.
2025-08-14T21:17:20.1118367Z 
2025-08-14T21:17:20.1118612Z         Please see :func:`torch.library.register_fake` for more details.
2025-08-14T21:17:20.1118930Z 
2025-08-14T21:17:20.1119029Z         Args:
2025-08-14T21:17:20.1119330Z             fn (Callable): The function to register as the FakeTensor
2025-08-14T21:17:20.1119722Z                 implementation.
2025-08-14T21:17:20.1119906Z 
2025-08-14T21:17:20.1120009Z         Examples:
2025-08-14T21:17:20.1120247Z             >>> import torch
2025-08-14T21:17:20.1120535Z             >>> import numpy as np
2025-08-14T21:17:20.1120847Z             >>> from torch import Tensor
2025-08-14T21:17:20.1121152Z             >>>
2025-08-14T21:17:20.1121471Z             >>> # Example 1: an operator without data-dependent output shape
2025-08-14T21:17:20.1122005Z             >>> @torch.library.custom_op("mylib::linear", mutates_args=())
2025-08-14T21:17:20.1122517Z             >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-08-14T21:17:20.1123049Z             >>>     return (x @ weight.t()) + bias
2025-08-14T21:17:20.1123371Z             >>>
2025-08-14T21:17:20.1123618Z             >>> @linear.register_fake
2025-08-14T21:17:20.1123923Z             >>> def _(x, weight, bias):
2025-08-14T21:17:20.1124244Z             >>>     assert x.dim() == 2
2025-08-14T21:17:20.1124568Z             >>>     assert weight.dim() == 2
2025-08-14T21:17:20.1124900Z             >>>     assert bias.dim() == 1
2025-08-14T21:17:20.1125245Z             >>>     assert x.shape[1] == weight.shape[1]
2025-08-14T21:17:20.1125624Z             >>>     assert weight.shape[0] == bias.shape[0]
2025-08-14T21:17:20.1125999Z             >>>     assert x.device == weight.device
2025-08-14T21:17:20.1126381Z             >>>     return x.new_empty(x.size(0), weight.size(0))
2025-08-14T21:17:20.1126734Z             >>>
2025-08-14T21:17:20.1126985Z             >>> x = torch.randn(2, 2)
2025-08-14T21:17:20.1127297Z             >>> weight = torch.randn(2, 2)
2025-08-14T21:17:20.1127750Z             >>> bias = torch.randn(2)
2025-08-14T21:17:20.1128099Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:20.1128548Z             >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias)
2025-08-14T21:17:20.1128992Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:20.1129493Z             >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias))
2025-08-14T21:17:20.1129948Z             >>>
2025-08-14T21:17:20.1130257Z             >>> # Example 2: an operator with data-dependent output shape
2025-08-14T21:17:20.1130760Z             >>> @torch.library.custom_op("mylib::nonzero", mutates_args=())
2025-08-14T21:17:20.1131197Z             >>> def nonzero(x: Tensor) -> Tensor:
2025-08-14T21:17:20.1131525Z             >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:20.1131876Z             >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-08-14T21:17:20.1132274Z             >>>     return torch.tensor(res, device=x.device)
2025-08-14T21:17:20.1132617Z             >>>
2025-08-14T21:17:20.1132854Z             >>> @nonzero.register_fake
2025-08-14T21:17:20.1133164Z             >>> def _(x):
2025-08-14T21:17:20.1133488Z             >>> # Number of nonzero-elements is data-dependent.
2025-08-14T21:17:20.1133917Z             >>> # Since we cannot peek at the data in an abstract impl,
2025-08-14T21:17:20.1134365Z             >>> # we use the ctx object to construct a new symint that
2025-08-14T21:17:20.1134868Z             >>> # represents the data-dependent size.
2025-08-14T21:17:20.1135326Z             >>>     ctx = torch.library.get_ctx()
2025-08-14T21:17:20.1135748Z             >>>     nnz = ctx.new_dynamic_size()
2025-08-14T21:17:20.1136097Z             >>>     shape = [nnz, x.dim()]
2025-08-14T21:17:20.1136472Z             >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-08-14T21:17:20.1136830Z             >>>     return result
2025-08-14T21:17:20.1137123Z             >>>
2025-08-14T21:17:20.1137386Z             >>> x = torch.tensor([0, 1, 2, 0, 0, 1])
2025-08-14T21:17:20.1137750Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:20.1138162Z             >>> out = torch.compile(nonzero, fullgraph=True)(x)
2025-08-14T21:17:20.1138601Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:20.1139016Z             >>> assert torch.allclose(out, x.nonzero())
2025-08-14T21:17:20.1139272Z 
2025-08-14T21:17:20.1139361Z         
2025-08-14T21:17:20.1140029Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('<source_block>', 37, 1, '_._ = None\n', 37, 2))
2025-08-14T21:17:20.1140670Z 
2025-08-14T21:17:20.1140769Z _._ = None
2025-08-14T21:17:20.1140971Z ^
2025-08-14T21:17:20.1254520Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94.
2025-08-14T21:17:20.1255724Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.1256107Z 
2025-08-14T21:17:20.1256353Z Registers a fake kernel based on the given operator profiles. This fake
2025-08-14T21:17:20.1256940Z kernel registration will override any existing fake kernel registrations.
2025-08-14T21:17:20.1257312Z 
2025-08-14T21:17:20.1257525Z The input is a dictionary mapping operator names to a set of operator
2025-08-14T21:17:20.1258095Z profiles, which we will use to generate fake kernels. The operator profiles
2025-08-14T21:17:20.1258656Z are a record of the input and output tensor metadata. Based on this
2025-08-14T21:17:20.1259203Z information we will match a given input to the recorded profile, and return
2025-08-14T21:17:20.1259792Z an output with the same metadata as in the recorded profile. If a profile
2025-08-14T21:17:20.1260280Z doesn't exist then an exception will be thrown.
2025-08-14T21:17:20.1260529Z 
2025-08-14T21:17:20.1260792Z The fake kernel generation is considered unsafe because it relies on the
2025-08-14T21:17:20.1261371Z rigid, pre-defined operator profiles that do not account for potential
2025-08-14T21:17:20.1261980Z variations in output behavior. Specifically, the generated kernels assume a
2025-08-14T21:17:20.1262613Z fixed relationship between input and output ranks. However, in reality, it's
2025-08-14T21:17:20.1263224Z possible that data-dependent operations may produce outputs of different
2025-08-14T21:17:20.1263818Z ranks even when given inputs of the same rank. The generated fake kernels
2025-08-14T21:17:20.1264388Z are inflexible and unable to accommodate these nuances, making them
2025-08-14T21:17:20.1264826Z potentially unsafe.
2025-08-14T21:17:20.1264974Z 
2025-08-14T21:17:20.1265058Z Args:
2025-08-14T21:17:20.1265401Z     op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator
2025-08-14T21:17:20.1265946Z         name to a set of operator profiles from which we will generate fake
2025-08-14T21:17:20.1266341Z         kernels.
2025-08-14T21:17:20.1266496Z 
2025-08-14T21:17:20.1266582Z Examples:
2025-08-14T21:17:20.1266712Z 
2025-08-14T21:17:20.1266881Z     >>> # Example: Registering an op-profile from draft-export
2025-08-14T21:17:20.1267261Z     >>> import torch
2025-08-14T21:17:20.1267571Z     >>> from torch.export._draft_export import draft_export
2025-08-14T21:17:20.1267934Z     >>>
2025-08-14T21:17:20.1268255Z     >>> @torch.library.custom_op("mylib::foo", mutates_args=())
2025-08-14T21:17:20.1268669Z     >>> def foo(x: Tensor, y: Tensor) -> Tensor:
2025-08-14T21:17:20.1269141Z     >>>     return x + y
2025-08-14T21:17:20.1269403Z     >>>
2025-08-14T21:17:20.1269622Z     >>> class M(torch.nn.Module):
2025-08-14T21:17:20.1269939Z     >>>     def forward(self, a, b):
2025-08-14T21:17:20.1270301Z     >>>         res = torch.ops.mylib.foo(a, b)  # no fake impl
2025-08-14T21:17:20.1270650Z     >>>         return res
2025-08-14T21:17:20.1270911Z     >>>
2025-08-14T21:17:20.1271204Z     >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4))
2025-08-14T21:17:20.1271670Z     >>>
2025-08-14T21:17:20.1272077Z     >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles):
2025-08-14T21:17:20.1272623Z     >>>     decomp = ep.run_decompositions()
2025-08-14T21:17:20.1272851Z 
2025-08-14T21:17:20.1272855Z 
2025-08-14T21:17:20.1273120Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.1273488Z 
2025-08-14T21:17:20.1332969Z msg = Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=96.
2025-08-14T21:17:20.1334079Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.1334723Z Create a custom operator whose implementation is backed by 1+ triton kernels.
2025-08-14T21:17:20.1335101Z 
2025-08-14T21:17:20.1335324Z     This is a more structured way of using triton kernels with PyTorch.
2025-08-14T21:17:20.1335916Z     Prefer using triton kernels with no ``torch.library`` custom operator wrappers
2025-08-14T21:17:20.1336694Z     (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because
2025-08-14T21:17:20.1337170Z     that is simpler;
2025-08-14T21:17:20.1337584Z     only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you
2025-08-14T21:17:20.1338183Z     want to create an operator that behaves like PyTorch built-in operators.
2025-08-14T21:17:20.1338745Z     For example, you may use a ``torch.library`` wrapper API to define the
2025-08-14T21:17:20.1339323Z     behavior of the triton kernel when passed a tensor subclass or under
2025-08-14T21:17:20.1339958Z     a TorchDispatchMode.
2025-08-14T21:17:20.1340185Z 
2025-08-14T21:17:20.1340536Z     Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op`
2025-08-14T21:17:20.1341009Z     when the implementation
2025-08-14T21:17:20.1341468Z     consists of 1+ triton kernels. :func:`torch.library.custom_op` treats
2025-08-14T21:17:20.1341983Z     custom operators as opaque (:func:`torch.compile` and
2025-08-14T21:17:20.1342504Z     :func:`torch.export.export` will never trace into them), but ``triton_op``
2025-08-14T21:17:20.1343092Z     makes the implementation visible to these subsystems, allowing them
2025-08-14T21:17:20.1343555Z     to optimize the triton kernel(s).
2025-08-14T21:17:20.1343769Z 
2025-08-14T21:17:20.1343971Z     Note that ``fn`` must only consist of calls to PyTorch-understood
2025-08-14T21:17:20.1344503Z     operators and triton kernels. Any triton kernels called inside ``fn``
2025-08-14T21:17:20.1345048Z     must be wrapped in a call to :func:`torch.library.wrap_triton`.
2025-08-14T21:17:20.1345353Z 
2025-08-14T21:17:20.1345449Z     Args:
2025-08-14T21:17:20.1345806Z         name (str): A name for the custom op that looks like "{namespace}::{name}",
2025-08-14T21:17:20.1346482Z             e.g. "mylib::my_linear". The name is used as the op's stable identifier
2025-08-14T21:17:20.1346985Z             in PyTorch subsystems (e.g. torch.export, FX graphs).
2025-08-14T21:17:20.1347517Z             To avoid name collisions, please use your project name as the namespace;
2025-08-14T21:17:20.1348080Z             e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace.
2025-08-14T21:17:20.1348692Z         mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates.
2025-08-14T21:17:20.1349330Z             This MUST be accurate, otherwise, the behavior is undefined. If "unknown",
2025-08-14T21:17:20.1350095Z             it pessimistically assumes that all inputs to the operator are being mutated.
2025-08-14T21:17:20.1350671Z         schema (None | str): A schema string for the operator. If None
2025-08-14T21:17:20.1351193Z             (recommended) we'll infer a schema for the operator from its type
2025-08-14T21:17:20.1351816Z             annotations. We recommend letting us infer a schema unless you
2025-08-14T21:17:20.1352255Z             have a specific reason not to.
2025-08-14T21:17:20.1352643Z             Example: "(Tensor x, int y) -> (Tensor, Tensor)".
2025-08-14T21:17:20.1352913Z 
2025-08-14T21:17:20.1353022Z     Example::
2025-08-14T21:17:20.1353155Z 
2025-08-14T21:17:20.1353304Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:20.1353640Z         >>> import torch
2025-08-14T21:17:20.1353962Z         >>> from torch.library import triton_op, wrap_triton
2025-08-14T21:17:20.1354318Z         >>>
2025-08-14T21:17:20.1354553Z         >>> import triton
2025-08-14T21:17:20.1354849Z         >>> from triton import language as tl
2025-08-14T21:17:20.1355158Z         >>>
2025-08-14T21:17:20.1355379Z         >>> @triton.jit
2025-08-14T21:17:20.1355639Z         >>> def add_kernel(
2025-08-14T21:17:20.1355902Z         >>>     in_ptr0,
2025-08-14T21:17:20.1356165Z         >>>     in_ptr1,
2025-08-14T21:17:20.1356425Z         >>>     out_ptr,
2025-08-14T21:17:20.1356672Z         >>>     n_elements,
2025-08-14T21:17:20.1356965Z         >>>     BLOCK_SIZE: "tl.constexpr",
2025-08-14T21:17:20.1357750Z         >>> ):
2025-08-14T21:17:20.1357989Z         >>>     pid = tl.program_id(axis=0)
2025-08-14T21:17:20.1358339Z         >>>     block_start = pid * BLOCK_SIZE
2025-08-14T21:17:20.1358725Z         >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-08-14T21:17:20.1359110Z         >>>     mask = offsets < n_elements
2025-08-14T21:17:20.1359453Z         >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-08-14T21:17:20.1359833Z         >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-08-14T21:17:20.1360189Z         >>>     output = x + y
2025-08-14T21:17:20.1360511Z         >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-08-14T21:17:20.1360864Z         >>>
2025-08-14T21:17:20.1361128Z         >>> @triton_op("mylib::add", mutates_args={})
2025-08-14T21:17:20.1361549Z         >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
2025-08-14T21:17:20.1361971Z         >>>     output = torch.empty_like(x)
2025-08-14T21:17:20.1362315Z         >>>     n_elements = output.numel()
2025-08-14T21:17:20.1362633Z         >>>
2025-08-14T21:17:20.1362844Z         >>>     def grid(meta):
2025-08-14T21:17:20.1363203Z         >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-08-14T21:17:20.1363585Z         >>>
2025-08-14T21:17:20.1363882Z         >>>     # NB: we need to wrap the triton kernel in a call to wrap_triton
2025-08-14T21:17:20.1364371Z         >>>     wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16)
2025-08-14T21:17:20.1364774Z         >>>     return output
2025-08-14T21:17:20.1365038Z         >>>
2025-08-14T21:17:20.1365257Z         >>> @torch.compile
2025-08-14T21:17:20.1365530Z         >>> def f(x, y):
2025-08-14T21:17:20.1365787Z         >>>     return add(x, y)
2025-08-14T21:17:20.1366064Z         >>>
2025-08-14T21:17:20.1366304Z         >>> x = torch.randn(3, device="cuda")
2025-08-14T21:17:20.1366653Z         >>> y = torch.randn(3, device="cuda")
2025-08-14T21:17:20.1366954Z         >>>
2025-08-14T21:17:20.1367170Z         >>> z = f(x, y)
2025-08-14T21:17:20.1367449Z         >>> assert torch.allclose(z, x + y)
2025-08-14T21:17:20.1367673Z 
2025-08-14T21:17:20.1367753Z     
2025-08-14T21:17:20.1368121Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.1368490Z 
2025-08-14T21:17:20.1369034Z msg = Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=296.
2025-08-14T21:17:20.1369995Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.1370574Z Allows capture of a triton kernel into a graph via make_fx or
2025-08-14T21:17:20.1370984Z     non-strict ``torch.export``.
2025-08-14T21:17:20.1371197Z 
2025-08-14T21:17:20.1371382Z     These technologies perform Dispatcher-based tracing (via
2025-08-14T21:17:20.1371890Z     ``__torch_dispatch__``) and cannot see calls to raw triton kernels.
2025-08-14T21:17:20.1372404Z     The ``wrap_triton`` API wraps a triton kernel into a callable that
2025-08-14T21:17:20.1372846Z     can actually be traced into a graph.
2025-08-14T21:17:20.1373067Z 
2025-08-14T21:17:20.1373291Z     Please use this API together with :func:`torch.library.triton_op`.
2025-08-14T21:17:20.1373616Z 
2025-08-14T21:17:20.1373717Z     Examples:
2025-08-14T21:17:20.1373845Z 
2025-08-14T21:17:20.1373944Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:20.1374225Z         >>> import torch
2025-08-14T21:17:20.1374488Z         >>> import triton
2025-08-14T21:17:20.1374765Z         >>> from triton import language as tl
2025-08-14T21:17:20.1375179Z         >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-08-14T21:17:20.1375603Z         >>> from torch.library import wrap_triton
2025-08-14T21:17:20.1375921Z         >>>
2025-08-14T21:17:20.1376140Z         >>> @triton.jit
2025-08-14T21:17:20.1376394Z         >>> def add_kernel(
2025-08-14T21:17:20.1376651Z         >>>     in_ptr0,
2025-08-14T21:17:20.1376906Z         >>>     in_ptr1,
2025-08-14T21:17:20.1377158Z         >>>     out_ptr,
2025-08-14T21:17:20.1377476Z         >>>     n_elements,
2025-08-14T21:17:20.1377751Z         >>>     BLOCK_SIZE: "tl.constexpr",
2025-08-14T21:17:20.1378062Z         >>> ):
2025-08-14T21:17:20.1378307Z         >>>     pid = tl.program_id(axis=0)
2025-08-14T21:17:20.1378632Z         >>>     block_start = pid * BLOCK_SIZE
2025-08-14T21:17:20.1379010Z         >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-08-14T21:17:20.1379385Z         >>>     mask = offsets < n_elements
2025-08-14T21:17:20.1379727Z         >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-08-14T21:17:20.1380101Z         >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-08-14T21:17:20.1380444Z         >>>     output = x + y
2025-08-14T21:17:20.1380759Z         >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-08-14T21:17:20.1381103Z         >>>
2025-08-14T21:17:20.1381322Z         >>> def add(x, y):
2025-08-14T21:17:20.1381613Z         >>>     output = torch.empty_like(x)
2025-08-14T21:17:20.1381946Z         >>>     n_elements = output.numel()
2025-08-14T21:17:20.1382255Z         >>>
2025-08-14T21:17:20.1382481Z         >>>     def grid_fn(meta):
2025-08-14T21:17:20.1382842Z         >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-08-14T21:17:20.1383221Z         >>>
2025-08-14T21:17:20.1383550Z         >>>     wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16)
2025-08-14T21:17:20.1383955Z         >>>     return output
2025-08-14T21:17:20.1384225Z         >>>
2025-08-14T21:17:20.1384471Z         >>> x = torch.randn(3, device="cuda")
2025-08-14T21:17:20.1384800Z         >>> y = torch.randn(3, device="cuda")
2025-08-14T21:17:20.1385133Z         >>> gm = make_fx(add)(x, y)
2025-08-14T21:17:20.1385438Z         >>> print(gm.code)
2025-08-14T21:17:20.1385711Z         >>> # def forward(self, x_1, y_1):
2025-08-14T21:17:20.1386168Z         >>> #     empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False)
2025-08-14T21:17:20.1386772Z         >>> #     triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation(
2025-08-14T21:17:20.1387272Z         >>> #         kernel_idx = 0, constant_args_idx = 0,
2025-08-14T21:17:20.1387621Z         >>> #         grid = [(1, 1, 1)], kwargs = {
2025-08-14T21:17:20.1388007Z         >>> #             'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like,
2025-08-14T21:17:20.1388413Z         >>> #             'n_elements': 3, 'BLOCK_SIZE': 16
2025-08-14T21:17:20.1388737Z         >>> #         })
2025-08-14T21:17:20.1389142Z         >>> #     return empty_like
2025-08-14T21:17:20.1389357Z 
2025-08-14T21:17:20.1389440Z     
2025-08-14T21:17:20.1389816Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.1390190Z 
2025-08-14T21:17:20.2233344Z msg = Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286.
2025-08-14T21:17:20.2234298Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2234719Z 
2025-08-14T21:17:20.2235001Z Test if two objects are equal, and print an error message if test fails.
2025-08-14T21:17:20.2235450Z 
2025-08-14T21:17:20.2235707Z The test is performed with ``actual == desired``.
2025-08-14T21:17:20.2235976Z 
2025-08-14T21:17:20.2236086Z Parameters
2025-08-14T21:17:20.2236369Z ----------
2025-08-14T21:17:20.2236656Z test_string : str
2025-08-14T21:17:20.2236937Z     The message supplied to AssertionError.
2025-08-14T21:17:20.2237313Z actual : object
2025-08-14T21:17:20.2237625Z     The object to test for equality against `desired`.
2025-08-14T21:17:20.2238008Z desired : object
2025-08-14T21:17:20.2238284Z     The expected result.
2025-08-14T21:17:20.2238470Z 
2025-08-14T21:17:20.2238556Z Examples
2025-08-14T21:17:20.2238802Z --------
2025-08-14T21:17:20.2239120Z >>> np.testing.print_assert_equal(
2025-08-14T21:17:20.2239568Z ...     "Test XYZ of func xyz", [0, 1], [0, 1]
2025-08-14T21:17:20.2239935Z ... )  # doctest: +SKIP
2025-08-14T21:17:20.2240521Z >>> np.testing.print_assert_equal(
2025-08-14T21:17:20.2240848Z ...     "Test XYZ of func xyz", [0, 1], [0, 2]
2025-08-14T21:17:20.2241241Z ... )  # doctest: +SKIP
2025-08-14T21:17:20.2241509Z Traceback (most recent call last):
2025-08-14T21:17:20.2241800Z ...
2025-08-14T21:17:20.2242102Z AssertionError: Test XYZ of func xyz failed
2025-08-14T21:17:20.2242429Z ACTUAL:
2025-08-14T21:17:20.2242620Z [0, 1]
2025-08-14T21:17:20.2242884Z DESIRED:
2025-08-14T21:17:20.2243091Z [0, 2]
2025-08-14T21:17:20.2243202Z 
2025-08-14T21:17:20.2243212Z 
2025-08-14T21:17:20.2243485Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2244039Z 
2025-08-14T21:17:20.2244963Z msg = Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331.
2025-08-14T21:17:20.2246398Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2246798Z 
2025-08-14T21:17:20.2247016Z Raises an AssertionError if two items are not equal up to desired
2025-08-14T21:17:20.2247434Z precision.
2025-08-14T21:17:20.2247562Z 
2025-08-14T21:17:20.2247761Z .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:20.2248224Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:20.2248716Z           instead of this function for more consistent floating point
2025-08-14T21:17:20.2249117Z           comparisons.
2025-08-14T21:17:20.2249274Z 
2025-08-14T21:17:20.2249493Z The test verifies that the elements of `actual` and `desired` satisfy.
2025-08-14T21:17:20.2249836Z 
2025-08-14T21:17:20.2250010Z     ``abs(desired-actual) < float64(1.5 * 10**(-decimal))``
2025-08-14T21:17:20.2250394Z 
2025-08-14T21:17:20.2250627Z That is a looser test than originally documented, but agrees with what the
2025-08-14T21:17:20.2251221Z actual implementation in `assert_array_almost_equal` did up to rounding
2025-08-14T21:17:20.2251804Z vagaries. An exception is raised at conflicting values. For ndarrays this
2025-08-14T21:17:20.2252293Z delegates to assert_array_almost_equal
2025-08-14T21:17:20.2252512Z 
2025-08-14T21:17:20.2252612Z Parameters
2025-08-14T21:17:20.2252816Z ----------
2025-08-14T21:17:20.2253043Z actual : array_like
2025-08-14T21:17:20.2253294Z     The object to check.
2025-08-14T21:17:20.2253559Z desired : array_like
2025-08-14T21:17:20.2253805Z     The expected object.
2025-08-14T21:17:20.2254072Z decimal : int, optional
2025-08-14T21:17:20.2254505Z     Desired precision, default is 7.
2025-08-14T21:17:20.2254817Z err_msg : str, optional
2025-08-14T21:17:20.2255135Z     The error message to be printed in case of failure.
2025-08-14T21:17:20.2255510Z verbose : bool, optional
2025-08-14T21:17:20.2255878Z     If True, the conflicting values are appended to the error message.
2025-08-14T21:17:20.2256214Z 
2025-08-14T21:17:20.2256295Z Raises
2025-08-14T21:17:20.2256498Z ------
2025-08-14T21:17:20.2256700Z AssertionError
2025-08-14T21:17:20.2257042Z   If actual and desired are not equal up to specified precision.
2025-08-14T21:17:20.2257348Z 
2025-08-14T21:17:20.2257441Z See Also
2025-08-14T21:17:20.2257638Z --------
2025-08-14T21:17:20.2257994Z assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:20.2258481Z                  relative and/or absolute precision.
2025-08-14T21:17:20.2258933Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:20.2259256Z 
2025-08-14T21:17:20.2259340Z Examples
2025-08-14T21:17:20.2259550Z --------
2025-08-14T21:17:20.2259837Z >>> from torch._numpy.testing import assert_almost_equal
2025-08-14T21:17:20.2260235Z >>> assert_almost_equal(2.3333333333333, 2.33333334)
2025-08-14T21:17:20.2260655Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
2025-08-14T21:17:20.2261057Z Traceback (most recent call last):
2025-08-14T21:17:20.2261340Z     ...
2025-08-14T21:17:20.2261555Z AssertionError:
2025-08-14T21:17:20.2261826Z Arrays are not almost equal to 10 decimals
2025-08-14T21:17:20.2262244Z  ACTUAL: 2.3333333333333
2025-08-14T21:17:20.2262494Z  DESIRED: 2.33333334
2025-08-14T21:17:20.2262661Z 
2025-08-14T21:17:20.2262765Z >>> assert_almost_equal(
2025-08-14T21:17:20.2263141Z ...     np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9
2025-08-14T21:17:20.2263536Z ... )
2025-08-14T21:17:20.2263772Z Traceback (most recent call last):
2025-08-14T21:17:20.2264070Z     ...
2025-08-14T21:17:20.2264272Z AssertionError:
2025-08-14T21:17:20.2264544Z Arrays are not almost equal to 9 decimals
2025-08-14T21:17:20.2264863Z <BLANKLINE>
2025-08-14T21:17:20.2265086Z Mismatched elements: 1 / 2 (50%)
2025-08-14T21:17:20.2265415Z Max absolute difference: 6.666699636781459e-09
2025-08-14T21:17:20.2265800Z Max relative difference: 2.8571569790287484e-09
2025-08-14T21:17:20.2266172Z  x: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-08-14T21:17:20.2266562Z  y: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-08-14T21:17:20.2266822Z 
2025-08-14T21:17:20.2266830Z 
2025-08-14T21:17:20.2267082Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2267452Z 
2025-08-14T21:17:20.2268039Z msg = Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457.
2025-08-14T21:17:20.2268972Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2269364Z 
2025-08-14T21:17:20.2269595Z Raises an AssertionError if two items are not equal up to significant
2025-08-14T21:17:20.2270032Z digits.
2025-08-14T21:17:20.2270150Z 
2025-08-14T21:17:20.2270347Z .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:20.2270809Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:20.2271308Z           instead of this function for more consistent floating point
2025-08-14T21:17:20.2271827Z           comparisons.
2025-08-14T21:17:20.2271986Z 
2025-08-14T21:17:20.2272193Z Given two numbers, check that they are approximately equal.
2025-08-14T21:17:20.2272712Z Approximately equal is defined as the number of significant digits
2025-08-14T21:17:20.2273146Z that agree.
2025-08-14T21:17:20.2273273Z 
2025-08-14T21:17:20.2273381Z Parameters
2025-08-14T21:17:20.2273592Z ----------
2025-08-14T21:17:20.2273822Z actual : scalar
2025-08-14T21:17:20.2274067Z     The object to check.
2025-08-14T21:17:20.2274318Z desired : scalar
2025-08-14T21:17:20.2274566Z     The expected object.
2025-08-14T21:17:20.2274941Z significant : int, optional
2025-08-14T21:17:20.2275234Z     Desired precision, default is 7.
2025-08-14T21:17:20.2275554Z err_msg : str, optional
2025-08-14T21:17:20.2275876Z     The error message to be printed in case of failure.
2025-08-14T21:17:20.2276234Z verbose : bool, optional
2025-08-14T21:17:20.2276615Z     If True, the conflicting values are appended to the error message.
2025-08-14T21:17:20.2276947Z 
2025-08-14T21:17:20.2277027Z Raises
2025-08-14T21:17:20.2277239Z ------
2025-08-14T21:17:20.2277439Z AssertionError
2025-08-14T21:17:20.2277775Z   If actual and desired are not equal up to specified precision.
2025-08-14T21:17:20.2278081Z 
2025-08-14T21:17:20.2278175Z See Also
2025-08-14T21:17:20.2278367Z --------
2025-08-14T21:17:20.2278725Z assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:20.2279219Z                  relative and/or absolute precision.
2025-08-14T21:17:20.2279671Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:20.2280009Z 
2025-08-14T21:17:20.2280092Z Examples
2025-08-14T21:17:20.2280299Z --------
2025-08-14T21:17:20.2280527Z >>> np.testing.assert_approx_equal(
2025-08-14T21:17:20.2280853Z ...     0.12345677777777e-20, 0.1234567e-20
2025-08-14T21:17:20.2281167Z ... )  # doctest: +SKIP
2025-08-14T21:17:20.2281446Z >>> np.testing.assert_approx_equal(
2025-08-14T21:17:20.2281739Z ...     0.12345670e-20,
2025-08-14T21:17:20.2282006Z ...     0.12345671e-20,  # doctest: +SKIP
2025-08-14T21:17:20.2282386Z ...     significant=8,
2025-08-14T21:17:20.2282617Z ... )
2025-08-14T21:17:20.2282856Z >>> np.testing.assert_approx_equal(
2025-08-14T21:17:20.2283164Z ...     0.12345670e-20,
2025-08-14T21:17:20.2283421Z ...     0.12345672e-20,  # doctest: +SKIP
2025-08-14T21:17:20.2283741Z ...     significant=8,
2025-08-14T21:17:20.2283990Z ... )
2025-08-14T21:17:20.2284209Z Traceback (most recent call last):
2025-08-14T21:17:20.2284503Z     ...
2025-08-14T21:17:20.2284716Z AssertionError:
2025-08-14T21:17:20.2284984Z Items are not equal to 8 significant digits:
2025-08-14T21:17:20.2285320Z  ACTUAL: 1.234567e-21
2025-08-14T21:17:20.2285572Z  DESIRED: 1.2345672e-21
2025-08-14T21:17:20.2285728Z 
2025-08-14T21:17:20.2285900Z the evaluated condition that raises the exception is
2025-08-14T21:17:20.2286170Z 
2025-08-14T21:17:20.2286362Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1)
2025-08-14T21:17:20.2286761Z True
2025-08-14T21:17:20.2286870Z 
2025-08-14T21:17:20.2286878Z 
2025-08-14T21:17:20.2287143Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2287514Z 
2025-08-14T21:17:20.2288140Z msg = Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744.
2025-08-14T21:17:20.2289077Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2289459Z 
2025-08-14T21:17:20.2289691Z Raises an AssertionError if two array_like objects are not equal.
2025-08-14T21:17:20.2290011Z 
2025-08-14T21:17:20.2290217Z Given two array_like objects, check that the shape is equal and all
2025-08-14T21:17:20.2290770Z elements of these objects are equal (but see the Notes for the special
2025-08-14T21:17:20.2291316Z handling of a scalar). An exception is raised at shape mismatch or
2025-08-14T21:17:20.2291847Z conflicting values. In contrast to the standard usage in numpy, NaNs
2025-08-14T21:17:20.2292412Z are compared like numbers, no assertion is raised if both objects have
2025-08-14T21:17:20.2292867Z NaNs in the same positions.
2025-08-14T21:17:20.2293047Z 
2025-08-14T21:17:20.2293284Z The usual caution for verifying equality with floating point numbers is
2025-08-14T21:17:20.2293707Z advised.
2025-08-14T21:17:20.2293836Z 
2025-08-14T21:17:20.2293926Z Parameters
2025-08-14T21:17:20.2294138Z ----------
2025-08-14T21:17:20.2294341Z x : array_like
2025-08-14T21:17:20.2294583Z     The actual object to check.
2025-08-14T21:17:20.2294863Z y : array_like
2025-08-14T21:17:20.2295172Z     The desired, expected object.
2025-08-14T21:17:20.2295479Z err_msg : str, optional
2025-08-14T21:17:20.2295796Z     The error message to be printed in case of failure.
2025-08-14T21:17:20.2296154Z verbose : bool, optional
2025-08-14T21:17:20.2296543Z     If True, the conflicting values are appended to the error message.
2025-08-14T21:17:20.2296968Z strict : bool, optional
2025-08-14T21:17:20.2297340Z     If True, raise an AssertionError when either the shape or the data
2025-08-14T21:17:20.2297831Z     type of the array_like objects does not match. The special
2025-08-14T21:17:20.2298330Z     handling for scalars mentioned in the Notes section is disabled.
2025-08-14T21:17:20.2298649Z 
2025-08-14T21:17:20.2298742Z Raises
2025-08-14T21:17:20.2298936Z ------
2025-08-14T21:17:20.2299148Z AssertionError
2025-08-14T21:17:20.2299423Z     If actual and desired objects are not equal.
2025-08-14T21:17:20.2299675Z 
2025-08-14T21:17:20.2299758Z See Also
2025-08-14T21:17:20.2299988Z --------
2025-08-14T21:17:20.2300498Z assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:20.2301068Z                  relative and/or absolute precision.
2025-08-14T21:17:20.2301575Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:20.2301931Z 
2025-08-14T21:17:20.2302015Z Notes
2025-08-14T21:17:20.2312210Z -----
2025-08-14T21:17:20.2312655Z When one of `x` and `y` is a scalar and the other is array_like, the
2025-08-14T21:17:20.2313407Z function checks that each element of the array_like object is equal to
2025-08-14T21:17:20.2313992Z the scalar. This behaviour can be disabled with the `strict` parameter.
2025-08-14T21:17:20.2314338Z 
2025-08-14T21:17:20.2314444Z Examples
2025-08-14T21:17:20.2314645Z --------
2025-08-14T21:17:20.2314908Z The first assert does not raise an exception:
2025-08-14T21:17:20.2315153Z 
2025-08-14T21:17:20.2315283Z >>> np.testing.assert_array_equal(
2025-08-14T21:17:20.2315635Z ...     [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan]
2025-08-14T21:17:20.2315979Z ... )
2025-08-14T21:17:20.2316094Z 
2025-08-14T21:17:20.2316337Z Use `assert_allclose` or one of the nulp (number of floating point values)
2025-08-14T21:17:20.2316790Z functions for these cases instead:
2025-08-14T21:17:20.2317012Z 
2025-08-14T21:17:20.2317124Z >>> np.testing.assert_allclose(
2025-08-14T21:17:20.2317526Z ...     [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0
2025-08-14T21:17:20.2317938Z ... )
2025-08-14T21:17:20.2318053Z 
2025-08-14T21:17:20.2318261Z As mentioned in the Notes section, `assert_array_equal` has special
2025-08-14T21:17:20.2318816Z handling for scalars. Here the test checks that each value in `x` is 3:
2025-08-14T21:17:20.2319158Z 
2025-08-14T21:17:20.2319279Z >>> x = np.full((2, 5), fill_value=3)
2025-08-14T21:17:20.2319599Z >>> np.testing.assert_array_equal(x, 3)
2025-08-14T21:17:20.2319831Z 
2025-08-14T21:17:20.2320046Z Use `strict` to raise an AssertionError when comparing a scalar with an
2025-08-14T21:17:20.2320477Z array:
2025-08-14T21:17:20.2320592Z 
2025-08-14T21:17:20.2320758Z >>> np.testing.assert_array_equal(x, 3, strict=True)
2025-08-14T21:17:20.2321127Z Traceback (most recent call last):
2025-08-14T21:17:20.2321425Z     ...
2025-08-14T21:17:20.2321640Z AssertionError:
2025-08-14T21:17:20.2321869Z Arrays are not equal
2025-08-14T21:17:20.2322116Z <BLANKLINE>
2025-08-14T21:17:20.2322344Z (shapes (2, 5), () mismatch)
2025-08-14T21:17:20.2322623Z  x: torch.ndarray([[3, 3, 3, 3, 3],
2025-08-14T21:17:20.2322930Z         [3, 3, 3, 3, 3]])
2025-08-14T21:17:20.2323231Z  y: torch.ndarray(3)
2025-08-14T21:17:20.2323385Z 
2025-08-14T21:17:20.2323597Z The `strict` parameter also ensures that the array data types match:
2025-08-14T21:17:20.2323941Z 
2025-08-14T21:17:20.2324040Z >>> x = np.array([2, 2, 2])
2025-08-14T21:17:20.2324349Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32)
2025-08-14T21:17:20.2324752Z >>> np.testing.assert_array_equal(x, y, strict=True)
2025-08-14T21:17:20.2325225Z Traceback (most recent call last):
2025-08-14T21:17:20.2325530Z     ...
2025-08-14T21:17:20.2325752Z AssertionError:
2025-08-14T21:17:20.2325986Z Arrays are not equal
2025-08-14T21:17:20.2326239Z <BLANKLINE>
2025-08-14T21:17:20.2326515Z (dtypes dtype("int64"), dtype("float32") mismatch)
2025-08-14T21:17:20.2326870Z  x: torch.ndarray([2, 2, 2])
2025-08-14T21:17:20.2327170Z  y: torch.ndarray([2., 2., 2.])
2025-08-14T21:17:20.2327356Z 
2025-08-14T21:17:20.2327622Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2327998Z 
2025-08-14T21:17:20.2328599Z msg = Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851.
2025-08-14T21:17:20.2329552Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2329944Z 
2025-08-14T21:17:20.2330158Z Raises an AssertionError if two objects are not equal up to desired
2025-08-14T21:17:20.2330587Z precision.
2025-08-14T21:17:20.2330716Z 
2025-08-14T21:17:20.2330901Z .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:20.2331374Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:20.2331867Z           instead of this function for more consistent floating point
2025-08-14T21:17:20.2332274Z           comparisons.
2025-08-14T21:17:20.2332431Z 
2025-08-14T21:17:20.2332671Z The test verifies identical shapes and that the elements of ``actual`` and
2025-08-14T21:17:20.2333196Z ``desired`` satisfy.
2025-08-14T21:17:20.2333351Z 
2025-08-14T21:17:20.2333494Z     ``abs(desired-actual) < 1.5 * 10**(-decimal)``
2025-08-14T21:17:20.2333735Z 
2025-08-14T21:17:20.2333974Z That is a looser test than originally documented, but agrees with what the
2025-08-14T21:17:20.2334556Z actual implementation did up to rounding vagaries. An exception is raised
2025-08-14T21:17:20.2335162Z at shape mismatch or conflicting values. In contrast to the standard usage
2025-08-14T21:17:20.2335747Z in numpy, NaNs are compared like numbers, no assertion is raised if both
2025-08-14T21:17:20.2336207Z objects have NaNs in the same positions.
2025-08-14T21:17:20.2336445Z 
2025-08-14T21:17:20.2336538Z Parameters
2025-08-14T21:17:20.2336755Z ----------
2025-08-14T21:17:20.2336960Z x : array_like
2025-08-14T21:17:20.2337208Z     The actual object to check.
2025-08-14T21:17:20.2337494Z y : array_like
2025-08-14T21:17:20.2337752Z     The desired, expected object.
2025-08-14T21:17:20.2338048Z decimal : int, optional
2025-08-14T21:17:20.2338334Z     Desired precision, default is 6.
2025-08-14T21:17:20.2338656Z err_msg : str, optional
2025-08-14T21:17:20.2338965Z   The error message to be printed in case of failure.
2025-08-14T21:17:20.2339344Z verbose : bool, optional
2025-08-14T21:17:20.2339725Z     If True, the conflicting values are appended to the error message.
2025-08-14T21:17:20.2340044Z 
2025-08-14T21:17:20.2340129Z Raises
2025-08-14T21:17:20.2340337Z ------
2025-08-14T21:17:20.2340562Z AssertionError
2025-08-14T21:17:20.2340891Z     If actual and desired are not equal up to specified precision.
2025-08-14T21:17:20.2341212Z 
2025-08-14T21:17:20.2341299Z See Also
2025-08-14T21:17:20.2341509Z --------
2025-08-14T21:17:20.2341860Z assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:20.2342355Z                  relative and/or absolute precision.
2025-08-14T21:17:20.2342816Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:20.2343143Z 
2025-08-14T21:17:20.2343243Z Examples
2025-08-14T21:17:20.2343446Z --------
2025-08-14T21:17:20.2343708Z the first assert does not raise an exception
2025-08-14T21:17:20.2343947Z 
2025-08-14T21:17:20.2344214Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan])
2025-08-14T21:17:20.2344588Z 
2025-08-14T21:17:20.2344711Z >>> np.testing.assert_array_almost_equal(
2025-08-14T21:17:20.2345109Z ...     [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5
2025-08-14T21:17:20.2345538Z ... )
2025-08-14T21:17:20.2345782Z Traceback (most recent call last):
2025-08-14T21:17:20.2346076Z     ...
2025-08-14T21:17:20.2346298Z AssertionError:
2025-08-14T21:17:20.2346573Z Arrays are not almost equal to 5 decimals
2025-08-14T21:17:20.2346889Z <BLANKLINE>
2025-08-14T21:17:20.2347134Z Mismatched elements: 1 / 3 (33.3%)
2025-08-14T21:17:20.2347476Z Max absolute difference: 5.999999999994898e-05
2025-08-14T21:17:20.2347841Z Max relative difference: 2.5713661239633743e-05
2025-08-14T21:17:20.2348260Z  x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-08-14T21:17:20.2348707Z  y: torch.ndarray([1.0000, 2.3334,    nan], dtype=float64)
2025-08-14T21:17:20.2348978Z 
2025-08-14T21:17:20.2349115Z >>> np.testing.assert_array_almost_equal(
2025-08-14T21:17:20.2349473Z ...     [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5
2025-08-14T21:17:20.2349814Z ... )
2025-08-14T21:17:20.2350054Z Traceback (most recent call last):
2025-08-14T21:17:20.2350337Z     ...
2025-08-14T21:17:20.2350560Z AssertionError:
2025-08-14T21:17:20.2350830Z Arrays are not almost equal to 5 decimals
2025-08-14T21:17:20.2351139Z <BLANKLINE>
2025-08-14T21:17:20.2351378Z x and y nan location mismatch:
2025-08-14T21:17:20.2351855Z  x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-08-14T21:17:20.2352280Z  y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64)
2025-08-14T21:17:20.2352563Z 
2025-08-14T21:17:20.2352567Z 
2025-08-14T21:17:20.2352821Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2353280Z 
2025-08-14T21:17:20.2353906Z msg = Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848.
2025-08-14T21:17:20.2354874Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.2355486Z Context manager that resets warning registry for catching warnings
2025-08-14T21:17:20.2355814Z 
2025-08-14T21:17:20.2356059Z     Warnings can be slippery, because, whenever a warning is triggered, Python
2025-08-14T21:17:20.2356660Z     adds a ``__warningregistry__`` member to the *calling* module.  This makes
2025-08-14T21:17:20.2357249Z     it impossible to retrigger the warning in this module, whatever you put in
2025-08-14T21:17:20.2357846Z     the warnings filters.  This context manager accepts a sequence of `modules`
2025-08-14T21:17:20.2358350Z     as a keyword argument to its constructor and:
2025-08-14T21:17:20.2358617Z 
2025-08-14T21:17:20.2358844Z     * stores and removes any ``__warningregistry__`` entries in given `modules`
2025-08-14T21:17:20.2359285Z       on entry;
2025-08-14T21:17:20.2359605Z     * resets ``__warningregistry__`` to its previous state on exit.
2025-08-14T21:17:20.2359917Z 
2025-08-14T21:17:20.2360141Z     This makes it possible to trigger any warning afresh inside the context
2025-08-14T21:17:20.2360671Z     manager without disturbing the state of warnings outside.
2025-08-14T21:17:20.2360969Z 
2025-08-14T21:17:20.2361222Z     For compatibility with Python 3.0, please consider all arguments to be
2025-08-14T21:17:20.2361664Z     keyword-only.
2025-08-14T21:17:20.2361821Z 
2025-08-14T21:17:20.2361911Z     Parameters
2025-08-14T21:17:20.2362144Z     ----------
2025-08-14T21:17:20.2362376Z     record : bool, optional
2025-08-14T21:17:20.2362752Z         Specifies whether warnings should be captured by a custom
2025-08-14T21:17:20.2363297Z         implementation of ``warnings.showwarning()`` and be appended to a list
2025-08-14T21:17:20.2363859Z         returned by the context manager. Otherwise None is returned by the
2025-08-14T21:17:20.2364424Z         context manager. The objects appended to the list are arguments whose
2025-08-14T21:17:20.2364948Z         attributes mirror the arguments to ``showwarning()``.
2025-08-14T21:17:20.2365352Z     modules : sequence, optional
2025-08-14T21:17:20.2365765Z         Sequence of modules for which to reset warnings registry on entry and
2025-08-14T21:17:20.2366378Z         restore on exit. To work correctly, all 'ignore' filters should
2025-08-14T21:17:20.2366809Z         filter by one of these modules.
2025-08-14T21:17:20.2367025Z 
2025-08-14T21:17:20.2367110Z     Examples
2025-08-14T21:17:20.2367335Z     --------
2025-08-14T21:17:20.2367572Z     >>> import warnings
2025-08-14T21:17:20.2367917Z     >>> with np.testing.clear_and_catch_warnings(  # doctest: +SKIP
2025-08-14T21:17:20.2368347Z     ...     modules=[np.core.fromnumeric]
2025-08-14T21:17:20.2368670Z     ... ):
2025-08-14T21:17:20.2368926Z     ...     warnings.simplefilter("always")
2025-08-14T21:17:20.2369370Z     ...     warnings.filterwarnings("ignore", module="np.core.fromnumeric")
2025-08-14T21:17:20.2369900Z     ...     # do something that raises a warning but ignore those in
2025-08-14T21:17:20.2370297Z     ...     # np.core.fromnumeric
2025-08-14T21:17:20.2370569Z     
2025-08-14T21:17:20.2370942Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.2371309Z 
2025-08-14T21:17:20.6176435Z msg = Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354.
2025-08-14T21:17:20.6177398Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.6178001Z Applies a 1D convolution over a quantized input signal composed of
2025-08-14T21:17:20.6178437Z     several quantized input planes.
2025-08-14T21:17:20.6178664Z 
2025-08-14T21:17:20.6179110Z     For details on input arguments, parameters, and implementation see
2025-08-14T21:17:20.6179585Z     :class:`~torch.nn.Conv1d`.
2025-08-14T21:17:20.6179810Z 
2025-08-14T21:17:20.6179931Z     .. note::
2025-08-14T21:17:20.6180262Z         Only `zeros` is supported for the :attr:`padding_mode` argument.
2025-08-14T21:17:20.6180592Z 
2025-08-14T21:17:20.6180680Z     .. note::
2025-08-14T21:17:20.6180996Z         Only `torch.quint8` is supported for the input data type.
2025-08-14T21:17:20.6181289Z 
2025-08-14T21:17:20.6181301Z 
2025-08-14T21:17:20.6181405Z     Attributes:
2025-08-14T21:17:20.6181755Z         weight (Tensor):     packed tensor derived from the learnable weight
2025-08-14T21:17:20.6182195Z                              parameter.
2025-08-14T21:17:20.6182561Z         scale (Tensor):      scalar for the output scale
2025-08-14T21:17:20.6182975Z         zero_point (Tensor): scalar for the output zero point
2025-08-14T21:17:20.6183264Z 
2025-08-14T21:17:20.6183418Z     See :class:`~torch.nn.Conv1d` for other attributes.
2025-08-14T21:17:20.6183686Z 
2025-08-14T21:17:20.6183792Z     Examples::
2025-08-14T21:17:20.6183927Z 
2025-08-14T21:17:20.6184085Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE)
2025-08-14T21:17:20.6184501Z         >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
2025-08-14T21:17:20.6184851Z         >>> input = torch.randn(20, 16, 100)
2025-08-14T21:17:20.6185191Z         >>> # quantize input to quint8
2025-08-14T21:17:20.6185510Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:20.6185908Z         >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0,
2025-08-14T21:17:20.6186376Z         ...                                     dtype=torch.quint8)
2025-08-14T21:17:20.6186724Z         >>> output = m(q_input)
2025-08-14T21:17:20.6186910Z 
2025-08-14T21:17:20.6187000Z     
2025-08-14T21:17:20.6187359Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.6187740Z 
2025-08-14T21:17:20.6409311Z msg = Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12.
2025-08-14T21:17:20.6410248Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.6410765Z A quantized long short-term memory (LSTM).
2025-08-14T21:17:20.6410996Z 
2025-08-14T21:17:20.6411274Z     For the description and the argument types, please, refer to :class:`~torch.nn.LSTM`
2025-08-14T21:17:20.6411682Z 
2025-08-14T21:17:20.6411774Z     Attributes:
2025-08-14T21:17:20.6412280Z         layers : instances of the `_LSTMLayer`
2025-08-14T21:17:20.6412513Z 
2025-08-14T21:17:20.6412605Z     .. note::
2025-08-14T21:17:20.6412958Z         To access the weights and biases, you need to access them per layer.
2025-08-14T21:17:20.6413495Z         See examples in :class:`~torch.ao.nn.quantizable.LSTM`
2025-08-14T21:17:20.6413783Z 
2025-08-14T21:17:20.6413887Z     Examples::
2025-08-14T21:17:20.6414121Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:20.6414423Z         >>> custom_module_config = {
2025-08-14T21:17:20.6414773Z         ...     'float_to_observed_custom_module_class': {
2025-08-14T21:17:20.6415143Z         ...         nn.LSTM: nn.quantizable.LSTM,
2025-08-14T21:17:20.6415470Z         ...     },
2025-08-14T21:17:20.6415759Z         ...     'observed_to_quantized_custom_module_class': {
2025-08-14T21:17:20.6416169Z         ...         nn.quantizable.LSTM: nn.quantized.LSTM,
2025-08-14T21:17:20.6416501Z         ...     }
2025-08-14T21:17:20.6416732Z         ... }
2025-08-14T21:17:20.6417087Z         >>> tq.prepare(model, prepare_custom_module_class=custom_module_config)
2025-08-14T21:17:20.6417629Z         >>> tq.convert(model, convert_custom_module_class=custom_module_config)
2025-08-14T21:17:20.6418048Z     
2025-08-14T21:17:20.6418418Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.6418787Z 
2025-08-14T21:17:20.7173188Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16.
2025-08-14T21:17:20.7174609Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.7175008Z 
2025-08-14T21:17:20.7175271Z The Activation sparsifier class aims to sparsify/prune activations in a neural
2025-08-14T21:17:20.7175883Z network. The idea is to attach the sparsifier to a layer (or layers) and it
2025-08-14T21:17:20.7176489Z zeroes out the activations based on the mask_fn (or sparsification function)
2025-08-14T21:17:20.7176942Z input by the user.
2025-08-14T21:17:20.7177318Z The mask_fn is applied once all the inputs are aggregated and reduced i.e.
2025-08-14T21:17:20.7177819Z mask = mask_fn(reduce_fn(aggregate_fn(activations)))
2025-08-14T21:17:20.7178084Z 
2025-08-14T21:17:20.7178181Z Note::
2025-08-14T21:17:20.7178630Z     The sparsification mask is computed on the input **before it goes through the attached layer**.
2025-08-14T21:17:20.7179084Z 
2025-08-14T21:17:20.7179165Z Args:
2025-08-14T21:17:20.7179381Z     model (nn.Module):
2025-08-14T21:17:20.7179756Z         The model whose layers will be sparsified. The layers that needs to be
2025-08-14T21:17:20.7180346Z         sparsified should be added separately using the register_layer() function
2025-08-14T21:17:20.7180826Z     aggregate_fn (Optional, Callable):
2025-08-14T21:17:20.7181294Z         default aggregate_fn that is used if not specified while registering the layer.
2025-08-14T21:17:20.7181942Z         specifies how inputs should be aggregated over time.
2025-08-14T21:17:20.7182509Z         The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor.
2025-08-14T21:17:20.7183002Z         Example
2025-08-14T21:17:20.7183311Z             def add_agg_fn(tensor1, tensor2):  return tensor1 + tensor2
2025-08-14T21:17:20.7183725Z             reduce_fn (Optional, Callable):
2025-08-14T21:17:20.7184202Z                 default reduce_fn that is used if not specified while registering the layer.
2025-08-14T21:17:20.7184856Z                 reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after
2025-08-14T21:17:20.7185339Z                 calling agg_fn() on all inputs.
2025-08-14T21:17:20.7185663Z                 Example
2025-08-14T21:17:20.7186020Z             def mean_reduce_fn(agg_tensor):    return agg_tensor.mean(dim=0)
2025-08-14T21:17:20.7186441Z             mask_fn (Optional, Callable):
2025-08-14T21:17:20.7187109Z                 default mask_fn that is used to create the sparsification mask using the tensor obtained after
2025-08-14T21:17:20.7187801Z                 calling the reduce_fn(). This is used by default if a custom one is passed in the
2025-08-14T21:17:20.7188281Z                 register_layer().
2025-08-14T21:17:20.7188817Z                 Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config
2025-08-14T21:17:20.7189388Z                 arguments.
2025-08-14T21:17:20.7189679Z             features (Optional, list):
2025-08-14T21:17:20.7190017Z                 default selected features to sparsify.
2025-08-14T21:17:20.7190533Z                 If this is non-empty, then the mask_fn will be applied for each feature of the input.
2025-08-14T21:17:20.7191023Z                 For example,
2025-08-14T21:17:20.7191516Z             mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features]
2025-08-14T21:17:20.7192012Z             feature_dim (Optional, int):
2025-08-14T21:17:20.7192524Z                 default dimension of input features. Again, features along this dim will be chosen
2025-08-14T21:17:20.7193033Z                 for sparsification.
2025-08-14T21:17:20.7193337Z             sparse_config (Dict):
2025-08-14T21:17:20.7193766Z                 Default configuration for the mask_fn. This config will be passed
2025-08-14T21:17:20.7194219Z                 with the mask_fn()
2025-08-14T21:17:20.7194414Z 
2025-08-14T21:17:20.7194574Z Example:
2025-08-14T21:17:20.7194798Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:20.7195075Z     >>> model = SomeModel()
2025-08-14T21:17:20.7195493Z     >>> act_sparsifier = ActivationSparsifier(...)  # init activation sparsifier
2025-08-14T21:17:20.7195975Z     >>> # Initialize aggregate_fn
2025-08-14T21:17:20.7196280Z     >>> def agg_fn(x, y):
2025-08-14T21:17:20.7196547Z     >>>     return x + y
2025-08-14T21:17:20.7196785Z     >>>
2025-08-14T21:17:20.7197012Z     >>> # Initialize reduce_fn
2025-08-14T21:17:20.7197301Z     >>> def reduce_fn(x):
2025-08-14T21:17:20.7197567Z     >>>     return torch.mean(x, dim=0)
2025-08-14T21:17:20.7197870Z     >>>
2025-08-14T21:17:20.7198087Z     >>> # Initialize mask_fn
2025-08-14T21:17:20.7198354Z     >>> def mask_fn(data):
2025-08-14T21:17:20.7198675Z     >>>     return torch.eye(data.shape).to(data.device)
2025-08-14T21:17:20.7199023Z     >>>
2025-08-14T21:17:20.7199214Z     >>>
2025-08-14T21:17:20.7199455Z     >>> act_sparsifier.register_layer(
2025-08-14T21:17:20.7199789Z     ...     model.some_layer,
2025-08-14T21:17:20.7200067Z     ...     aggregate_fn=agg_fn,
2025-08-14T21:17:20.7200406Z     ...     reduce_fn=reduce_fn,
2025-08-14T21:17:20.7200742Z     ...     mask_fn=mask_fn,
2025-08-14T21:17:20.7200996Z     ... )
2025-08-14T21:17:20.7201202Z     >>>
2025-08-14T21:17:20.7201424Z     >>> # start training process
2025-08-14T21:17:20.7201775Z     >>> for _ in [...]:
2025-08-14T21:17:20.7202029Z     >>> # epoch starts
2025-08-14T21:17:20.7202367Z     >>> # model.forward(), compute_loss() and model.backwards()
2025-08-14T21:17:20.7202750Z     >>> # epoch ends
2025-08-14T21:17:20.7203001Z     >>>     act_sparsifier.step()
2025-08-14T21:17:20.7203307Z     >>> # end training process
2025-08-14T21:17:20.7203605Z     >>> sparsifier.squash_mask()
2025-08-14T21:17:20.7203803Z 
2025-08-14T21:17:20.7204056Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.7204442Z 
2025-08-14T21:17:20.7205294Z msg = Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91.
2025-08-14T21:17:20.7206507Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.7206886Z 
2025-08-14T21:17:20.7207105Z Abstract method that needs to be implemented by the child class.
2025-08-14T21:17:20.7207688Z The expected return type should is a dictionary of name to schedule_param value
2025-08-14T21:17:20.7208416Z The returned values will be updated in sparsifier when the scheduler step() function
2025-08-14T21:17:20.7208904Z is called.
2025-08-14T21:17:20.7209197Z 
2025-08-14T21:17:20.7209297Z Example:
2025-08-14T21:17:20.7209523Z     >>> def get_schedule_param(self):
2025-08-14T21:17:20.7209839Z     ...     new_param = {}
2025-08-14T21:17:20.7210174Z     ...     for name in self.sparsifier.data_groups.keys():
2025-08-14T21:17:20.7210543Z     ...         new_param[name] = (
2025-08-14T21:17:20.7210965Z     ...             self.sparsifier.data_groups[name][self.schedule_param] * 0.5
2025-08-14T21:17:20.7211379Z     ...         )
2025-08-14T21:17:20.7211611Z     ...     return new_param
2025-08-14T21:17:20.7211801Z 
2025-08-14T21:17:20.7212140Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param]
2025-08-14T21:17:20.7212698Z would be halved
2025-08-14T21:17:20.7212837Z 
2025-08-14T21:17:20.7213107Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.7213477Z 
2025-08-14T21:17:20.7542284Z msg = Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229.
2025-08-14T21:17:20.7543355Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.7543918Z Squashes the sparse masks into the appropriate tensors.
2025-08-14T21:17:20.7544201Z 
2025-08-14T21:17:20.7544625Z         If either the `params_to_keep` or `params_to_keep_per_layer` is set,
2025-08-14T21:17:20.7545136Z         the module will have a `sparse_params` dict attached to it.
2025-08-14T21:17:20.7545451Z 
2025-08-14T21:17:20.7545536Z         Args:
2025-08-14T21:17:20.7545859Z             params_to_keep: List of keys to save in the module or a dict
2025-08-14T21:17:20.7546334Z                             representing the modules and keys that will have
2025-08-14T21:17:20.7546745Z                             sparsity parameters saved
2025-08-14T21:17:20.7547222Z             params_to_keep_per_layer: Dict to specify the params that should be
2025-08-14T21:17:20.7547715Z                             saved for specific layers. The keys in the dict
2025-08-14T21:17:20.7548148Z                             should be the module fqn, while the values should
2025-08-14T21:17:20.7548575Z                             be a list of strings with the names of the variables
2025-08-14T21:17:20.7548989Z                             to save in the `sparse_params`
2025-08-14T21:17:20.7549230Z 
2025-08-14T21:17:20.7549330Z         Examples:
2025-08-14T21:17:20.7549611Z             >>> # xdoctest: +SKIP("locals are undefined")
2025-08-14T21:17:20.7549965Z             >>> # Don't save any sparse params
2025-08-14T21:17:20.7550313Z             >>> sparsifier.squash_mask()
2025-08-14T21:17:20.7550676Z             >>> hasattr(model.submodule1, "sparse_params")
2025-08-14T21:17:20.7551005Z             False
2025-08-14T21:17:20.7551152Z 
2025-08-14T21:17:20.7551276Z             >>> # Keep sparse params per layer
2025-08-14T21:17:20.7551697Z             >>> sparsifier.squash_mask(
2025-08-14T21:17:20.7552022Z             ...     params_to_keep_per_layer={
2025-08-14T21:17:20.7552381Z             ...         "submodule1.linear1": ("foo", "bar"),
2025-08-14T21:17:20.7552762Z             ...         "submodule2.linear42": ("baz",),
2025-08-14T21:17:20.7553092Z             ...     }
2025-08-14T21:17:20.7553316Z             ... )
2025-08-14T21:17:20.7553623Z             >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:20.7553998Z             {'foo': 42, 'bar': 24}
2025-08-14T21:17:20.7554342Z             >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:20.7554712Z             {'baz': 0.1}
2025-08-14T21:17:20.7554872Z 
2025-08-14T21:17:20.7555007Z             >>> # Keep sparse params for all layers
2025-08-14T21:17:20.7555415Z             >>> sparsifier.squash_mask(params_to_keep=("foo", "bar"))
2025-08-14T21:17:20.7555980Z             >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:20.7556355Z             {'foo': 42, 'bar': 24}
2025-08-14T21:17:20.7556713Z             >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:20.7557077Z             {'foo': 42, 'bar': 24}
2025-08-14T21:17:20.7557280Z 
2025-08-14T21:17:20.7557477Z             >>> # Keep some sparse params for all layers, and specific ones for
2025-08-14T21:17:20.7557896Z             >>> # some other layers
2025-08-14T21:17:20.7558205Z             >>> sparsifier.squash_mask(
2025-08-14T21:17:20.7558544Z             ...     params_to_keep=("foo", "bar"),
2025-08-14T21:17:20.7558971Z             ...     params_to_keep_per_layer={"submodule2.linear42": ("baz",)},
2025-08-14T21:17:20.7559362Z             ... )
2025-08-14T21:17:20.7559662Z             >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:20.7560035Z             {'foo': 42, 'bar': 24}
2025-08-14T21:17:20.7560395Z             >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:20.7560777Z             {'foo': 42, 'bar': 24, 'baz': 0.1}
2025-08-14T21:17:20.7561082Z         
2025-08-14T21:17:20.7561461Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.7561830Z 
2025-08-14T21:17:20.8508931Z msg = Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181.
2025-08-14T21:17:20.8510340Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.8510739Z 
2025-08-14T21:17:20.8510992Z Config object that specifies the supported data types passed as arguments to
2025-08-14T21:17:20.8511666Z quantize ops in the reference model spec, for input and output activations,
2025-08-14T21:17:20.8512114Z weights, and biases.
2025-08-14T21:17:20.8512285Z 
2025-08-14T21:17:20.8512441Z For example, consider the following reference model:
2025-08-14T21:17:20.8512728Z 
2025-08-14T21:17:20.8512892Z   quant1 - [dequant1 - fp32_linear - quant2] - dequant2
2025-08-14T21:17:20.8513160Z 
2025-08-14T21:17:20.8513385Z The pattern in the square brackets refers to the reference pattern of
2025-08-14T21:17:20.8513956Z statically quantized linear. Setting the input dtype as `torch.quint8`
2025-08-14T21:17:20.8514530Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument
2025-08-14T21:17:20.8515133Z to the first quantize op (quant1). Similarly, setting the output dtype as
2025-08-14T21:17:20.8515705Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to
2025-08-14T21:17:20.8516158Z the second quantize op (quant2).
2025-08-14T21:17:20.8516355Z 
2025-08-14T21:17:20.8516574Z Note that the dtype here does not refer to the interface dtypes of the
2025-08-14T21:17:20.8517125Z op. For example, the "input dtype" here is not the dtype of the input
2025-08-14T21:17:20.8517674Z tensor passed to the quantized linear op. Though it can still be the
2025-08-14T21:17:20.8518224Z same as the interface dtype, this is not always the case, e.g. the
2025-08-14T21:17:20.8518768Z interface dtype is fp32 in dynamic quantization but the "input dtype"
2025-08-14T21:17:20.8519325Z specified in the DTypeConfig would still be quint8. The semantics of
2025-08-14T21:17:20.8519860Z dtypes here are the same as the semantics of the dtypes specified in
2025-08-14T21:17:20.8520284Z the observers.
2025-08-14T21:17:20.8520423Z 
2025-08-14T21:17:20.8520644Z These dtypes are matched against the ones specified in the user's
2025-08-14T21:17:20.8521177Z QConfig. If there is a match, and the QConfig satisfies the constraints
2025-08-14T21:17:20.8521746Z specified in the DTypeConfig (if any), then we will quantize the given
2025-08-14T21:17:20.8522317Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and
2025-08-14T21:17:20.8522781Z the pattern will not be quantized.
2025-08-14T21:17:20.8522989Z 
2025-08-14T21:17:20.8523104Z Example usage::
2025-08-14T21:17:20.8523259Z 
2025-08-14T21:17:20.8523472Z     >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:20.8523792Z     >>> dtype_config1 = DTypeConfig(
2025-08-14T21:17:20.8524105Z     ...     input_dtype=torch.quint8,
2025-08-14T21:17:20.8524432Z     ...     output_dtype=torch.quint8,
2025-08-14T21:17:20.8524761Z     ...     weight_dtype=torch.qint8,
2025-08-14T21:17:20.8525075Z     ...     bias_dtype=torch.float)
2025-08-14T21:17:20.8525296Z 
2025-08-14T21:17:20.8525405Z     >>> dtype_config2 = DTypeConfig(
2025-08-14T21:17:20.8525754Z     ...     input_dtype=DTypeWithConstraints(
2025-08-14T21:17:20.8526100Z     ...         dtype=torch.quint8,
2025-08-14T21:17:20.8526402Z     ...         quant_min_lower_bound=0,
2025-08-14T21:17:20.8526732Z     ...         quant_max_upper_bound=255,
2025-08-14T21:17:20.8527042Z     ...     ),
2025-08-14T21:17:20.8527290Z     ...     output_dtype=DTypeWithConstraints(
2025-08-14T21:17:20.8527638Z     ...         dtype=torch.quint8,
2025-08-14T21:17:20.8527946Z     ...         quant_min_lower_bound=0,
2025-08-14T21:17:20.8528262Z     ...         quant_max_upper_bound=255,
2025-08-14T21:17:20.8528568Z     ...     ),
2025-08-14T21:17:20.8528831Z     ...     weight_dtype=DTypeWithConstraints(
2025-08-14T21:17:20.8529162Z     ...         dtype=torch.qint8,
2025-08-14T21:17:20.8529477Z     ...         quant_min_lower_bound=-128,
2025-08-14T21:17:20.8529808Z     ...         quant_max_upper_bound=127,
2025-08-14T21:17:20.8530111Z     ...     ),
2025-08-14T21:17:20.8530339Z     ...     bias_dtype=torch.float)
2025-08-14T21:17:20.8530641Z 
2025-08-14T21:17:20.8530748Z     >>> dtype_config1.input_dtype
2025-08-14T21:17:20.8531042Z     torch.quint8
2025-08-14T21:17:20.8531183Z 
2025-08-14T21:17:20.8531289Z     >>> dtype_config2.input_dtype
2025-08-14T21:17:20.8531584Z     torch.quint8
2025-08-14T21:17:20.8531723Z 
2025-08-14T21:17:20.8531869Z     >>> dtype_config2.input_dtype_with_constraints
2025-08-14T21:17:20.8532667Z     DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None)
2025-08-14T21:17:20.8533317Z 
2025-08-14T21:17:20.8533568Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.8533952Z 
2025-08-14T21:17:20.9668012Z msg = Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24.
2025-08-14T21:17:20.9669104Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.9669506Z 
2025-08-14T21:17:20.9669825Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into
2025-08-14T21:17:20.9670539Z with their models. The class works with all traceable GraphModules to help diagnose issues,
2025-08-14T21:17:20.9671271Z though the requirements on the type of model more-so depends on the specific report the user
2025-08-14T21:17:20.9672073Z is trying to generate. With respect to the reports, the ModelReport class is initialized with
2025-08-14T21:17:20.9672786Z a set of Detector classes, each of which generate reports on quantization configuration
2025-08-14T21:17:20.9673282Z issues a use might have.
2025-08-14T21:17:20.9673473Z 
2025-08-14T21:17:20.9673601Z Currently supports generating reports on:
2025-08-14T21:17:20.9674073Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module)
2025-08-14T21:17:20.9674696Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules)
2025-08-14T21:17:20.9675375Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules)
2025-08-14T21:17:20.9676003Z - Suggestions for outlier detection for all layers (Graph Modules)
2025-08-14T21:17:20.9676326Z 
2025-08-14T21:17:20.9676736Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver)
2025-08-14T21:17:20.9677618Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport
2025-08-14T21:17:20.9678676Z class compiles the report generated by each Detector class into a single report to return to the user. It also
2025-08-14T21:17:20.9679393Z has the capability to remove all the observers it inserted as well.
2025-08-14T21:17:20.9679719Z 
2025-08-14T21:17:20.9680016Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule
2025-08-14T21:17:20.9680417Z 
2025-08-14T21:17:20.9680791Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class
2025-08-14T21:17:20.9681613Z     Make sure that these are all unique types of detectors [do not have more than 1 of the same class]
2025-08-14T21:17:20.9682059Z 
2025-08-14T21:17:20.9682346Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors.
2025-08-14T21:17:20.9682987Z     This set is generated by calling the get_detector_name() of each detector
2025-08-14T21:17:20.9683332Z 
2025-08-14T21:17:20.9683709Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest
2025-08-14T21:17:20.9684487Z     The purpose of this is to keep track of what observers were inserted for each detector, so that they
2025-08-14T21:17:20.9685029Z     can be removed at the end if desired
2025-08-14T21:17:20.9685262Z 
2025-08-14T21:17:20.9685579Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not
2025-08-14T21:17:20.9686257Z     This is to ensure we only insert observers once with the ModelReport instance
2025-08-14T21:17:20.9686738Z 
2025-08-14T21:17:20.9686994Z * :attr:`_removed_observers` A boolean to track if we have removed observers already
2025-08-14T21:17:20.9687670Z     The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport
2025-08-14T21:17:20.9688409Z     instance. This also allows the functionality where we can generate the report multiple times
2025-08-14T21:17:20.9688992Z     as long as we haven't removed the observers yet.
2025-08-14T21:17:20.9689255Z 
2025-08-14T21:17:20.9689337Z Note:
2025-08-14T21:17:20.9689757Z     This class was initially designed to work with the Fx Graph Mode workflow in mind. However,
2025-08-14T21:17:20.9690494Z     full functionality is available as long as there is a traceable GraphModule that is being used.
2025-08-14T21:17:20.9691232Z     One method to get a traceable GraphModule without going through the Fx workflow is to use
2025-08-14T21:17:20.9691756Z     the QuantizationTracer class.
2025-08-14T21:17:20.9691977Z 
2025-08-14T21:17:20.9692082Z General Flow for Fx workflow:
2025-08-14T21:17:20.9692667Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model
2025-08-14T21:17:20.9693286Z 2.) Prepare your model with prepare_fx
2025-08-14T21:17:20.9693762Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers
2025-08-14T21:17:20.9694243Z 4.) Calibrate your model with data
2025-08-14T21:17:20.9694818Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers
2025-08-14T21:17:20.9695376Z Optional
2025-08-14T21:17:20.9695777Z     6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance
2025-08-14T21:17:20.9696423Z     7.) To help in parsing report information and debugging, view report info as a:
2025-08-14T21:17:20.9696868Z         - Table
2025-08-14T21:17:20.9697103Z         - Histogram
2025-08-14T21:17:20.9697348Z         - Line plot
2025-08-14T21:17:20.9697809Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions
2025-08-14T21:17:20.9698257Z 
2025-08-14T21:17:20.9698373Z Example (with QuantizationTracer):
2025-08-14T21:17:20.9698692Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:20.9698973Z     >>> # get the necessary qconfig
2025-08-14T21:17:20.9699292Z     >>> config = PrepareCustomConfig()
2025-08-14T21:17:20.9699674Z     >>> skipped_module_names, skipped_module_classes = (
2025-08-14T21:17:20.9700284Z     ...     get_skipped_module_name_and_classes(config, False)
2025-08-14T21:17:20.9700653Z     ... )
2025-08-14T21:17:20.9700837Z 
2025-08-14T21:17:20.9701009Z     >>> # initialize our model and get GraphModule
2025-08-14T21:17:20.9701364Z     >>> model = SomeModel()
2025-08-14T21:17:20.9701797Z     >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes)
2025-08-14T21:17:20.9702352Z     >>> graph_module = GraphModule(model, tracer.trace(model))
2025-08-14T21:17:20.9702658Z 
2025-08-14T21:17:20.9702810Z     >>> # get our set of detectors and ModelReport instance
2025-08-14T21:17:20.9703189Z     >>> detector_set = set(
2025-08-14T21:17:20.9703446Z     ...     [
2025-08-14T21:17:20.9703728Z     ...         DynamicStaticDetector(tolerance=0.5),
2025-08-14T21:17:20.9704190Z     ...         InputWeightEqualizationDetector(ratio_threshold=0.7),
2025-08-14T21:17:20.9704578Z     ...     ]
2025-08-14T21:17:20.9704799Z     ... )
2025-08-14T21:17:20.9705144Z     >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set)
2025-08-14T21:17:20.9705475Z 
2025-08-14T21:17:20.9705649Z     >>> # now we insert the observers and calibrate the model
2025-08-14T21:17:20.9706174Z     >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration()
2025-08-14T21:17:20.9706691Z     >>> for i in range(num_callibration_batches):
2025-08-14T21:17:20.9707074Z     >>>     example_input = get_callibration_input()
2025-08-14T21:17:20.9707454Z     >>>     tracer_model_with_observers(example_input)
2025-08-14T21:17:20.9707782Z 
2025-08-14T21:17:20.9708042Z     >>> # finally we generate the reports and optionally remove the observers we inserted
2025-08-14T21:17:20.9708584Z     >>> reports = tracer_reporter.generate_model_report(
2025-08-14T21:17:20.9708978Z     ...     remove_inserted_observers=True
2025-08-14T21:17:20.9709467Z     ... )
2025-08-14T21:17:20.9709602Z 
2025-08-14T21:17:20.9709828Z     >>> # Optional: we can generate the qconfig mapping based on the suggestions
2025-08-14T21:17:20.9710340Z     >>> qconfigs = model_report.generate_qconfig_mapping()
2025-08-14T21:17:20.9710610Z 
2025-08-14T21:17:20.9710852Z     >>> # Optional: we can generate the equalization mapping based on the suggestions
2025-08-14T21:17:20.9711485Z     >>> qconfigs = model_report.generate_equalization_mapping()
2025-08-14T21:17:20.9711792Z 
2025-08-14T21:17:20.9712074Z     >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired
2025-08-14T21:17:20.9712695Z     >>> model_report_visualizer = tracer_reporter.generate_visualizer()
2025-08-14T21:17:20.9713025Z 
2025-08-14T21:17:20.9713029Z 
2025-08-14T21:17:20.9713283Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.9713666Z 
2025-08-14T21:17:20.9752060Z msg = Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301.
2025-08-14T21:17:20.9753544Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.9754002Z 
2025-08-14T21:17:20.9754277Z Takes in optional filter values and generates two tables with desired information.
2025-08-14T21:17:20.9754727Z 
2025-08-14T21:17:20.9754956Z The generated tables are presented in both a list-of-lists format
2025-08-14T21:17:20.9755277Z 
2025-08-14T21:17:20.9755487Z The reason for the two tables are that they handle different things:
2025-08-14T21:17:20.9755993Z 1.) the first table handles all tensor level information
2025-08-14T21:17:20.9756493Z 2.) the second table handles and displays all channel based information
2025-08-14T21:17:20.9756823Z 
2025-08-14T21:17:20.9757157Z The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-08-14T21:17:20.9758084Z     statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-08-14T21:17:20.9759258Z     tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-08-14T21:17:20.9759741Z 
2025-08-14T21:17:20.9759855Z Tensor table columns:
2025-08-14T21:17:20.9760221Z     idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:20.9760685Z     ----  ---------  ---------   ---------   ---------        ---------
2025-08-14T21:17:20.9761027Z 
2025-08-14T21:17:20.9761159Z Per-Channel table columns:
2025-08-14T21:17:20.9761666Z     idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:20.9762174Z     ----  ---------  -------  ---------   ---------   ---------        ---------
2025-08-14T21:17:20.9762529Z 
2025-08-14T21:17:20.9762616Z Args:
2025-08-14T21:17:20.9763009Z     feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:20.9763513Z         contain this filter substring
2025-08-14T21:17:20.9763883Z         Default = "", results in all the features being printed
2025-08-14T21:17:20.9764432Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:20.9765072Z         Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:20.9765469Z 
2025-08-14T21:17:20.9765595Z Returns a dictionary with two keys:
2025-08-14T21:17:20.9765973Z     (Dict[str, Tuple[List, List]]) A dict containing two keys:
2025-08-14T21:17:20.9770708Z     "tensor_level_info", "channel_level_info"
2025-08-14T21:17:20.9771220Z         Each key maps to a tuple with:
2025-08-14T21:17:20.9771552Z             A list of the headers of each table
2025-08-14T21:17:20.9771973Z             A list of lists containing the table information row by row
2025-08-14T21:17:20.9772454Z             The 0th index row will contain the headers of the columns
2025-08-14T21:17:20.9772877Z             The rest of the rows will contain data
2025-08-14T21:17:20.9773118Z 
2025-08-14T21:17:20.9773210Z Example Use:
2025-08-14T21:17:20.9773484Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:20.9773876Z     >>> mod_report_visualizer.generate_filtered_tables(
2025-08-14T21:17:20.9774329Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:20.9774922Z     ... )  # generates table with per_channel_min info for all modules in block 1 of the model
2025-08-14T21:17:20.9775326Z 
2025-08-14T21:17:20.9775579Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.9775982Z 
2025-08-14T21:17:20.9776914Z msg = Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399.
2025-08-14T21:17:20.9778184Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.9778575Z 
2025-08-14T21:17:20.9778848Z Takes in optional filter values and prints out formatted tables of the information.
2025-08-14T21:17:20.9779255Z 
2025-08-14T21:17:20.9779602Z The reason for the two tables printed out instead of one large one are that they handle different things:
2025-08-14T21:17:20.9780235Z 1.) the first table handles all tensor level information
2025-08-14T21:17:20.9780716Z 2.) the second table handles and displays all channel based information
2025-08-14T21:17:20.9781059Z 
2025-08-14T21:17:20.9781375Z The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-08-14T21:17:20.9782150Z     statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-08-14T21:17:20.9782958Z     tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-08-14T21:17:20.9783427Z 
2025-08-14T21:17:20.9783526Z Tensor table columns:
2025-08-14T21:17:20.9783887Z  idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:20.9784365Z ----  ---------  ---------   ---------   ---------        ---------
2025-08-14T21:17:20.9784722Z 
2025-08-14T21:17:20.9784840Z Per-Channel table columns:
2025-08-14T21:17:20.9785037Z 
2025-08-14T21:17:20.9785258Z  idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:20.9785765Z ----  ---------  -------  ---------   ---------   ---------        ---------
2025-08-14T21:17:20.9786046Z 
2025-08-14T21:17:20.9786150Z Args:
2025-08-14T21:17:20.9786531Z     feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:20.9787035Z         contain this filter substring
2025-08-14T21:17:20.9787418Z         Default = "", results in all the features being printed
2025-08-14T21:17:20.9787951Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:20.9788590Z         Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:20.9788968Z 
2025-08-14T21:17:20.9789056Z Example Use:
2025-08-14T21:17:20.9789324Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:20.9789739Z     >>> mod_report_visualizer.generate_table_visualization(
2025-08-14T21:17:20.9790222Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:20.9790629Z     ... )
2025-08-14T21:17:20.9790938Z     >>> # prints out neatly formatted table with per_channel_min info
2025-08-14T21:17:20.9791379Z     >>> # for all modules in block 1 of the model
2025-08-14T21:17:20.9791856Z 
2025-08-14T21:17:20.9792150Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.9792520Z 
2025-08-14T21:17:20.9793445Z msg = Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564.
2025-08-14T21:17:20.9794713Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.9795108Z 
2025-08-14T21:17:20.9795350Z Takes in a feature and optional module_filter and plots of the desired data.
2025-08-14T21:17:20.9795718Z 
2025-08-14T21:17:20.9795991Z For per channel features, it averages the value across the channels and plots a point
2025-08-14T21:17:20.9796658Z per module. The reason for this is that for models with hundreds of channels, it can
2025-08-14T21:17:20.9797311Z be hard to differentiate one channel line from another, and so the point of generating
2025-08-14T21:17:20.9797992Z a single average point per module is to give a sense of general trends that encourage
2025-08-14T21:17:20.9798496Z further deep dives.
2025-08-14T21:17:20.9798650Z 
2025-08-14T21:17:20.9798748Z Note:
2025-08-14T21:17:20.9799127Z     Only features in the report that have tensor value data are plottable by this class
2025-08-14T21:17:20.9799687Z     When the tensor information is plotted, it will plot:
2025-08-14T21:17:20.9800109Z         idx as the x val, feature value as the y_val
2025-08-14T21:17:20.9800525Z     When the channel information is plotted, it will plot:
2025-08-14T21:17:20.9801199Z         the first idx of each module as the x val, feature value as the y_val [for each channel]
2025-08-14T21:17:20.9801825Z         The reason for this is that we want to be able to compare values across the
2025-08-14T21:17:20.9802418Z         channels for same layer, and it will be hard if values are staggered by idx
2025-08-14T21:17:20.9802934Z         This means each module is represented by only 1 x value
2025-08-14T21:17:20.9803309Z Args:
2025-08-14T21:17:20.9803654Z     feature_filter (str): Filters the features presented to only those that
2025-08-14T21:17:20.9804099Z         contain this filter substring
2025-08-14T21:17:20.9804574Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:20.9805208Z         Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:20.9805576Z 
2025-08-14T21:17:20.9805677Z Example Use:
2025-08-14T21:17:20.9806022Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:20.9806435Z     >>> mod_report_visualizer.generate_plot_visualization(
2025-08-14T21:17:20.9806909Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:20.9807306Z     ... )
2025-08-14T21:17:20.9807618Z     >>> # outputs line plot of per_channel_min information for all
2025-08-14T21:17:20.9808109Z     >>> # modules in block1 of model each channel gets it's own line,
2025-08-14T21:17:20.9808585Z     >>> # and it's plotted across the in-order modules on the x-axis
2025-08-14T21:17:20.9808887Z 
2025-08-14T21:17:20.9809337Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.9809726Z 
2025-08-14T21:17:20.9810661Z msg = Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643.
2025-08-14T21:17:20.9811970Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:20.9812347Z 
2025-08-14T21:17:20.9812636Z Takes in a feature and optional module_filter and plots the histogram of desired data.
2025-08-14T21:17:20.9813036Z 
2025-08-14T21:17:20.9813118Z Note:
2025-08-14T21:17:20.9813507Z     Only features in the report that have tensor value data can be viewed as a histogram
2025-08-14T21:17:20.9814282Z     If you want to plot a histogram from all the channel values of a specific feature for
2025-08-14T21:17:20.9814965Z         a specific model, make sure to specify both the model and the feature properly
2025-08-14T21:17:20.9815589Z         in the filters and you should be able to see a distribution of the channel data
2025-08-14T21:17:20.9815970Z 
2025-08-14T21:17:20.9816050Z Args:
2025-08-14T21:17:20.9816438Z     feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:20.9816932Z         contain this filter substring
2025-08-14T21:17:20.9817323Z         Default = "", results in all the features being printed
2025-08-14T21:17:20.9817865Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:20.9818489Z         Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:20.9819087Z     num_bins (int, optional): The number of bins to create the histogram with
2025-08-14T21:17:20.9819629Z         Default = 10, the values will be split into 10 equal sized bins
2025-08-14T21:17:20.9819934Z 
2025-08-14T21:17:20.9820038Z Example Use:
2025-08-14T21:17:20.9820270Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:20.9820746Z     >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization(
2025-08-14T21:17:20.9821368Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:20.9821757Z     ... )
2025-08-14T21:17:20.9822163Z     # outputs histogram of per_channel_min information for all modules in block1 of model
2025-08-14T21:17:20.9822830Z         information is gathered across all channels for all modules in block 1 for the
2025-08-14T21:17:20.9823434Z         per_channel_min and is displayed in a histogram of equally sized bins
2025-08-14T21:17:20.9823771Z 
2025-08-14T21:17:20.9824023Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:20.9824402Z 
2025-08-14T21:17:21.1213422Z msg = Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734.
2025-08-14T21:17:21.1214406Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.1215305Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler.
2025-08-14T21:17:21.1216004Z     Label will only appear if CPU activity tracing is enabled.
2025-08-14T21:17:21.1216301Z 
2025-08-14T21:17:21.1216455Z     It is useful when tracing the code profile.
2025-08-14T21:17:21.1216716Z 
2025-08-14T21:17:21.1217050Z     Args:
2025-08-14T21:17:21.1217320Z         name (str): Label assigned to the block of code.
2025-08-14T21:17:21.1217770Z         node_id (int): ID of node, for distributed profiling. Unset in
2025-08-14T21:17:21.1218187Z         non-distributed cases.
2025-08-14T21:17:21.1218378Z 
2025-08-14T21:17:21.1218466Z     Example:
2025-08-14T21:17:21.1218790Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER)
2025-08-14T21:17:21.1219230Z         >>> x = torch.randn((1, 1), requires_grad=True)
2025-08-14T21:17:21.1219626Z         >>> with torch.autograd.profiler.profile() as prof:
2025-08-14T21:17:21.1220001Z         ...     y = x**2
2025-08-14T21:17:21.1220331Z         ...     with torch.autograd.profiler.record_function(
2025-08-14T21:17:21.1220703Z         ...         "label-z"
2025-08-14T21:17:21.1220974Z         ...     ):  # label the block
2025-08-14T21:17:21.1221279Z         ...         z = y**3
2025-08-14T21:17:21.1221555Z         ...     y.backward()
2025-08-14T21:17:21.1221828Z         >>> # xdoctest: +IGNORE_WANT
2025-08-14T21:17:21.1222177Z         >>> # NOTE: some columns were removed for brevity
2025-08-14T21:17:21.1222638Z         >>> print(prof.key_averages().table(sort_by="self_cpu_time_total"))
2025-08-14T21:17:21.1223156Z         -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:21.1223662Z         Name                                 Self CPU total %  CPU time avg     Number of Calls
2025-08-14T21:17:21.1224286Z         -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:21.1224738Z         pow                                  60.77%           47.470us         3
2025-08-14T21:17:21.1225111Z         mul                                  21.73%           25.465us         2
2025-08-14T21:17:21.1225537Z         PowBackward0                         12.03%           121.891us        1
2025-08-14T21:17:21.1226078Z         torch::autograd::AccumulateGrad      2.70%            6.324us          1
2025-08-14T21:17:21.1226568Z         label-z                              2.13%            12.421us         1
2025-08-14T21:17:21.1227030Z         torch::autograd::GraphRoot           0.64%            1.503us          1
2025-08-14T21:17:21.1227546Z         -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:21.1227978Z         Self CPU time total: 234.344us
2025-08-14T21:17:21.1228289Z         CUDA time total: 0.000us
2025-08-14T21:17:21.1228491Z 
2025-08-14T21:17:21.1228572Z     
2025-08-14T21:17:21.1228945Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.1229315Z 
2025-08-14T21:17:21.2946775Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=722.
2025-08-14T21:17:21.2948596Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:21.2949256Z 
2025-08-14T21:17:21.2949721Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh.
2025-08-14T21:17:21.2950932Z The submesh created consists of the dimensions and the communicators indicated by
2025-08-14T21:17:21.2951870Z ``mesh_dim_names``
2025-08-14T21:17:21.2952129Z 
2025-08-14T21:17:21.2952267Z Args:
2025-08-14T21:17:21.2952888Z     mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the
2025-08-14T21:17:21.2953899Z     mesh dimension of the DeviceMesh to create the submesh for.
2025-08-14T21:17:21.2954600Z Returns:
2025-08-14T21:17:21.2954976Z     A :class:`DeviceMesh` object
2025-08-14T21:17:21.2955282Z 
2025-08-14T21:17:21.2955765Z The following program runs on each process/rank in an SPMD manner in a world size of 8.
2025-08-14T21:17:21.2956624Z In the first example:
2025-08-14T21:17:21.2957336Z     Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]).
2025-08-14T21:17:21.2958755Z     Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of  DeviceMesh:([4, 5, 6, 7]).
2025-08-14T21:17:21.2959842Z     Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of  DeviceMesh:([0, 4]).
2025-08-14T21:17:21.2960858Z     Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of  DeviceMesh:([1, 5]).
2025-08-14T21:17:21.2961787Z     Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of  DeviceMesh:([2, 6]).
2025-08-14T21:17:21.2962763Z     Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of  DeviceMesh:([3, 7]).
2025-08-14T21:17:21.2963381Z 
2025-08-14T21:17:21.2963547Z In the second example:
2025-08-14T21:17:21.2964345Z     Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]).
2025-08-14T21:17:21.2965072Z     Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]).
2025-08-14T21:17:21.2965729Z     Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]).
2025-08-14T21:17:21.2966391Z     Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]).
2025-08-14T21:17:21.2966772Z 
2025-08-14T21:17:21.2966874Z Example::
2025-08-14T21:17:21.2967013Z 
2025-08-14T21:17:21.2967120Z     >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:21.2967516Z     >>> from torch.distributed.device_mesh import DeviceMesh
2025-08-14T21:17:21.2968030Z     >>>
2025-08-14T21:17:21.2968366Z     >>> # Initialize a 2D device mesh as (2, 4) to represent the topology
2025-08-14T21:17:21.2968907Z     >>> # of cross-host(dim 0), and within-host (dim 1).
2025-08-14T21:17:21.2969483Z     >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-08-14T21:17:21.2969962Z     >>> tp_mesh = mesh_2d["tp"]
2025-08-14T21:17:21.2970264Z     >>> dp_mesh = mesh_2d["dp"]
2025-08-14T21:17:21.2970545Z     >>>
2025-08-14T21:17:21.2970756Z     >>> # Initialize a 3D mesh.
2025-08-14T21:17:21.2971234Z     >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp"))
2025-08-14T21:17:21.2971947Z     >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh.
2025-08-14T21:17:21.2972481Z     >>> dp_cp_mesh = mesh_3d["dp", "cp"]
2025-08-14T21:17:21.2972821Z     >>> cp_dp_mesh = mesh_3d["cp", "dp"]
2025-08-14T21:17:21.2973051Z 
2025-08-14T21:17:21.2973728Z Original Error: SyntaxError('positional argument follows keyword argument', ('<source_block>', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83))
2025-08-14T21:17:21.2974521Z 
2025-08-14T21:17:21.2974776Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-08-14T21:17:21.2975253Z                                                                                  ^
2025-08-14T21:17:21.3300795Z msg = Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2706.
2025-08-14T21:17:21.3301817Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3302201Z 
2025-08-14T21:17:21.3302455Z Send or Receive a batch of tensors asynchronously and return a list of requests.
2025-08-14T21:17:21.3302834Z 
2025-08-14T21:17:21.3303084Z Process each of the operations in ``p2p_op_list`` and return the corresponding
2025-08-14T21:17:21.3303658Z requests. NCCL, Gloo, and UCC backend are currently supported.
2025-08-14T21:17:21.3303975Z 
2025-08-14T21:17:21.3304069Z Args:
2025-08-14T21:17:21.3304406Z     p2p_op_list: A list of point-to-point operations(type of each operator is
2025-08-14T21:17:21.3304987Z         ``torch.distributed.P2POp``). The order of the isend/irecv in the list
2025-08-14T21:17:21.3305552Z         matters and it needs to match with corresponding isend/irecv on the
2025-08-14T21:17:21.3306009Z         remote end.
2025-08-14T21:17:21.3306174Z 
2025-08-14T21:17:21.3306262Z Returns:
2025-08-14T21:17:21.3306911Z     A list of distributed request objects returned by calling the corresponding
2025-08-14T21:17:21.3307781Z     op in the op_list.
2025-08-14T21:17:21.3308040Z 
2025-08-14T21:17:21.3308130Z Examples:
2025-08-14T21:17:21.3308367Z     >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:21.3308771Z     >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank
2025-08-14T21:17:21.3309419Z     >>> recv_tensor = torch.randn(2, dtype=torch.float32)
2025-08-14T21:17:21.3309896Z     >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size)
2025-08-14T21:17:21.3310343Z     >>> recv_op = dist.P2POp(
2025-08-14T21:17:21.3310735Z     ...     dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size
2025-08-14T21:17:21.3311122Z     ... )
2025-08-14T21:17:21.3311382Z     >>> reqs = batch_isend_irecv([send_op, recv_op])
2025-08-14T21:17:21.3311822Z     >>> for req in reqs:
2025-08-14T21:17:21.3312071Z     >>>     req.wait()
2025-08-14T21:17:21.3312323Z     >>> recv_tensor
2025-08-14T21:17:21.3312578Z     tensor([2, 3])     # Rank 0
2025-08-14T21:17:21.3312850Z     tensor([0, 1])     # Rank 1
2025-08-14T21:17:21.3313046Z 
2025-08-14T21:17:21.3313311Z .. note:: Note that when this API is used with the NCCL PG backend, users must set
2025-08-14T21:17:21.3313896Z     the current GPU device with `torch.cuda.set_device`, otherwise it will
2025-08-14T21:17:21.3314350Z     lead to unexpected hang issues.
2025-08-14T21:17:21.3314651Z 
2025-08-14T21:17:21.3314860Z     In addition, if this API is the first collective call in the ``group``
2025-08-14T21:17:21.3315468Z     passed to ``dist.P2POp``, all ranks of the ``group`` must participate in
2025-08-14T21:17:21.3316030Z     this API call; otherwise, the behavior is undefined. If this API call is
2025-08-14T21:17:21.3316597Z     not the first collective call in the ``group``, batched P2P operations
2025-08-14T21:17:21.3317125Z     involving only a subset of ranks of the ``group`` are allowed.
2025-08-14T21:17:21.3317446Z 
2025-08-14T21:17:21.3317699Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3318064Z 
2025-08-14T21:17:21.3318674Z msg = Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2838.
2025-08-14T21:17:21.3319719Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3320097Z 
2025-08-14T21:17:21.3320369Z Reduces the tensor data across all machines in a way that all get the final result.
2025-08-14T21:17:21.3320776Z 
2025-08-14T21:17:21.3321002Z After the call ``tensor`` is going to be bitwise identical in all processes.
2025-08-14T21:17:21.3321361Z 
2025-08-14T21:17:21.3321471Z Complex tensors are supported.
2025-08-14T21:17:21.3321666Z 
2025-08-14T21:17:21.3321763Z Args:
2025-08-14T21:17:21.3322082Z     tensor (Tensor): Input and output of the collective. The function
2025-08-14T21:17:21.3322516Z         operates in-place.
2025-08-14T21:17:21.3322823Z     op (optional): One of the values from
2025-08-14T21:17:21.3323197Z         ``torch.distributed.ReduceOp``
2025-08-14T21:17:21.3323779Z         enum.  Specifies an operation used for element-wise reductions.
2025-08-14T21:17:21.3324336Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.3325064Z         the default process group will be used.
2025-08-14T21:17:21.3325859Z     async_op (bool, optional): Whether this op should be an async op
2025-08-14T21:17:21.3326189Z 
2025-08-14T21:17:21.3326275Z Returns:
2025-08-14T21:17:21.3326538Z     Async work handle, if async_op is set to True.
2025-08-14T21:17:21.3326928Z     None, if not async_op or if not part of the group
2025-08-14T21:17:21.3327193Z 
2025-08-14T21:17:21.3327279Z Examples:
2025-08-14T21:17:21.3327514Z     >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:21.3327863Z     >>> # All tensors below are of torch.int64 type.
2025-08-14T21:17:21.3328286Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.3328775Z     >>> device = torch.device(f"cuda:{rank}")
2025-08-14T21:17:21.3329247Z     >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-08-14T21:17:21.3329680Z     >>> tensor
2025-08-14T21:17:21.3329937Z     tensor([1, 2], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3330281Z     tensor([3, 4], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3330626Z     >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-08-14T21:17:21.3330967Z     >>> tensor
2025-08-14T21:17:21.3331217Z     tensor([4, 6], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3331541Z     tensor([4, 6], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3331772Z 
2025-08-14T21:17:21.3331911Z     >>> # All tensors below are of torch.cfloat type.
2025-08-14T21:17:21.3344256Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.3344635Z     >>> tensor = torch.tensor(
2025-08-14T21:17:21.3344986Z     ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-08-14T21:17:21.3345343Z     ... ) + 2 * rank * (1 + 1j)
2025-08-14T21:17:21.3345639Z     >>> tensor
2025-08-14T21:17:21.3345921Z     tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3346306Z     tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3346698Z     >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-08-14T21:17:21.3347033Z     >>> tensor
2025-08-14T21:17:21.3347298Z     tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3347803Z     tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3348117Z 
2025-08-14T21:17:21.3348121Z 
2025-08-14T21:17:21.3348378Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3348753Z 
2025-08-14T21:17:21.3349392Z msg = Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3198.
2025-08-14T21:17:21.3350363Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3350745Z 
2025-08-14T21:17:21.3350987Z Gathers picklable objects from the whole group in a single process.
2025-08-14T21:17:21.3351325Z 
2025-08-14T21:17:21.3351652Z Similar to :func:`gather`, but Python objects can be passed in. Note that the
2025-08-14T21:17:21.3352161Z object must be picklable in order to be gathered.
2025-08-14T21:17:21.3352420Z 
2025-08-14T21:17:21.3352519Z Args:
2025-08-14T21:17:21.3352764Z     obj (Any): Input object. Must be picklable.
2025-08-14T21:17:21.3353226Z     object_gather_list (list[Any]): Output list. On the ``dst`` rank, it
2025-08-14T21:17:21.3353756Z         should be correctly sized as the size of the group for this
2025-08-14T21:17:21.3354286Z         collective and will contain the output. Must be ``None`` on non-dst
2025-08-14T21:17:21.3354721Z         ranks. (default is ``None``)
2025-08-14T21:17:21.3355254Z     dst (int, optional): Destination rank on global process group (regardless of ``group`` argument).
2025-08-14T21:17:21.3355900Z         (If both ``dst`` and ``group_dst`` are None, default is global rank 0)
2025-08-14T21:17:21.3356436Z     group: (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.3356983Z         the default process group will be used. Default is ``None``.
2025-08-14T21:17:21.3357871Z     group_dst (int, optional): Destination rank on ``group``.  Invalid to specify both ``dst`` and ``group_dst``
2025-08-14T21:17:21.3358605Z 
2025-08-14T21:17:21.3358710Z Returns:
2025-08-14T21:17:21.3359007Z     None. On the ``dst`` rank, ``object_gather_list`` will contain the
2025-08-14T21:17:21.3359420Z     output of the collective.
2025-08-14T21:17:21.3359608Z 
2025-08-14T21:17:21.3359846Z .. note:: Note that this API differs slightly from the gather collective
2025-08-14T21:17:21.3360384Z     since it does not provide an async_op handle and thus will be a blocking
2025-08-14T21:17:21.3360815Z     call.
2025-08-14T21:17:21.3360947Z 
2025-08-14T21:17:21.3361181Z .. note:: For NCCL-based processed groups, internal tensor representations
2025-08-14T21:17:21.3361855Z     of objects must be moved to the GPU device before communication takes
2025-08-14T21:17:21.3362329Z     place. In this case, the device used is given by
2025-08-14T21:17:21.3362818Z     ``torch.cuda.current_device()`` and it is the user's responsibility to
2025-08-14T21:17:21.3363403Z     ensure that this is set so that each rank has an individual GPU, via
2025-08-14T21:17:21.3363834Z     ``torch.cuda.set_device()``.
2025-08-14T21:17:21.3364051Z 
2025-08-14T21:17:21.3364144Z .. warning::
2025-08-14T21:17:21.3364525Z     Object collectives have a number of serious performance and scalability
2025-08-14T21:17:21.3365080Z     limitations.  See :ref:`object_collectives` for details.
2025-08-14T21:17:21.3365471Z 
2025-08-14T21:17:21.3365561Z .. warning::
2025-08-14T21:17:21.3365898Z     :func:`gather_object` uses ``pickle`` module implicitly, which is
2025-08-14T21:17:21.3366439Z     known to be insecure. It is possible to construct malicious pickle data
2025-08-14T21:17:21.3367168Z     which will execute arbitrary code during unpickling. Only call this
2025-08-14T21:17:21.3367985Z     function with data you trust.
2025-08-14T21:17:21.3368314Z 
2025-08-14T21:17:21.3368403Z .. warning::
2025-08-14T21:17:21.3368755Z     Calling :func:`gather_object` with GPU tensors is not well supported
2025-08-14T21:17:21.3369313Z     and inefficient as it incurs GPU -> CPU transfer since tensors would be
2025-08-14T21:17:21.3369900Z     pickled. Please consider using :func:`gather` instead.
2025-08-14T21:17:21.3370222Z 
2025-08-14T21:17:21.3370325Z Example::
2025-08-14T21:17:21.3370583Z     >>> # xdoctest: +SKIP("need process group init")
2025-08-14T21:17:21.3371020Z     >>> # Note: Process group initialization omitted on each rank.
2025-08-14T21:17:21.3371441Z     >>> import torch.distributed as dist
2025-08-14T21:17:21.3371780Z     >>> # Assumes world_size of 3.
2025-08-14T21:17:21.3372152Z     >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object
2025-08-14T21:17:21.3372582Z     >>> output = [None for _ in gather_objects]
2025-08-14T21:17:21.3372943Z     >>> dist.gather_object(
2025-08-14T21:17:21.3373233Z     ...     gather_objects[dist.get_rank()],
2025-08-14T21:17:21.3373600Z     ...     output if dist.get_rank() == 0 else None,
2025-08-14T21:17:21.3373937Z     ...     dst=0
2025-08-14T21:17:21.3374154Z     ... )
2025-08-14T21:17:21.3374373Z     >>> # On rank 0
2025-08-14T21:17:21.3374604Z     >>> output
2025-08-14T21:17:21.3374823Z     ['foo', 12, {1: 2}]
2025-08-14T21:17:21.3374992Z 
2025-08-14T21:17:21.3375246Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3375629Z 
2025-08-14T21:17:21.3376229Z msg = Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3794.
2025-08-14T21:17:21.3377177Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3377555Z 
2025-08-14T21:17:21.3377709Z Gathers tensors from the whole group in a list.
2025-08-14T21:17:21.3377963Z 
2025-08-14T21:17:21.3378106Z Complex and uneven sized tensors are supported.
2025-08-14T21:17:21.3378371Z 
2025-08-14T21:17:21.3378454Z Args:
2025-08-14T21:17:21.3378756Z     tensor_list (list[Tensor]): Output list. It should contain
2025-08-14T21:17:21.3379262Z         correctly-sized tensors to be used for output of the collective.
2025-08-14T21:17:21.3379722Z         Uneven sized tensors are supported.
2025-08-14T21:17:21.3380149Z     tensor (Tensor): Tensor to be broadcast from current process.
2025-08-14T21:17:21.3380693Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.3381164Z         the default process group will be used.
2025-08-14T21:17:21.3381607Z     async_op (bool, optional): Whether this op should be an async op
2025-08-14T21:17:21.3381917Z 
2025-08-14T21:17:21.3382017Z Returns:
2025-08-14T21:17:21.3382269Z     Async work handle, if async_op is set to True.
2025-08-14T21:17:21.3382743Z     None, if not async_op or if not part of the group
2025-08-14T21:17:21.3383001Z 
2025-08-14T21:17:21.3383105Z Examples:
2025-08-14T21:17:21.3383377Z     >>> # xdoctest: +SKIP("need process group init")
2025-08-14T21:17:21.3383754Z     >>> # All tensors below are of torch.int64 dtype.
2025-08-14T21:17:21.3384149Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.3384586Z     >>> device = torch.device(f"cuda:{rank}")
2025-08-14T21:17:21.3384908Z     >>> tensor_list = [
2025-08-14T21:17:21.3385291Z     ...     torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2)
2025-08-14T21:17:21.3385718Z     ... ]
2025-08-14T21:17:21.3385926Z     >>> tensor_list
2025-08-14T21:17:21.3386278Z     [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0
2025-08-14T21:17:21.3386800Z     [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1
2025-08-14T21:17:21.3387351Z     >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-08-14T21:17:21.3387782Z     >>> tensor
2025-08-14T21:17:21.3388040Z     tensor([1, 2], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3388385Z     tensor([3, 4], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3388721Z     >>> dist.all_gather(tensor_list, tensor)
2025-08-14T21:17:21.3389055Z     >>> tensor_list
2025-08-14T21:17:21.3389465Z     [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0
2025-08-14T21:17:21.3389974Z     [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1
2025-08-14T21:17:21.3390425Z 
2025-08-14T21:17:21.3390573Z     >>> # All tensors below are of torch.cfloat dtype.
2025-08-14T21:17:21.3390956Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.3391283Z     >>> tensor_list = [
2025-08-14T21:17:21.3391771Z     ...     torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2)
2025-08-14T21:17:21.3392204Z     ... ]
2025-08-14T21:17:21.3392426Z     >>> tensor_list
2025-08-14T21:17:21.3392817Z     [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0
2025-08-14T21:17:21.3393457Z     [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1
2025-08-14T21:17:21.3393928Z     >>> tensor = torch.tensor(
2025-08-14T21:17:21.3394258Z     ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-08-14T21:17:21.3394623Z     ... ) + 2 * rank * (1 + 1j)
2025-08-14T21:17:21.3394946Z     >>> tensor
2025-08-14T21:17:21.3395306Z     tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-08-14T21:17:21.3395716Z     tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-08-14T21:17:21.3396090Z     >>> dist.all_gather(tensor_list, tensor)
2025-08-14T21:17:21.3396413Z     >>> tensor_list
2025-08-14T21:17:21.3396798Z     [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0
2025-08-14T21:17:21.3397407Z     [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1
2025-08-14T21:17:21.3397765Z 
2025-08-14T21:17:21.3397785Z 
2025-08-14T21:17:21.3398044Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3398417Z 
2025-08-14T21:17:21.3426097Z msg = Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4500.
2025-08-14T21:17:21.3427377Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3427769Z 
2025-08-14T21:17:21.3428027Z Split input tensor and then scatter the split list to all processes in a group.
2025-08-14T21:17:21.3428418Z 
2025-08-14T21:17:21.3428680Z Later the received tensors are concatenated from all the processes in the group
2025-08-14T21:17:21.3429193Z and returned as a single output tensor.
2025-08-14T21:17:21.3429418Z 
2025-08-14T21:17:21.3429543Z Complex tensors are supported.
2025-08-14T21:17:21.3429737Z 
2025-08-14T21:17:21.3429819Z Args:
2025-08-14T21:17:21.3430118Z     output (Tensor): Gathered concatenated output tensor.
2025-08-14T21:17:21.3430710Z     input (Tensor): Input tensor to scatter.
2025-08-14T21:17:21.3431160Z     output_split_sizes: (list[Int], optional): Output split sizes for dim 0
2025-08-14T21:17:21.3431801Z         if specified None or empty, dim 0 of ``output`` tensor must divide
2025-08-14T21:17:21.3432242Z         equally by ``world_size``.
2025-08-14T21:17:21.3432654Z     input_split_sizes: (list[Int], optional): Input split sizes for dim 0
2025-08-14T21:17:21.3433205Z         if specified None or empty, dim 0 of ``input`` tensor must divide
2025-08-14T21:17:21.3433634Z         equally by ``world_size``.
2025-08-14T21:17:21.3434075Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.3434543Z         the default process group will be used.
2025-08-14T21:17:21.3434986Z     async_op (bool, optional): Whether this op should be an async op.
2025-08-14T21:17:21.3435299Z 
2025-08-14T21:17:21.3435397Z Returns:
2025-08-14T21:17:21.3435653Z     Async work handle, if async_op is set to True.
2025-08-14T21:17:21.3436061Z     None, if not async_op or if not part of the group.
2025-08-14T21:17:21.3436316Z 
2025-08-14T21:17:21.3436447Z .. warning::
2025-08-14T21:17:21.3436758Z     `all_to_all_single` is experimental and subject to change.
2025-08-14T21:17:21.3437041Z 
2025-08-14T21:17:21.3437143Z Examples:
2025-08-14T21:17:21.3437381Z     >>> # xdoctest: +SKIP("Undefined rank")
2025-08-14T21:17:21.3437917Z     >>> input = torch.arange(4) + rank * 4
2025-08-14T21:17:21.3438455Z     >>> input
2025-08-14T21:17:21.3438795Z     tensor([0, 1, 2, 3])     # Rank 0
2025-08-14T21:17:21.3439178Z     tensor([4, 5, 6, 7])     # Rank 1
2025-08-14T21:17:21.3439565Z     tensor([8, 9, 10, 11])   # Rank 2
2025-08-14T21:17:21.3440034Z     tensor([12, 13, 14, 15]) # Rank 3
2025-08-14T21:17:21.3440689Z     >>> output = torch.empty([4], dtype=torch.int64)
2025-08-14T21:17:21.3441148Z     >>> dist.all_to_all_single(output, input)
2025-08-14T21:17:21.3441461Z     >>> output
2025-08-14T21:17:21.3441719Z     tensor([0, 4, 8, 12])    # Rank 0
2025-08-14T21:17:21.3442108Z     tensor([1, 5, 9, 13])    # Rank 1
2025-08-14T21:17:21.3442711Z     tensor([2, 6, 10, 14])   # Rank 2
2025-08-14T21:17:21.3443044Z     tensor([3, 7, 11, 15])   # Rank 3
2025-08-14T21:17:21.3443252Z 
2025-08-14T21:17:21.3443418Z     >>> # Essentially, it is similar to following operation:
2025-08-14T21:17:21.3443839Z     >>> scatter_list = list(input.chunk(world_size))
2025-08-14T21:17:21.3444226Z     >>> gather_list = list(output.chunk(world_size))
2025-08-14T21:17:21.3444593Z     >>> for i in range(world_size):
2025-08-14T21:17:21.3445031Z     >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i)
2025-08-14T21:17:21.3445379Z 
2025-08-14T21:17:21.3445506Z     >>> # Another example with uneven split
2025-08-14T21:17:21.3445818Z     >>> input
2025-08-14T21:17:21.3446111Z     tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-08-14T21:17:21.3446554Z     tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-08-14T21:17:21.3447016Z     tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-08-14T21:17:21.3447442Z     tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-08-14T21:17:21.3447816Z     >>> input_splits
2025-08-14T21:17:21.3448100Z     [2, 2, 1, 1]                                                     # Rank 0
2025-08-14T21:17:21.3448459Z     [3, 2, 2, 2]                                                     # Rank 1
2025-08-14T21:17:21.3448829Z     [2, 1, 1, 1]                                                     # Rank 2
2025-08-14T21:17:21.3449195Z     [2, 2, 2, 1]                                                     # Rank 3
2025-08-14T21:17:21.3449535Z     >>> output_splits
2025-08-14T21:17:21.3449805Z     [2, 3, 2, 2]                                                     # Rank 0
2025-08-14T21:17:21.3450183Z     [2, 2, 1, 2]                                                     # Rank 1
2025-08-14T21:17:21.3450648Z     [1, 2, 1, 2]                                                     # Rank 2
2025-08-14T21:17:21.3451006Z     [1, 2, 1, 1]                                                     # Rank 3
2025-08-14T21:17:21.3451349Z     >>> output = ...
2025-08-14T21:17:21.3451720Z     >>> dist.all_to_all_single(output, input, output_splits, input_splits)
2025-08-14T21:17:21.3452135Z     >>> output
2025-08-14T21:17:21.3452423Z     tensor([ 0,  1, 10, 11, 12, 20, 21, 30, 31])                     # Rank 0
2025-08-14T21:17:21.3452864Z     tensor([ 2,  3, 13, 14, 22, 32, 33])                             # Rank 1
2025-08-14T21:17:21.3453300Z     tensor([ 4, 15, 16, 23, 34, 35])                                 # Rank 2
2025-08-14T21:17:21.3453723Z     tensor([ 5, 17, 18, 24, 36])                                     # Rank 3
2025-08-14T21:17:21.3454008Z 
2025-08-14T21:17:21.3454012Z 
2025-08-14T21:17:21.3454172Z     >>> # Another example with tensors of torch.cfloat type.
2025-08-14T21:17:21.3454551Z     >>> input = torch.tensor(
2025-08-14T21:17:21.3454888Z     ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-08-14T21:17:21.3455231Z     ... ) + 4 * rank * (1 + 1j)
2025-08-14T21:17:21.3455505Z     >>> input
2025-08-14T21:17:21.3455818Z     tensor([1+1j, 2+2j, 3+3j, 4+4j])                                # Rank 0
2025-08-14T21:17:21.3456270Z     tensor([5+5j, 6+6j, 7+7j, 8+8j])                                # Rank 1
2025-08-14T21:17:21.3456790Z     tensor([9+9j, 10+10j, 11+11j, 12+12j])                          # Rank 2
2025-08-14T21:17:21.3457309Z     tensor([13+13j, 14+14j, 15+15j, 16+16j])                        # Rank 3
2025-08-14T21:17:21.3457763Z     >>> output = torch.empty([4], dtype=torch.int64)
2025-08-14T21:17:21.3458136Z     >>> dist.all_to_all_single(output, input)
2025-08-14T21:17:21.3458457Z     >>> output
2025-08-14T21:17:21.3458766Z     tensor([1+1j, 5+5j, 9+9j, 13+13j])                              # Rank 0
2025-08-14T21:17:21.3459230Z     tensor([2+2j, 6+6j, 10+10j, 14+14j])                            # Rank 1
2025-08-14T21:17:21.3459698Z     tensor([3+3j, 7+7j, 11+11j, 15+15j])                            # Rank 2
2025-08-14T21:17:21.3460164Z     tensor([4+4j, 8+8j, 12+12j, 16+16j])                            # Rank 3
2025-08-14T21:17:21.3460455Z 
2025-08-14T21:17:21.3460718Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3461084Z 
2025-08-14T21:17:21.3461698Z msg = Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4642.
2025-08-14T21:17:21.3462628Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3463018Z 
2025-08-14T21:17:21.3463383Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list.
2025-08-14T21:17:21.3463880Z 
2025-08-14T21:17:21.3463990Z Complex tensors are supported.
2025-08-14T21:17:21.3464182Z 
2025-08-14T21:17:21.3464276Z Args:
2025-08-14T21:17:21.3464608Z     output_tensor_list (list[Tensor]): List of tensors to be gathered one
2025-08-14T21:17:21.3465039Z         per rank.
2025-08-14T21:17:21.3465413Z     input_tensor_list (list[Tensor]): List of tensors to scatter one per rank.
2025-08-14T21:17:21.3465987Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.3466464Z         the default process group will be used.
2025-08-14T21:17:21.3466905Z     async_op (bool, optional): Whether this op should be an async op.
2025-08-14T21:17:21.3467219Z 
2025-08-14T21:17:21.3467316Z Returns:
2025-08-14T21:17:21.3467564Z     Async work handle, if async_op is set to True.
2025-08-14T21:17:21.3467973Z     None, if not async_op or if not part of the group.
2025-08-14T21:17:21.3468229Z 
2025-08-14T21:17:21.3468336Z .. warning::
2025-08-14T21:17:21.3468609Z     `all_to_all` is experimental and subject to change.
2025-08-14T21:17:21.3468878Z 
2025-08-14T21:17:21.3468967Z Examples:
2025-08-14T21:17:21.3469277Z     >>> # xdoctest: +SKIP("Undefined rank")
2025-08-14T21:17:21.3469615Z     >>> input = torch.arange(4) + rank * 4
2025-08-14T21:17:21.3469956Z     >>> input = list(input.chunk(4))
2025-08-14T21:17:21.3470262Z     >>> input
2025-08-14T21:17:21.3470571Z     [tensor([0]), tensor([1]), tensor([2]), tensor([3])]     # Rank 0
2025-08-14T21:17:21.3471017Z     [tensor([4]), tensor([5]), tensor([6]), tensor([7])]     # Rank 1
2025-08-14T21:17:21.3471631Z     [tensor([8]), tensor([9]), tensor([10]), tensor([11])]   # Rank 2
2025-08-14T21:17:21.3472094Z     [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3
2025-08-14T21:17:21.3472556Z     >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-08-14T21:17:21.3472976Z     >>> dist.all_to_all(output, input)
2025-08-14T21:17:21.3473282Z     >>> output
2025-08-14T21:17:21.3473574Z     [tensor([0]), tensor([4]), tensor([8]), tensor([12])]    # Rank 0
2025-08-14T21:17:21.3474028Z     [tensor([1]), tensor([5]), tensor([9]), tensor([13])]    # Rank 1
2025-08-14T21:17:21.3474485Z     [tensor([2]), tensor([6]), tensor([10]), tensor([14])]   # Rank 2
2025-08-14T21:17:21.3474939Z     [tensor([3]), tensor([7]), tensor([11]), tensor([15])]   # Rank 3
2025-08-14T21:17:21.3475219Z 
2025-08-14T21:17:21.3475381Z     >>> # Essentially, it is similar to following operation:
2025-08-14T21:17:21.3475765Z     >>> scatter_list = input
2025-08-14T21:17:21.3476050Z     >>> gather_list = output
2025-08-14T21:17:21.3476375Z     >>> for i in range(world_size):
2025-08-14T21:17:21.3476844Z     >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i)
2025-08-14T21:17:21.3477195Z 
2025-08-14T21:17:21.3477282Z     >>> input
2025-08-14T21:17:21.3477577Z     tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-08-14T21:17:21.3478007Z     tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-08-14T21:17:21.3478448Z     tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-08-14T21:17:21.3478888Z     tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-08-14T21:17:21.3479254Z     >>> input_splits
2025-08-14T21:17:21.3479541Z     [2, 2, 1, 1]                                                     # Rank 0
2025-08-14T21:17:21.3479911Z     [3, 2, 2, 2]                                                     # Rank 1
2025-08-14T21:17:21.3480282Z     [2, 1, 1, 1]                                                     # Rank 2
2025-08-14T21:17:21.3480641Z     [2, 2, 2, 1]                                                     # Rank 3
2025-08-14T21:17:21.3480983Z     >>> output_splits
2025-08-14T21:17:21.3481271Z     [2, 3, 2, 2]                                                     # Rank 0
2025-08-14T21:17:21.3481626Z     [2, 2, 1, 2]                                                     # Rank 1
2025-08-14T21:17:21.3481998Z     [1, 2, 1, 2]                                                     # Rank 2
2025-08-14T21:17:21.3482376Z     [1, 2, 1, 1]                                                     # Rank 3
2025-08-14T21:17:21.3482753Z     >>> input = list(input.split(input_splits))
2025-08-14T21:17:21.3483074Z     >>> input
2025-08-14T21:17:21.3483418Z     [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])]                   # Rank 0
2025-08-14T21:17:21.3483951Z     [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1
2025-08-14T21:17:21.3484468Z     [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])]                 # Rank 2
2025-08-14T21:17:21.3485002Z     [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])]         # Rank 3
2025-08-14T21:17:21.3485422Z     >>> output = ...
2025-08-14T21:17:21.3485694Z     >>> dist.all_to_all(output, input)
2025-08-14T21:17:21.3485988Z     >>> output
2025-08-14T21:17:21.3486324Z     [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])]   # Rank 0
2025-08-14T21:17:21.3486848Z     [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])]           # Rank 1
2025-08-14T21:17:21.3487439Z     [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])]              # Rank 2
2025-08-14T21:17:21.3487975Z     [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])]                  # Rank 3
2025-08-14T21:17:21.3488299Z 
2025-08-14T21:17:21.3488475Z     >>> # Another example with tensors of torch.cfloat type.
2025-08-14T21:17:21.3488859Z     >>> input = torch.tensor(
2025-08-14T21:17:21.3489184Z     ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-08-14T21:17:21.3489544Z     ... ) + 4 * rank * (1 + 1j)
2025-08-14T21:17:21.3489870Z     >>> input = list(input.chunk(4))
2025-08-14T21:17:21.3490220Z     >>> input
2025-08-14T21:17:21.3490571Z     [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])]            # Rank 0
2025-08-14T21:17:21.3491114Z     [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])]            # Rank 1
2025-08-14T21:17:21.3491654Z     [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])]      # Rank 2
2025-08-14T21:17:21.3492221Z     [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])]    # Rank 3
2025-08-14T21:17:21.3492867Z     >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-08-14T21:17:21.3493493Z     >>> dist.all_to_all(output, input)
2025-08-14T21:17:21.3493948Z     >>> output
2025-08-14T21:17:21.3494487Z     [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])]          # Rank 0
2025-08-14T21:17:21.3495407Z     [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])]        # Rank 1
2025-08-14T21:17:21.3496320Z     [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])]        # Rank 2
2025-08-14T21:17:21.3496878Z     [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])]        # Rank 3
2025-08-14T21:17:21.3497225Z 
2025-08-14T21:17:21.3497229Z 
2025-08-14T21:17:21.3497486Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3497860Z 
2025-08-14T21:17:21.3498407Z msg = Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2.
2025-08-14T21:17:21.3499276Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.3499658Z 
2025-08-14T21:17:21.3499792Z Module ``torch.distributed.launch``.
2025-08-14T21:17:21.3500012Z 
2025-08-14T21:17:21.3500279Z ``torch.distributed.launch`` is a module that spawns up multiple distributed
2025-08-14T21:17:21.3500793Z training processes on each of the training nodes.
2025-08-14T21:17:21.3501067Z 
2025-08-14T21:17:21.3501161Z .. warning::
2025-08-14T21:17:21.3501291Z 
2025-08-14T21:17:21.3501556Z     This module is going to be deprecated in favor of :ref:`torchrun <launcher-api>`.
2025-08-14T21:17:21.3501933Z 
2025-08-14T21:17:21.3502172Z The utility can be used for single-node distributed training, in which one or
2025-08-14T21:17:21.3502767Z more processes per node will be spawned. The utility can be used for either
2025-08-14T21:17:21.3503348Z CPU training or GPU training. If the utility is used for GPU training,
2025-08-14T21:17:21.3503936Z each distributed process will be operating on a single GPU. This can achieve
2025-08-14T21:17:21.3504531Z well-improved single-node training performance. It can also be used in
2025-08-14T21:17:21.3505153Z multi-node distributed training, by spawning up multiple processes on each node
2025-08-14T21:17:21.3505778Z for well-improved multi-node distributed training performance as well.
2025-08-14T21:17:21.3506353Z This will especially be beneficial for systems with multiple Infiniband
2025-08-14T21:17:21.3506960Z interfaces that have direct-GPU support, since all of them can be utilized for
2025-08-14T21:17:21.3507456Z aggregated communication bandwidth.
2025-08-14T21:17:21.3507667Z 
2025-08-14T21:17:21.3507913Z In both cases of single-node distributed training or multi-node distributed
2025-08-14T21:17:21.3508498Z training, this utility will launch the given number of processes per node
2025-08-14T21:17:21.3509402Z (``--nproc-per-node``). If used for GPU training, this number needs to be less
2025-08-14T21:17:21.3509985Z or equal to the number of GPUs on the current system (``nproc_per_node``),
2025-08-14T21:17:21.3510533Z and each process will be operating on a single GPU from *GPU 0 to
2025-08-14T21:17:21.3510953Z GPU (nproc_per_node - 1)*.
2025-08-14T21:17:21.3511209Z 
2025-08-14T21:17:21.3511359Z **How to use this module:**
2025-08-14T21:17:21.3511643Z 
2025-08-14T21:17:21.3511816Z 1. Single-Node multi-process distributed training
2025-08-14T21:17:21.3512084Z 
2025-08-14T21:17:21.3512177Z ::
2025-08-14T21:17:21.3512354Z 
2025-08-14T21:17:21.3512629Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:21.3513183Z                YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
2025-08-14T21:17:21.3513710Z                arguments of your training script)
2025-08-14T21:17:21.3513953Z 
2025-08-14T21:17:21.3514174Z 2. Multi-Node multi-process distributed training: (e.g. two nodes)
2025-08-14T21:17:21.3514516Z 
2025-08-14T21:17:21.3514520Z 
2025-08-14T21:17:21.3514666Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)*
2025-08-14T21:17:21.3514920Z 
2025-08-14T21:17:21.3515020Z ::
2025-08-14T21:17:21.3515129Z 
2025-08-14T21:17:21.3515377Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:21.3515888Z                --nnodes=2 --node-rank=0 --master-addr="192.168.1.1"
2025-08-14T21:17:21.3516496Z                --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-08-14T21:17:21.3516982Z                and all other arguments of your training script)
2025-08-14T21:17:21.3517247Z 
2025-08-14T21:17:21.3517331Z Node 2:
2025-08-14T21:17:21.3517459Z 
2025-08-14T21:17:21.3517543Z ::
2025-08-14T21:17:21.3517663Z 
2025-08-14T21:17:21.3517898Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:21.3518411Z                --nnodes=2 --node-rank=1 --master-addr="192.168.1.1"
2025-08-14T21:17:21.3518888Z                --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-08-14T21:17:21.3519373Z                and all other arguments of your training script)
2025-08-14T21:17:21.3519637Z 
2025-08-14T21:17:21.3519810Z 3. To look up what optional arguments this module offers:
2025-08-14T21:17:21.3520079Z 
2025-08-14T21:17:21.3520175Z ::
2025-08-14T21:17:21.3520285Z 
2025-08-14T21:17:21.3520426Z     python -m torch.distributed.launch --help
2025-08-14T21:17:21.3520684Z 
2025-08-14T21:17:21.3520688Z 
2025-08-14T21:17:21.3520785Z **Important Notices:**
2025-08-14T21:17:21.3520946Z 
2025-08-14T21:17:21.3521146Z 1. This utility and multi-process distributed (single-node or
2025-08-14T21:17:21.3521692Z multi-node) GPU training currently only achieves the best performance using
2025-08-14T21:17:21.3522318Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to
2025-08-14T21:17:21.3522786Z use for GPU training.
2025-08-14T21:17:21.3522954Z 
2025-08-14T21:17:21.3523175Z 2. In your training program, you must parse the command-line argument:
2025-08-14T21:17:21.3523743Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module.
2025-08-14T21:17:21.3524324Z If your training program uses GPUs, you should ensure that your code only
2025-08-14T21:17:21.3524858Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by:
2025-08-14T21:17:21.3525177Z 
2025-08-14T21:17:21.3525285Z Parsing the local_rank argument
2025-08-14T21:17:21.3525479Z 
2025-08-14T21:17:21.3525571Z ::
2025-08-14T21:17:21.3525679Z 
2025-08-14T21:17:21.3525787Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.3526045Z     >>> import argparse
2025-08-14T21:17:21.3526351Z     >>> parser = argparse.ArgumentParser()
2025-08-14T21:17:21.3526771Z     >>> parser.add_argument("--local-rank", "--local_rank", type=int)
2025-08-14T21:17:21.3527201Z     >>> args = parser.parse_args()
2025-08-14T21:17:21.3527404Z 
2025-08-14T21:17:21.3527541Z Set your device to local rank using either
2025-08-14T21:17:21.3527835Z 
2025-08-14T21:17:21.3527924Z ::
2025-08-14T21:17:21.3528048Z 
2025-08-14T21:17:21.3528251Z     >>> torch.cuda.set_device(args.local_rank)  # before your code runs
2025-08-14T21:17:21.3528582Z 
2025-08-14T21:17:21.3528663Z or
2025-08-14T21:17:21.3528774Z 
2025-08-14T21:17:21.3528873Z ::
2025-08-14T21:17:21.3528981Z 
2025-08-14T21:17:21.3529111Z     >>> with torch.cuda.device(args.local_rank):
2025-08-14T21:17:21.3529466Z     >>>    # your code to run
2025-08-14T21:17:21.3529747Z     >>>    ...
2025-08-14T21:17:21.3529880Z 
2025-08-14T21:17:21.3529985Z .. versionchanged:: 2.0.0
2025-08-14T21:17:21.3530173Z 
2025-08-14T21:17:21.3530419Z     The launcher will passes the ``--local-rank=<rank>`` argument to your script.
2025-08-14T21:17:21.3531037Z     From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the
2025-08-14T21:17:21.3531548Z     previously used underscored ``--local_rank``.
2025-08-14T21:17:21.3531799Z 
2025-08-14T21:17:21.3532041Z     For backward compatibility, it may be necessary for users to handle both
2025-08-14T21:17:21.3532669Z     cases in their argument parsing code. This means including both ``"--local-rank"``
2025-08-14T21:17:21.3533285Z     and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is
2025-08-14T21:17:21.3533879Z     provided, the launcher will trigger an error: "error: unrecognized arguments:
2025-08-14T21:17:21.3534478Z     --local-rank=<rank>". For training code that only supports PyTorch 2.0.0+,
2025-08-14T21:17:21.3535052Z     including ``"--local-rank"`` should be sufficient.
2025-08-14T21:17:21.3535315Z 
2025-08-14T21:17:21.3535559Z 3. In your training program, you are supposed to call the following function
2025-08-14T21:17:21.3536147Z at the beginning to start the distributed backend. It is strongly recommended
2025-08-14T21:17:21.3536733Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work,
2025-08-14T21:17:21.3537263Z but ``env://`` is the one that is officially supported by this module.
2025-08-14T21:17:21.3537573Z 
2025-08-14T21:17:21.3537659Z ::
2025-08-14T21:17:21.3537764Z 
2025-08-14T21:17:21.3537968Z     >>> torch.distributed.init_process_group(backend='YOUR BACKEND',
2025-08-14T21:17:21.3538432Z     >>>                                      init_method='env://')
2025-08-14T21:17:21.3538670Z 
2025-08-14T21:17:21.3538919Z 4. In your training program, you can either use regular distributed functions
2025-08-14T21:17:21.3539523Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your
2025-08-14T21:17:21.3540075Z training program uses GPUs for training and you would like to use
2025-08-14T21:17:21.3540589Z :func:`torch.nn.parallel.DistributedDataParallel` module,
2025-08-14T21:17:21.3540996Z here is how to configure it.
2025-08-14T21:17:21.3541176Z 
2025-08-14T21:17:21.3541257Z ::
2025-08-14T21:17:21.3541372Z 
2025-08-14T21:17:21.3541561Z     >>> model = torch.nn.parallel.DistributedDataParallel(model,
2025-08-14T21:17:21.3542015Z     >>>                                                   device_ids=[args.local_rank],
2025-08-14T21:17:21.3542419Z     >>>                                                   output_device=args.local_rank)
2025-08-14T21:17:21.3542676Z 
2025-08-14T21:17:21.3542917Z Please ensure that ``device_ids`` argument is set to be the only GPU device id
2025-08-14T21:17:21.3543510Z that your code will be operating on. This is generally the local rank of the
2025-08-14T21:17:21.3544101Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``,
2025-08-14T21:17:21.3544669Z and ``output_device`` needs to be ``args.local_rank`` in order to use this
2025-08-14T21:17:21.3545090Z utility
2025-08-14T21:17:21.3545213Z 
2025-08-14T21:17:21.3545455Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable
2025-08-14T21:17:21.3546035Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with
2025-08-14T21:17:21.3546578Z ``--use-env=True``. You must adjust the subprocess example above to replace
2025-08-14T21:17:21.3547176Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher
2025-08-14T21:17:21.3547664Z will not pass ``--local-rank`` when you specify this flag.
2025-08-14T21:17:21.3547947Z 
2025-08-14T21:17:21.3548051Z .. warning::
2025-08-14T21:17:21.3548184Z 
2025-08-14T21:17:21.3548388Z     ``local_rank`` is NOT globally unique: it is only unique per process
2025-08-14T21:17:21.3548904Z     on a machine.  Thus, don't use it to decide if you should, e.g.,
2025-08-14T21:17:21.3549335Z     write to a networked filesystem.  See
2025-08-14T21:17:21.3549774Z     https://github.com/pytorch/pytorch/issues/12042 for an example of
2025-08-14T21:17:21.3550275Z     how things can go wrong if you don't do this correctly.
2025-08-14T21:17:21.3550549Z 
2025-08-14T21:17:21.3550553Z 
2025-08-14T21:17:21.3550567Z 
2025-08-14T21:17:21.3550571Z 
2025-08-14T21:17:21.3550821Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.3551189Z 
2025-08-14T21:17:21.4206099Z msg = Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361.
2025-08-14T21:17:21.4207195Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.4207582Z 
2025-08-14T21:17:21.4207841Z Creates an :class:`ShardedTensor` from local shards and the global metadata.
2025-08-14T21:17:21.4208528Z Needs to be called on all ranks in an SPMD fashion.
2025-08-14T21:17:21.4208867Z 
2025-08-14T21:17:21.4208953Z Args:
2025-08-14T21:17:21.4209530Z     local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list
2025-08-14T21:17:21.4210094Z         of shards that represent the local shards on this rank.
2025-08-14T21:17:21.4210617Z     global_size (int...):  a list, tuple, or `torch.Size` of integers defining the
2025-08-14T21:17:21.4211092Z         shape of the overall sharded tensor.
2025-08-14T21:17:21.4211321Z 
2025-08-14T21:17:21.4211430Z Keyword args:
2025-08-14T21:17:21.4211829Z     process_group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:21.4212344Z         the default process group will be used.
2025-08-14T21:17:21.4212760Z     init_rrefs (bool, optional): Whether or not to initialize
2025-08-14T21:17:21.4213246Z         :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-08-14T21:17:21.4213770Z         Need to initialize the RPC Framework if specified as ``True``.
2025-08-14T21:17:21.4214184Z         Default: ``False``.
2025-08-14T21:17:21.4214354Z 
2025-08-14T21:17:21.4214451Z Returns:
2025-08-14T21:17:21.4214713Z     A :class:`ShardedTensor` object handle on this rank
2025-08-14T21:17:21.4214982Z 
2025-08-14T21:17:21.4214986Z 
2025-08-14T21:17:21.4215072Z Examples:
2025-08-14T21:17:21.4215452Z     Suppose we want construct a sharded tensor on two ranks, global size = (10, 5),
2025-08-14T21:17:21.4215998Z     each shard have a (5, 5) local tensor, we can do it like below:
2025-08-14T21:17:21.4216316Z 
2025-08-14T21:17:21.4216402Z     on rank 0:
2025-08-14T21:17:21.4216657Z     >>> # xdoctest: +SKIP("not distributed")
2025-08-14T21:17:21.4217012Z     >>> local_shard_metadata = ShardMetadata(
2025-08-14T21:17:21.4217333Z     >>>     shard_offsets=[0, 0],
2025-08-14T21:17:21.4217627Z     >>>     shard_lengths=[5, 5],
2025-08-14T21:17:21.4217931Z     >>>     placement="rank:0/cuda:0"
2025-08-14T21:17:21.4218217Z     >>> )
2025-08-14T21:17:21.4218534Z     >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-08-14T21:17:21.4219045Z     >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-08-14T21:17:21.4219352Z 
2025-08-14T21:17:21.4219437Z     on rank 1:
2025-08-14T21:17:21.4219689Z     >>> # xdoctest: +SKIP("not distributed")
2025-08-14T21:17:21.4220036Z     >>> local_shard_metadata = ShardMetadata(
2025-08-14T21:17:21.4220358Z     >>>     shard_offsets=[5, 0],
2025-08-14T21:17:21.4220655Z     >>>     shard_lengths=[5, 5],
2025-08-14T21:17:21.4221086Z     >>>     placement="rank:1/cuda:1"
2025-08-14T21:17:21.4221387Z     >>> )
2025-08-14T21:17:21.4221689Z     >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-08-14T21:17:21.4222198Z     >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-08-14T21:17:21.4222504Z 
2025-08-14T21:17:21.4222770Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.4223141Z 
2025-08-14T21:17:21.4336076Z msg = Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835.
2025-08-14T21:17:21.4337223Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.4337608Z 
2025-08-14T21:17:21.4337873Z Initialize a ShardedTensor given only one local tensor, global sharded tensor
2025-08-14T21:17:21.4338373Z size and sharding spec on each rank.
2025-08-14T21:17:21.4338587Z 
2025-08-14T21:17:21.4338682Z Args:
2025-08-14T21:17:21.4339025Z     local_tensor (Tensor): Single tensor of local shard stored in each rank.
2025-08-14T21:17:21.4339637Z     sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`):
2025-08-14T21:17:21.4340189Z         The specification describing how to shard the Tensor.
2025-08-14T21:17:21.4340650Z     global_size (Sequence[int]): Size of the sharded tensor.
2025-08-14T21:17:21.4341295Z     process_group (ProcessGroup, optional): The process group to aggregate on.
2025-08-14T21:17:21.4341829Z         Default: None
2025-08-14T21:17:21.4342290Z     init_rrefs (bool, optional): Whether or not to initialize
2025-08-14T21:17:21.4342777Z         :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-08-14T21:17:21.4343622Z         Need to initialize the RPC Framework if specified as ``True``.
2025-08-14T21:17:21.4344164Z         Default: ``False``.
2025-08-14T21:17:21.4344337Z 
2025-08-14T21:17:21.4344436Z Returns:
2025-08-14T21:17:21.4344798Z     A :class:`ShardedTensor` sharded based on the given sharding_spec with local
2025-08-14T21:17:21.4345280Z         tensor stored in the current rank.
2025-08-14T21:17:21.4345500Z 
2025-08-14T21:17:21.4345597Z Examples:
2025-08-14T21:17:21.4345806Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.4346111Z     >>> # All tensors below are of torch.int64 type.
2025-08-14T21:17:21.4346477Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.4346871Z     >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank
2025-08-14T21:17:21.4347369Z     >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2]))
2025-08-14T21:17:21.4347780Z     >>> local_tensor
2025-08-14T21:17:21.4348062Z     tensor([[1, 2, 3, 4]]) # Rank 0
2025-08-14T21:17:21.4348349Z     tensor([[3, 4, 5, 6]]) # Rank 1
2025-08-14T21:17:21.4348641Z     >>> sharding_dim = 0
2025-08-14T21:17:21.4348932Z     >>> sharding_spec = ChunkShardingSpec(
2025-08-14T21:17:21.4349265Z             dim=sharding_dim,
2025-08-14T21:17:21.4349534Z             placements=[
2025-08-14T21:17:21.4349809Z                 "rank:0/cuda:0",
2025-08-14T21:17:21.4350092Z                 "rank:1/cuda:1",
2025-08-14T21:17:21.4350355Z             ],
2025-08-14T21:17:21.4350579Z         )
2025-08-14T21:17:21.4350831Z     >>> st = ShardedTensor._init_from_local_tensor(
2025-08-14T21:17:21.4351190Z     ...     local_tensor, sharding_spec, [2, 4]
2025-08-14T21:17:21.4351607Z     ... )
2025-08-14T21:17:21.4351820Z     >>> st
2025-08-14T21:17:21.4352026Z     ShardedTensor(
2025-08-14T21:17:21.4352287Z         ShardedTensorMetadata(
2025-08-14T21:17:21.4352583Z             shards_metadata=[
2025-08-14T21:17:21.4353026Z                 ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0),
2025-08-14T21:17:21.4353678Z                 ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1),
2025-08-14T21:17:21.4354149Z             ],
2025-08-14T21:17:21.4354391Z             size=torch.Size([2, 4])
2025-08-14T21:17:21.4354671Z     )
2025-08-14T21:17:21.4355019Z     >>> st.local_tensor()
2025-08-14T21:17:21.4355297Z     tensor([1, 2, 3, 4]) # Rank 0
2025-08-14T21:17:21.4355577Z     tensor([3, 4, 5, 6]) # Rank 1
2025-08-14T21:17:21.4355778Z 
2025-08-14T21:17:21.4356047Z Warning: This API is experimental and subject to change. It lacks of a fully across
2025-08-14T21:17:21.4356684Z          rank validations, and we only validate the local shard on the current rank.
2025-08-14T21:17:21.4357257Z          We fully rely on the user to ensure local tensor is sharded based on the
2025-08-14T21:17:21.4357693Z          sharding spec.
2025-08-14T21:17:21.4357864Z 
2025-08-14T21:17:21.4358114Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.4358478Z 
2025-08-14T21:17:21.4359169Z msg = Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076.
2025-08-14T21:17:21.4360211Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.4360600Z 
2025-08-14T21:17:21.4360849Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support
2025-08-14T21:17:21.4361313Z single local shard.
2025-08-14T21:17:21.4361459Z 
2025-08-14T21:17:21.4361690Z If ``resharding_spec`` is same as the original one, this becomes a no-op.
2025-08-14T21:17:21.4362259Z If only ``resharding_spec`` shares the same sharding dim with the original one,
2025-08-14T21:17:21.4362821Z we swap local shards directly.
2025-08-14T21:17:21.4363275Z For more generic cases, we merge different shards across different ranks and split
2025-08-14T21:17:21.4363911Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API.
2025-08-14T21:17:21.4364277Z 
2025-08-14T21:17:21.4364359Z Args:
2025-08-14T21:17:21.4364769Z     resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The
2025-08-14T21:17:21.4365345Z         specification describing how the tensor is sharded.
2025-08-14T21:17:21.4365622Z 
2025-08-14T21:17:21.4365704Z Returns:
2025-08-14T21:17:21.4366028Z     A :class:`ShardedTensor` object whose local shards are resharded.
2025-08-14T21:17:21.4366345Z 
2025-08-14T21:17:21.4366442Z Examples:
2025-08-14T21:17:21.4366666Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.4366943Z     >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:21.4367347Z     >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank
2025-08-14T21:17:21.4367765Z     >>> tensor = torch.stack([tensor, tensor])
2025-08-14T21:17:21.4368072Z     >>> tensor
2025-08-14T21:17:21.4368321Z     tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0
2025-08-14T21:17:21.4368667Z     tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1
2025-08-14T21:17:21.4368999Z     tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2
2025-08-14T21:17:21.4369350Z     tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3
2025-08-14T21:17:21.4369684Z     >>> sharding_dim = 0
2025-08-14T21:17:21.4369953Z     >>> spec = ChunkShardingSpec(
2025-08-14T21:17:21.4370265Z             dim=sharding_dim,
2025-08-14T21:17:21.4370548Z             placements=[
2025-08-14T21:17:21.4370798Z                 "rank:0/cuda:0",
2025-08-14T21:17:21.4371106Z                 "rank:1/cuda:1",
2025-08-14T21:17:21.4371376Z                 "rank:2/cuda:2",
2025-08-14T21:17:21.4371660Z                 "rank:3/cuda:3",
2025-08-14T21:17:21.4371932Z             ],
2025-08-14T21:17:21.4372142Z         )
2025-08-14T21:17:21.4372368Z     >>> current_offsets = [0] * 2
2025-08-14T21:17:21.4372678Z     >>> current_offsets[0] = rank * 2
2025-08-14T21:17:21.4372992Z     >>> shard_metadata = ShardMetadata(
2025-08-14T21:17:21.4373369Z             shard_offsets=copy.deepcopy(current_offsets),
2025-08-14T21:17:21.4373746Z             shard_sizes=tensor.size(),
2025-08-14T21:17:21.4374095Z             placement=spec.placements[rank],
2025-08-14T21:17:21.4374402Z         )
2025-08-14T21:17:21.4374625Z     >>> local_shards = [
2025-08-14T21:17:21.4374885Z             Shard(
2025-08-14T21:17:21.4375185Z                 tensor=tensor,
2025-08-14T21:17:21.4375484Z                 metadata=shard_metadata,
2025-08-14T21:17:21.4375790Z             )
2025-08-14T21:17:21.4375995Z         ]
2025-08-14T21:17:21.4376349Z     >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size())
2025-08-14T21:17:21.4376800Z     >>> sharding_dim = 1
2025-08-14T21:17:21.4377082Z     >>> resharding_spec = ChunkShardingSpec(
2025-08-14T21:17:21.4377428Z             dim=sharding_dim,
2025-08-14T21:17:21.4377713Z             placements=[
2025-08-14T21:17:21.4377963Z                 "rank:0/cuda:0",
2025-08-14T21:17:21.4378244Z                 "rank:1/cuda:1",
2025-08-14T21:17:21.4378521Z                 "rank:2/cuda:2",
2025-08-14T21:17:21.4378787Z                 "rank:3/cuda:3",
2025-08-14T21:17:21.4379054Z             ],
2025-08-14T21:17:21.4379268Z         )
2025-08-14T21:17:21.4379489Z     >>> st.reshard(resharding_spec)
2025-08-14T21:17:21.4379811Z     >>> tensor = st.local_shards()[0].tensor
2025-08-14T21:17:21.4380123Z     >>> tensor
2025-08-14T21:17:21.4380400Z     tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0
2025-08-14T21:17:21.4380778Z     tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1
2025-08-14T21:17:21.4381166Z     tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2
2025-08-14T21:17:21.4381562Z     tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3
2025-08-14T21:17:21.4381851Z 
2025-08-14T21:17:21.4382105Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.4382520Z 
2025-08-14T21:17:21.4559390Z msg = Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12.
2025-08-14T21:17:21.4560404Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.4560785Z 
2025-08-14T21:17:21.4561017Z Representation of a sharding plan, describes how to shard a module
2025-08-14T21:17:21.4561632Z across hosts. `plan` is used to shard module parameters according to the spec provided,
2025-08-14T21:17:21.4562301Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output
2025-08-14T21:17:21.4562957Z layout of a module with a spec, and when to convert back to data parallel fashion.
2025-08-14T21:17:21.4563321Z 
2025-08-14T21:17:21.4563416Z Args:
2025-08-14T21:17:21.4563796Z     plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`,
2025-08-14T21:17:21.4564367Z           :class:`torch.distributed._shard.sharder.Sharder`]):
2025-08-14T21:17:21.4564920Z         a dict describes how to shard a module, there're currently two ways to shard a module:
2025-08-14T21:17:21.4565566Z             1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of
2025-08-14T21:17:21.4566057Z                a parameter to a `ShardingSpec`.
2025-08-14T21:17:21.4566555Z             2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module
2025-08-14T21:17:21.4567039Z                to a `Sharder` object.
2025-08-14T21:17:21.4567568Z     output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional):
2025-08-14T21:17:21.4568287Z         a dict specifies the layout of a module's output which produces a ShardedTensor,
2025-08-14T21:17:21.4568903Z         keyed by the name of module to ShardingSpec("" in key means the root module).
2025-08-14T21:17:21.4569375Z         Default: `None`
2025-08-14T21:17:21.4569783Z     return_local_tensor (List[str], optional): a list of string, each element enables
2025-08-14T21:17:21.4570399Z         a module's sharded output to be returned as a Tensor from its local shards to
2025-08-14T21:17:21.4571011Z         ensure further processing in a data parallel fashion. ("" in list means the
2025-08-14T21:17:21.4571475Z         root module).
2025-08-14T21:17:21.4571711Z         Default: None
2025-08-14T21:17:21.4571952Z Example:
2025-08-14T21:17:21.4572499Z   Suppose we want to shard a module with two linear layers and then run it with DDP, we also
2025-08-14T21:17:21.4573182Z   want to convert the output of the second linear layer back to DDP, we can do it as follows:
2025-08-14T21:17:21.4573597Z 
2025-08-14T21:17:21.4573770Z     >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d)
2025-08-14T21:17:21.4574168Z     >>> class MyModule(nn.Module):
2025-08-14T21:17:21.4574494Z     >>>     def __init__(self) -> None:
2025-08-14T21:17:21.4574799Z     >>>        super().__init__()
2025-08-14T21:17:21.4575096Z     >>>        self.fc1 = nn.Linear()
2025-08-14T21:17:21.4575404Z     >>>        self.gelu = nn.GELU()
2025-08-14T21:17:21.4575699Z     >>>        self.fc2 = nn.Linear()
2025-08-14T21:17:21.4576005Z     >>>        self.relu = nn.Linear()
2025-08-14T21:17:21.4576296Z     >>>
2025-08-14T21:17:21.4576506Z     >>>     def forward(self, input):
2025-08-14T21:17:21.4576883Z     >>>         return self.relu(self.fc2(self.gelu(self.fc1(input))))
2025-08-14T21:17:21.4577169Z 
2025-08-14T21:17:21.4577188Z 
2025-08-14T21:17:21.4577315Z     >>> # xdoctest: +SKIP("Undefined spec1, spec2)
2025-08-14T21:17:21.4577672Z     >>> sharding_plan = ShardingPlan(
2025-08-14T21:17:21.4577962Z     >>>    plan={
2025-08-14T21:17:21.4578206Z     >>>        "fc1.weight": spec1,
2025-08-14T21:17:21.4578510Z     >>>        "fc2.weight": spec2
2025-08-14T21:17:21.4578778Z     >>>    },
2025-08-14T21:17:21.4579051Z     >>>    output_plan={
2025-08-14T21:17:21.4579320Z     >>>        "fc2": output_spec
2025-08-14T21:17:21.4579629Z     >>>    },
2025-08-14T21:17:21.4579872Z     >>>    return_local_tensor=["fc2"]
2025-08-14T21:17:21.4580174Z     >>> )
2025-08-14T21:17:21.4580293Z 
2025-08-14T21:17:21.4580542Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.4580924Z 
2025-08-14T21:17:21.5539598Z msg = Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72.
2025-08-14T21:17:21.5541790Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.5542503Z 
2025-08-14T21:17:21.5542700Z Run post-localSGD algorithm.
2025-08-14T21:17:21.5543055Z 
2025-08-14T21:17:21.5543475Z This DDP communication hook is used for running post-localSGD algorithm,
2025-08-14T21:17:21.5544370Z by combining with a model averaging component (e.g.,
2025-08-14T21:17:21.5545415Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`)
2025-08-14T21:17:21.5546361Z that runs after the optimizer step.
2025-08-14T21:17:21.5546740Z 
2025-08-14T21:17:21.5546882Z Args:
2025-08-14T21:17:21.5547502Z     state (PostLocalSGDState): State information to run post-localSGD.
2025-08-14T21:17:21.5548607Z         Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD.
2025-08-14T21:17:21.5550101Z     bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-08-14T21:17:21.5551693Z         Note that since DDP comm hook only supports single process single device mode,
2025-08-14T21:17:21.5552636Z         only exactly one tensor is stored in this bucket.
2025-08-14T21:17:21.5553125Z 
2025-08-14T21:17:21.5553283Z Returns:
2025-08-14T21:17:21.5553977Z     Future handler of the communication, which updates the gradients in place.
2025-08-14T21:17:21.5554684Z 
2025-08-14T21:17:21.5554872Z Example::
2025-08-14T21:17:21.5555254Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.5556010Z     >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup,
2025-08-14T21:17:21.5556939Z                               start_localSGD_iter=10)
2025-08-14T21:17:21.5557690Z     >>> ddp_model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:21.5558840Z     >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``.
2025-08-14T21:17:21.5560697Z     >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module.
2025-08-14T21:17:21.5561588Z 
2025-08-14T21:17:21.5562084Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.5562767Z 
2025-08-14T21:17:21.5594198Z msg = Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342.
2025-08-14T21:17:21.5596382Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.5597072Z 
2025-08-14T21:17:21.5597249Z Implement PowerSGD algorithm.
2025-08-14T21:17:21.5597594Z 
2025-08-14T21:17:21.5598007Z This DDP communication hook implements PowerSGD gradient compression
2025-08-14T21:17:21.5599070Z algorithm described in the `paper <https://arxiv.org/abs/1905.13727>`_.
2025-08-14T21:17:21.5600135Z Once gradient tensors are aggregated across all workers, this hook applies
2025-08-14T21:17:21.5600994Z compression as follows:
2025-08-14T21:17:21.5601279Z 
2025-08-14T21:17:21.5602114Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups:
2025-08-14T21:17:21.5603161Z 
2025-08-14T21:17:21.5603966Z     1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth.
2025-08-14T21:17:21.5605002Z 
2025-08-14T21:17:21.5605993Z     1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases).
2025-08-14T21:17:21.5607123Z 
2025-08-14T21:17:21.5607320Z 2. Handles uncompressed tensors:
2025-08-14T21:17:21.5607701Z 
2025-08-14T21:17:21.5608638Z     2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression;
2025-08-14T21:17:21.5610013Z 
2025-08-14T21:17:21.5610641Z     2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor.
2025-08-14T21:17:21.5611533Z 
2025-08-14T21:17:21.5611977Z 3. Handles the tensors that should be compressed by PowerSGD compression:
2025-08-14T21:17:21.5612645Z 
2025-08-14T21:17:21.5613089Z     3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M,
2025-08-14T21:17:21.5614347Z     such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized;
2025-08-14T21:17:21.5615097Z 
2025-08-14T21:17:21.5615373Z     3.2. Computes each P in Ps, which is equal to MQ;
2025-08-14T21:17:21.5615853Z 
2025-08-14T21:17:21.5616062Z     3.3. Allreduces Ps as a batch;
2025-08-14T21:17:21.5616432Z 
2025-08-14T21:17:21.5616642Z     3.4. Orthogonalizes each P in Ps;
2025-08-14T21:17:21.5617053Z 
2025-08-14T21:17:21.5617394Z     3.5. Computes each Q in Qs, which is approximately equal to M^TP;
2025-08-14T21:17:21.5617974Z 
2025-08-14T21:17:21.5618176Z     3.6. Allreduces Qs as a batch;
2025-08-14T21:17:21.5618562Z 
2025-08-14T21:17:21.5619146Z     3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T.
2025-08-14T21:17:21.5619920Z 
2025-08-14T21:17:21.5620669Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations.
2025-08-14T21:17:21.5621967Z This not only gives the user more control over the tradeoff between speedup and accuracy,
2025-08-14T21:17:21.5623386Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers.
2025-08-14T21:17:21.5624315Z 
2025-08-14T21:17:21.5624459Z Args:
2025-08-14T21:17:21.5625385Z     state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc.
2025-08-14T21:17:21.5627020Z         To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter``
2025-08-14T21:17:21.5628090Z         and ``min_compression_rate``.
2025-08-14T21:17:21.5629510Z     bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-08-14T21:17:21.5630943Z         Note that since DDP comm hook only supports single process single device mode,
2025-08-14T21:17:21.5631958Z         only exactly one tensor is stored in this bucket.
2025-08-14T21:17:21.5632362Z 
2025-08-14T21:17:21.5632511Z Returns:
2025-08-14T21:17:21.5633082Z     Future handler of the communication, which updates the gradients in place.
2025-08-14T21:17:21.5633727Z 
2025-08-14T21:17:21.5633906Z Example::
2025-08-14T21:17:21.5634268Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.5635036Z     >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1,
2025-08-14T21:17:21.5635982Z                               start_powerSGD_iter=10, min_compression_rate=0.5)
2025-08-14T21:17:21.5636700Z     >>> ddp_model.register_comm_hook(state, powerSGD_hook)
2025-08-14T21:17:21.5637153Z 
2025-08-14T21:17:21.5637602Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.5638280Z 
2025-08-14T21:17:21.5645133Z msg = Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38.
2025-08-14T21:17:21.5647146Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.5647814Z 
2025-08-14T21:17:21.5648145Z Averages parameters periodically after the warm-up stage.
2025-08-14T21:17:21.5648958Z 
2025-08-14T21:17:21.5649425Z This can be used for running `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-08-14T21:17:21.5650452Z by running :class:`~torch.nn.DistributedDataParallel` (DDP)
2025-08-14T21:17:21.5651420Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`.
2025-08-14T21:17:21.5652069Z 
2025-08-14T21:17:21.5652245Z Args:
2025-08-14T21:17:21.5652744Z     period (int): The number of steps per model averaging.
2025-08-14T21:17:21.5653697Z                   Usually the period should be greater than ``1`` to reduce the communication cost.
2025-08-14T21:17:21.5654539Z                   Otherwise, only DDP needs to be used.
2025-08-14T21:17:21.5655303Z     warmup_steps (int): The number of warm-up steps. During this stage,
2025-08-14T21:17:21.5656037Z                         model averaging is skipped.
2025-08-14T21:17:21.5656716Z     process_group: The process group to be used for all-reduce.
2025-08-14T21:17:21.5657490Z                    If ``None``, the default process group, which
2025-08-14T21:17:21.5658244Z                    is created by :func:`torch.distributed.init_process_group`,
2025-08-14T21:17:21.5658968Z                    will be used. (default: ``None``)
2025-08-14T21:17:21.5659388Z 
2025-08-14T21:17:21.5659551Z Example::
2025-08-14T21:17:21.5659775Z 
2025-08-14T21:17:21.5659993Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.5660571Z     >>> import torch
2025-08-14T21:17:21.5661027Z     >>> import torch.distributed as dist
2025-08-14T21:17:21.5662006Z     >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD
2025-08-14T21:17:21.5663294Z     >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-08-14T21:17:21.5664194Z     >>> import torch.nn as nn
2025-08-14T21:17:21.5664634Z     >>>
2025-08-14T21:17:21.5665092Z     >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-08-14T21:17:21.5665783Z     >>> torch.cuda.set_device(rank)
2025-08-14T21:17:21.5666345Z     >>> module = nn.Linear(1, 1, bias=False).cuda()
2025-08-14T21:17:21.5667004Z     >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:21.5667687Z     >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:21.5668263Z     >>> )
2025-08-14T21:17:21.5668724Z     >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:21.5669695Z     >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-08-14T21:17:21.5670927Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:21.5671696Z     >>>
2025-08-14T21:17:21.5672338Z     >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-08-14T21:17:21.5673209Z     >>> # After 100 steps, run model averaging every 4 steps.
2025-08-14T21:17:21.5674206Z     >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:21.5675439Z     >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-08-14T21:17:21.5676276Z     >>> for step in range(0, 200):
2025-08-14T21:17:21.5676828Z     >>>    optimizer.zero_grad()
2025-08-14T21:17:21.5677370Z     >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:21.5677914Z     >>>    loss.backward()
2025-08-14T21:17:21.5678392Z     >>>    optimizer.step()
2025-08-14T21:17:21.5679023Z     >>>    # Will average model parameters globally every 4 steps. Thus,
2025-08-14T21:17:21.5679865Z     >>>    # inter-node communication only occurs every 4 iterations after
2025-08-14T21:17:21.5680611Z     >>>    # the initial ``warmup_steps`` period.
2025-08-14T21:17:21.5681306Z     >>>    averager.average_parameters(model.parameters())
2025-08-14T21:17:21.5681789Z 
2025-08-14T21:17:21.5682253Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.5682924Z 
2025-08-14T21:17:21.5684579Z msg = Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19.
2025-08-14T21:17:21.5687059Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.5687743Z 
2025-08-14T21:17:21.5688310Z Runs hierarchical model averaging (`hierarchical SGD <https://arxiv.org/pdf/2010.12998.pdf>`_).
2025-08-14T21:17:21.5689075Z 
2025-08-14T21:17:21.5689572Z Process groups of different sizes are organized in a hierarchy, and they average parameters
2025-08-14T21:17:21.5690646Z by using different periods concurrently after the warm-up stage.
2025-08-14T21:17:21.5691889Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`
2025-08-14T21:17:21.5693430Z that supports `post-local SGD <https://arxiv.org/abs/1808.07217>`_, which essentially only supports
2025-08-14T21:17:21.5694812Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine
2025-08-14T21:17:21.5696256Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`.
2025-08-14T21:17:21.5697655Z Similarly, the process groups within this class do not have such an intra-machine process
2025-08-14T21:17:21.5698872Z subgroup, which should be embedded by the post-local SGD communication hook instead.
2025-08-14T21:17:21.5699544Z 
2025-08-14T21:17:21.5699685Z Args:
2025-08-14T21:17:21.5700351Z     period_group_size_dict: An ordered dict mapping keys of model averaging period to
2025-08-14T21:17:21.5701396Z                             process group size, used for initializing process groups of
2025-08-14T21:17:21.5702394Z                             different sizes in a hierarchy to average parameters concurrently.
2025-08-14T21:17:21.5703404Z                             Particularly, at each iteration, there will be at most a single
2025-08-14T21:17:21.5704444Z                             process group that runs averaging -- the period of such group should
2025-08-14T21:17:21.5705433Z                             have the largest period which the current step can be divided by.
2025-08-14T21:17:21.5706244Z                             For example, if the dict has three keys: 2, 4, and 8,
2025-08-14T21:17:21.5707107Z                             then this means totally three process groups will be created to
2025-08-14T21:17:21.5708048Z                             average parameters every 2, 4, and 8 iterations, respectively.
2025-08-14T21:17:21.5709513Z                             At the 4th iteration, only the second process group will run
2025-08-14T21:17:21.5710428Z                             averaging, because the first process group should be a
2025-08-14T21:17:21.5711359Z                             subset of the second process group, and no need to execute the first
2025-08-14T21:17:21.5712271Z                             process group redundantly.
2025-08-14T21:17:21.5713045Z                             On the other hand, the third process group can only be triggered
2025-08-14T21:17:21.5713955Z                             every 8 iterations, so it will not be triggered at the 4th iteration.
2025-08-14T21:17:21.5715040Z     warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped.
2025-08-14T21:17:21.5716571Z     process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging.
2025-08-14T21:17:21.5717845Z                                             If ``None``, the default process group, which is created
2025-08-14T21:17:21.5718744Z                                             by :func:`torch.distributed.init_process_group`, will be used.
2025-08-14T21:17:21.5719511Z                                             (default: ``None``)
2025-08-14T21:17:21.5719951Z 
2025-08-14T21:17:21.5720132Z Example::
2025-08-14T21:17:21.5720563Z     >>> # xdoctest: +SKIP('undefined rank')
2025-08-14T21:17:21.5721168Z     >>> from collections import OrderedDict
2025-08-14T21:17:21.5722531Z     >>> import torch
2025-08-14T21:17:21.5723135Z     >>> import torch.distributed as dist
2025-08-14T21:17:21.5724052Z     >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-08-14T21:17:21.5724973Z     >>>     PostLocalSGDState,
2025-08-14T21:17:21.5725468Z     >>>     post_localSGD_hook,
2025-08-14T21:17:21.5725920Z     >>> )
2025-08-14T21:17:21.5726718Z     >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD
2025-08-14T21:17:21.5727751Z     >>> import torch.nn as nn
2025-08-14T21:17:21.5728222Z     >>>
2025-08-14T21:17:21.5728684Z     >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-08-14T21:17:21.5729366Z     >>> torch.cuda.set_device(rank)
2025-08-14T21:17:21.5729973Z     >>> module = nn.Linear(1, 1, bias=False).to(rank)
2025-08-14T21:17:21.5730673Z     >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:21.5731378Z     >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:21.5731978Z     >>> )
2025-08-14T21:17:21.5732439Z     >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:21.5733289Z     >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4.
2025-08-14T21:17:21.5734146Z     >>> subgroup, _ = dist.new_subgroups()
2025-08-14T21:17:21.5735077Z     >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100)
2025-08-14T21:17:21.5736107Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:21.5736729Z     >>>
2025-08-14T21:17:21.5737446Z     >>> # Average parameters among each group of 8 processes every 4 iterations, and among all
2025-08-14T21:17:21.5738398Z     >>> # the 16 processes every 16 iterations.
2025-08-14T21:17:21.5739136Z     >>> averager = hierarchicalSGD.HierarchicalModelAverager(
2025-08-14T21:17:21.5740088Z     >>>     period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100)
2025-08-14T21:17:21.5741346Z     >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:21.5742642Z     >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-08-14T21:17:21.5743621Z     >>> # After 100 steps, run model averaging at two levels.
2025-08-14T21:17:21.5744247Z     >>> for step in range(0, 200):
2025-08-14T21:17:21.5744742Z     >>>    optimizer.zero_grad()
2025-08-14T21:17:21.5745218Z     >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:21.5745764Z     >>>    loss.backward()
2025-08-14T21:17:21.5746435Z     >>>    optimizer.step()
2025-08-14T21:17:21.5746993Z     >>>    # Average parameters after ``optimizer.step()``.
2025-08-14T21:17:21.5747984Z     >>>    # Thus, the inter-node communication only occurs periodically after ``warmup_steps``.
2025-08-14T21:17:21.5749021Z     >>>    averager.average_parameters(model.parameters())
2025-08-14T21:17:21.5749525Z 
2025-08-14T21:17:21.5749713Z .. warning ::
2025-08-14T21:17:21.5750388Z     The last group size in the dict must be the size of the provided ``process_group``,
2025-08-14T21:17:21.5751643Z     which indicates model averaging at the highest level of the hierarchy.
2025-08-14T21:17:21.5752850Z     If ``process_group`` is not provided, then the last group size should be equal to the world size.
2025-08-14T21:17:21.5753640Z 
2025-08-14T21:17:21.5753813Z .. warning ::
2025-08-14T21:17:21.5754408Z     `HierarchicalModelAverager` is experimental and subject to change.
2025-08-14T21:17:21.5754983Z 
2025-08-14T21:17:21.5755424Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.5756068Z 
2025-08-14T21:17:21.6207388Z msg = Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40.
2025-08-14T21:17:21.6208509Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6221516Z 
2025-08-14T21:17:21.6221989Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint
2025-08-14T21:17:21.6222971Z on the coordinator rank, and then broadcast and shard each tensor to all ranks.
2025-08-14T21:17:21.6223355Z 
2025-08-14T21:17:21.6223520Z . N.B. Intended to be used with DynamicMetaLoadPlanner
2025-08-14T21:17:21.6223870Z 
2025-08-14T21:17:21.6223981Z .. warning::
2025-08-14T21:17:21.6224293Z     Current implementation only supports loading Tensors.
2025-08-14T21:17:21.6224640Z 
2025-08-14T21:17:21.6224766Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6225108Z >>> sd = {"mode": model}
2025-08-14T21:17:21.6225410Z >>> dcp.load(
2025-08-14T21:17:21.6225622Z >>>    sd,
2025-08-14T21:17:21.6225949Z >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-08-14T21:17:21.6226348Z >>>    planner=DynamicMetaLoadPlanner(),
2025-08-14T21:17:21.6226748Z >>>    checkpoint_id="path_to_model.pt"
2025-08-14T21:17:21.6227063Z >>> )
2025-08-14T21:17:21.6227181Z 
2025-08-14T21:17:21.6227494Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6227869Z 
2025-08-14T21:17:21.6228652Z msg = Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151.
2025-08-14T21:17:21.6229816Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6230211Z 
2025-08-14T21:17:21.6230642Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict,
2025-08-14T21:17:21.6231590Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a
2025-08-14T21:17:21.6232216Z metadata file, like Torch Save files.
2025-08-14T21:17:21.6232434Z 
2025-08-14T21:17:21.6232614Z . N.B. Intended to be used with BroadcastingTorchSaveReader
2025-08-14T21:17:21.6232977Z 
2025-08-14T21:17:21.6233071Z .. warning::
2025-08-14T21:17:21.6233386Z     Current implementation only supports loading Tensors.
2025-08-14T21:17:21.6233731Z 
2025-08-14T21:17:21.6233861Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6234167Z >>> sd = {"mode": model}
2025-08-14T21:17:21.6234484Z >>> dcp.load(
2025-08-14T21:17:21.6234709Z >>>    sd,
2025-08-14T21:17:21.6234974Z >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-08-14T21:17:21.6235423Z >>>    planner=DynamicMetaLoadPlanner(),
2025-08-14T21:17:21.6235769Z >>>    checkpoint_id="path_to_model.pt"
2025-08-14T21:17:21.6236120Z >>> )
2025-08-14T21:17:21.6236249Z 
2025-08-14T21:17:21.6236681Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6237070Z 
2025-08-14T21:17:21.6317872Z msg = Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221.
2025-08-14T21:17:21.6318946Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6319330Z 
2025-08-14T21:17:21.6319559Z Load a state_dict in conjunction with FSDP sharded optimizer state.
2025-08-14T21:17:21.6319880Z 
2025-08-14T21:17:21.6320044Z This is the current recommended way to checkpoint FSDP.
2025-08-14T21:17:21.6320423Z >>> # xdoctest: +SKIP
2025-08-14T21:17:21.6320738Z >>> import torch.distributed.checkpoint as dist_cp
2025-08-14T21:17:21.6321080Z >>> # Save
2025-08-14T21:17:21.6321312Z >>> model: torch.nn.Model
2025-08-14T21:17:21.6321610Z >>> optim_params = model.parameters()
2025-08-14T21:17:21.6321969Z >>> optim = torch.optim.SGD(optim_params, lr=0.01)
2025-08-14T21:17:21.6322315Z >>> # Save
2025-08-14T21:17:21.6322665Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT):
2025-08-14T21:17:21.6323098Z >>>     state_dict = {
2025-08-14T21:17:21.6323403Z >>>         "optimizer": FSDP.optim_state_dict(model, optim),
2025-08-14T21:17:21.6323782Z >>>         "model": model.state_dict()
2025-08-14T21:17:21.6324169Z >>>     }
2025-08-14T21:17:21.6324384Z >>>     dist_cp.save_state_dict(
2025-08-14T21:17:21.6324739Z >>>         state_dict=optim_state,
2025-08-14T21:17:21.6325126Z >>>         storage_writer=dist_cp.FileSystemWriter("checkpoint"),
2025-08-14T21:17:21.6325545Z >>>         planner=dist_cp.DefaultSavePlanner(),
2025-08-14T21:17:21.6325880Z >>>     )
2025-08-14T21:17:21.6326091Z >>>
2025-08-14T21:17:21.6326280Z >>> # Load
2025-08-14T21:17:21.6326632Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT):
2025-08-14T21:17:21.6327110Z >>>     model_state_dict = model_tp.state_dict()
2025-08-14T21:17:21.6327455Z >>>     checkpoint = {
2025-08-14T21:17:21.6327720Z >>>         "model": model_state_dict
2025-08-14T21:17:21.6328016Z >>>     }
2025-08-14T21:17:21.6328241Z >>>     dist_cp.load_state_dict(
2025-08-14T21:17:21.6328533Z >>>         state_dict=checkpoint,
2025-08-14T21:17:21.6328930Z >>>         storage_reader=dist_cp.FileSystemReader(checkpoint_file),
2025-08-14T21:17:21.6329372Z >>>         planner=dist_cp.DefaultLoadPlanner(),
2025-08-14T21:17:21.6329710Z >>>     )
2025-08-14T21:17:21.6329989Z >>>     model.load_state_dict(checkpoint["model_state"])
2025-08-14T21:17:21.6330341Z >>>
2025-08-14T21:17:21.6330621Z >>>     optim_state = dist_cp.load_sharded_optimizer_state_dict(
2025-08-14T21:17:21.6331019Z >>>         model_state_dict,
2025-08-14T21:17:21.6331324Z >>>         optimizer_key="optimizer",
2025-08-14T21:17:21.6331722Z >>>         storage_reader=dist_cp.FileSystemReader("checkpoint"),
2025-08-14T21:17:21.6332088Z >>>     )
2025-08-14T21:17:21.6332292Z >>>
2025-08-14T21:17:21.6332563Z >>>     flattened_osd = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:21.6332937Z >>>        model, optim, optim_state["optimizer"]
2025-08-14T21:17:21.6333263Z >>>     )
2025-08-14T21:17:21.6333465Z >>>
2025-08-14T21:17:21.6333690Z >>>     optim.load_state_dict(flattened_osd)
2025-08-14T21:17:21.6333930Z 
2025-08-14T21:17:21.6334179Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6334549Z 
2025-08-14T21:17:21.6349654Z msg = Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122.
2025-08-14T21:17:21.6350947Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6351328Z 
2025-08-14T21:17:21.6351693Z Abstract class defining the protocol used by save_state_dict to plan the save process.
2025-08-14T21:17:21.6352115Z 
2025-08-14T21:17:21.6352588Z SavePlanners are stateful objects that can be used to customize the whole save process.
2025-08-14T21:17:21.6353019Z 
2025-08-14T21:17:21.6353300Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-08-14T21:17:21.6353827Z will be visible to the whole process.
2025-08-14T21:17:21.6354044Z 
2025-08-14T21:17:21.6354321Z A planner subclass can expect the following sequence of calls during save_state_dict:
2025-08-14T21:17:21.6354734Z 
2025-08-14T21:17:21.6354863Z 1) set_up_planner - called on all ranks.
2025-08-14T21:17:21.6355231Z     Signals the start of a checkpoint save.
2025-08-14T21:17:21.6355462Z 
2025-08-14T21:17:21.6355597Z 2) create_local_plan - called on all ranks.
2025-08-14T21:17:21.6356106Z     Process the state_dict and produces a `SavePlan` that will be sent for global planning.
2025-08-14T21:17:21.6356613Z 
2025-08-14T21:17:21.6356798Z 3) create_global_plan - called on the coordinator rank only.
2025-08-14T21:17:21.6357344Z     Takes the SavePlan from all ranks and make any global decision.
2025-08-14T21:17:21.6357812Z 
2025-08-14T21:17:21.6358115Z 4) finish_plan - called on all ranks.
2025-08-14T21:17:21.6358724Z     This gives each rank a chance to adjust to global planning decisions.
2025-08-14T21:17:21.6359059Z 
2025-08-14T21:17:21.6359228Z 5) resolve_data - called multiple times on each rank
2025-08-14T21:17:21.6359696Z     Lookups a value on the `state_dict` for the storage layer to write.
2025-08-14T21:17:21.6360027Z 
2025-08-14T21:17:21.6360381Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as
2025-08-14T21:17:21.6361042Z most changes can be expressed by changes in a single method.
2025-08-14T21:17:21.6361335Z 
2025-08-14T21:17:21.6361474Z There are 3 usual patterns of extension:
2025-08-14T21:17:21.6361700Z 
2025-08-14T21:17:21.6361953Z Rewriting state_dict. This is the simplest way to extend the save process as it
2025-08-14T21:17:21.6362558Z doesn't requite understanding the intrincacies of how SavePlan works:
2025-08-14T21:17:21.6362899Z 
2025-08-14T21:17:21.6363031Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6363377Z >>> class RenamePlanner(DefaultSavePlanner):
2025-08-14T21:17:21.6363729Z >>>     def set_up_planner(
2025-08-14T21:17:21.6364000Z >>>         self,
2025-08-14T21:17:21.6364246Z >>>         state_dict: STATE_DICT_TYPE,
2025-08-14T21:17:21.6364597Z >>>         storage_meta: Optional[StorageMeta],
2025-08-14T21:17:21.6364948Z >>>         is_coordinator: bool,
2025-08-14T21:17:21.6365243Z >>>     ) -> None:
2025-08-14T21:17:21.6365489Z >>> # prefix all keys with `foo_``
2025-08-14T21:17:21.6365987Z >>>         super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator)
2025-08-14T21:17:21.6366388Z 
2025-08-14T21:17:21.6366732Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted
2025-08-14T21:17:21.6367179Z 
2025-08-14T21:17:21.6367292Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6367643Z >>> class FP16Planner(DefaultSavePlanner):
2025-08-14T21:17:21.6367997Z >>>     def create_local_plan(self):
2025-08-14T21:17:21.6368330Z >>>         plan = super().create_local_plan()
2025-08-14T21:17:21.6368649Z >>>         for p in plan:
2025-08-14T21:17:21.6368944Z >>>             if p.tensor_data is not None:
2025-08-14T21:17:21.6369329Z >>>                 p.tensor_data.properties.dtype = torch.float16
2025-08-14T21:17:21.6369686Z >>>         return plan
2025-08-14T21:17:21.6369932Z >>>
2025-08-14T21:17:21.6370162Z >>>     def resolve_data(self, write_item):
2025-08-14T21:17:21.6370505Z >>>         item = super().resolve_data(write_item)
2025-08-14T21:17:21.6371018Z >>>         return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16)
2025-08-14T21:17:21.6371419Z 
2025-08-14T21:17:21.6371761Z Using the global planning step to make central decisions that can't be made individually by each rank
2025-08-14T21:17:21.6372218Z 
2025-08-14T21:17:21.6372342Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6372743Z >>> from itertools import zip_longest
2025-08-14T21:17:21.6373075Z >>> from dataclasses import replace
2025-08-14T21:17:21.6373462Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner):
2025-08-14T21:17:21.6374009Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0
2025-08-14T21:17:21.6374539Z >>> # This sample doesn't handle ShardedTensors
2025-08-14T21:17:21.6374915Z >>>     def create_global_plan(self, all_plans):
2025-08-14T21:17:21.6375310Z >>>         iters = [iter(all_plans[0].items)] * len(all_plans)
2025-08-14T21:17:21.6375673Z >>>         items_per_rank = [
2025-08-14T21:17:21.6375999Z >>>             [item for item in items if item is not None]
2025-08-14T21:17:21.6376411Z >>>             for items in zip(*zip_longest(*iters), strict=True)
2025-08-14T21:17:21.6376763Z >>>         ]
2025-08-14T21:17:21.6376995Z >>>         all_plans = [
2025-08-14T21:17:21.6377277Z >>>             replace(plan, items=items)
2025-08-14T21:17:21.6377680Z >>>             for plan, items in zip(all_plans, items_per_rank, strict=True)
2025-08-14T21:17:21.6378077Z >>>         ]
2025-08-14T21:17:21.6378350Z >>>         return super().create_global_plan(all_plans)
2025-08-14T21:17:21.6378601Z 
2025-08-14T21:17:21.6378877Z Finally, some planners need to save additional metadata in the checkpoint, this is
2025-08-14T21:17:21.6379525Z accomplished by having each rank contribute their data items in the local plan and
2025-08-14T21:17:21.6380090Z the global planner aggregate them:
2025-08-14T21:17:21.6380332Z 
2025-08-14T21:17:21.6380457Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6380822Z >>> class SaveExtraDataPlanner(DefaultSavePlanner):
2025-08-14T21:17:21.6381228Z >>>     def create_local_plan(self) -> SavePlan:
2025-08-14T21:17:21.6381591Z >>>         plan = super().create_local_plan()
2025-08-14T21:17:21.6381989Z >>>         return replace(plan, planner_data="per-rank-data")
2025-08-14T21:17:21.6382339Z >>>
2025-08-14T21:17:21.6382760Z >>>     def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]:
2025-08-14T21:17:21.6383378Z >>>         global_plan, metadata = super().create_global_plan(all_plans)
2025-08-14T21:17:21.6383843Z >>>         merged_data = [p.planner_data for p in global_plan]
2025-08-14T21:17:21.6384292Z >>>         metadata = replace(metadata, planner_data=merged_data)
2025-08-14T21:17:21.6384694Z >>>         return global_plan, metadata
2025-08-14T21:17:21.6384911Z 
2025-08-14T21:17:21.6385175Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6385544Z 
2025-08-14T21:17:21.6386138Z msg = Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305.
2025-08-14T21:17:21.6387108Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6387482Z 
2025-08-14T21:17:21.6387779Z Abstract class defining the protocol used by load_state_dict to plan the load process.
2025-08-14T21:17:21.6388187Z 
2025-08-14T21:17:21.6388485Z LoadPlanner are stateful objects that can be used to customize the whole load process.
2025-08-14T21:17:21.6388893Z 
2025-08-14T21:17:21.6389171Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-08-14T21:17:21.6389698Z will be visible to the whole process.
2025-08-14T21:17:21.6389912Z 
2025-08-14T21:17:21.6390201Z A planner subclass can expect the following sequence of calls during load_state_dict:
2025-08-14T21:17:21.6390597Z 
2025-08-14T21:17:21.6390728Z 1) set_up_planner - called on all ranks.
2025-08-14T21:17:21.6391073Z     Signals the start of loading a checkpoint.
2025-08-14T21:17:21.6391322Z 
2025-08-14T21:17:21.6391527Z 2) create_local_plan - called on all ranks.
2025-08-14T21:17:21.6392050Z     Process the state_dict and produces a `LoadPlan` that will be sent for global planning.
2025-08-14T21:17:21.6392452Z 
2025-08-14T21:17:21.6392632Z 3) create_global_plan - called on the coordinator rank only.
2025-08-14T21:17:21.6393196Z     Takes the LoadPlan from all ranks and make any global decision.
2025-08-14T21:17:21.6393519Z 
2025-08-14T21:17:21.6393665Z 4) load_bytes - called multiple times on each rank
2025-08-14T21:17:21.6394093Z     This is called once per non-tensor value in state_dict.
2025-08-14T21:17:21.6394371Z 
2025-08-14T21:17:21.6394591Z 5) resolve_tensor and commit_tensor - called multiple times on each rank
2025-08-14T21:17:21.6395120Z     They are called in pair for each Tensor value in state_dict.
2025-08-14T21:17:21.6395414Z 
2025-08-14T21:17:21.6395728Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as
2025-08-14T21:17:21.6396340Z most changes can be expressed by changes in a single method.
2025-08-14T21:17:21.6396630Z 
2025-08-14T21:17:21.6396781Z There are two usual patterns of extension:
2025-08-14T21:17:21.6397016Z 
2025-08-14T21:17:21.6397267Z Rewriting state_dict. This is the simplest way to extend the load process as it
2025-08-14T21:17:21.6397902Z doesn't requite understanding the intrincacies of how LoadPlan works. We need
2025-08-14T21:17:21.6398506Z to keep a reference to the original state_dict as load happens in place so
2025-08-14T21:17:21.6398974Z we need to be able to perform it in place
2025-08-14T21:17:21.6399201Z 
2025-08-14T21:17:21.6399311Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6399667Z >>> class RenamePlanner(DefaultLoadPlanner):
2025-08-14T21:17:21.6400042Z >>>     def set_up_planner(
2025-08-14T21:17:21.6400326Z >>>         self,
2025-08-14T21:17:21.6400578Z >>>         state_dict: STATE_DICT_TYPE,
2025-08-14T21:17:21.6400898Z >>>         metadata: Metadata,
2025-08-14T21:17:21.6401183Z >>>         is_coordinator: bool,
2025-08-14T21:17:21.6401469Z >>>     ) -> None:
2025-08-14T21:17:21.6401735Z >>>         self.original_state_dict = state_dict
2025-08-14T21:17:21.6402131Z >>>         state_dict = {"foo_" + k: v for k, v in state_dict.items()}
2025-08-14T21:17:21.6402508Z >>>
2025-08-14T21:17:21.6402748Z >>>         if self.flatten_sharded_tensors:
2025-08-14T21:17:21.6403128Z >>>             state_dict = _flatten_sharded_tensors(state_dict)
2025-08-14T21:17:21.6403467Z >>>
2025-08-14T21:17:21.6403689Z >>>         if self.flatten_state_dict:
2025-08-14T21:17:21.6404089Z >>>             state_dict, self.mappings = flatten_state_dict(state_dict)
2025-08-14T21:17:21.6404464Z >>>
2025-08-14T21:17:21.6404687Z >>>         self.state_dict = state_dict
2025-08-14T21:17:21.6405012Z >>>         self.metadata = metadata
2025-08-14T21:17:21.6405332Z >>>         self.is_coordinator = is_coordinator
2025-08-14T21:17:21.6405651Z >>>
2025-08-14T21:17:21.6405889Z >>>     def load_bytes(self, read_item, value):
2025-08-14T21:17:21.6406217Z >>> # Remove the "foo_" prefix
2025-08-14T21:17:21.6406724Z >>>         self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False)
2025-08-14T21:17:21.6407171Z 
2025-08-14T21:17:21.6407174Z 
2025-08-14T21:17:21.6407436Z Modifying resolve_tensor and commit_tensor to handle load time transformation.
2025-08-14T21:17:21.6407812Z 
2025-08-14T21:17:21.6407940Z >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:21.6408306Z >>> class MetaModelMaterialize(DefaultSavePlanner):
2025-08-14T21:17:21.6408701Z >>>     def resolve_tensor(self, read_item):
2025-08-14T21:17:21.6409296Z >>>         tensor = super().resolve_tensor(read_item)
2025-08-14T21:17:21.6409693Z >>>         return torch.empty_like(tensor, device="cpu")
2025-08-14T21:17:21.6410044Z >>>
2025-08-14T21:17:21.6410291Z >>>     def commit_tensor(self, read_item, tensor):
2025-08-14T21:17:21.6410691Z >>>         self.state_dict[read_item.dest_index.fqn] = tensor
2025-08-14T21:17:21.6410954Z 
2025-08-14T21:17:21.6411206Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6411585Z 
2025-08-14T21:17:21.6574072Z msg = Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118.
2025-08-14T21:17:21.6575255Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6575637Z 
2025-08-14T21:17:21.6575814Z Return the model state_dict and optimizers state_dict.
2025-08-14T21:17:21.6576085Z 
2025-08-14T21:17:21.6576307Z ``get_state_dict`` can process any module that is parallelized by PyTorch
2025-08-14T21:17:21.6576914Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any
2025-08-14T21:17:21.6577552Z combination of these parallelisms. The main functions of ``get_state_dict``
2025-08-14T21:17:21.6578144Z are: 1.) returning a model and optimizer state_dict that can be resharded
2025-08-14T21:17:21.6578678Z with a different number of trainers and/or different parallelisms.
2025-08-14T21:17:21.6579256Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call
2025-08-14T21:17:21.6579720Z these APIs.
2025-08-14T21:17:21.6579963Z 3.) sanity checking the result state_dict.
2025-08-14T21:17:21.6580202Z 
2025-08-14T21:17:21.6580413Z The keys of the result state dictionary are the canonical FQNs (Fully
2025-08-14T21:17:21.6580972Z Qualified Names).  A canonical FQN refers to the FQN based on a parameter's
2025-08-14T21:17:21.6581567Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a
2025-08-14T21:17:21.6582119Z parameter is the FQN returned by ``module.named_parameters()`` or
2025-08-14T21:17:21.6582700Z ``module.named_buffers()`` when the module is not distributed by any
2025-08-14T21:17:21.6583327Z parallelisms. Since the optimizer internally uses parameter IDs to represent
2025-08-14T21:17:21.6583947Z a parameter, there will be a conversion from the parameter IDs to the
2025-08-14T21:17:21.6584387Z canonical FQNs when calling this API.
2025-08-14T21:17:21.6584615Z 
2025-08-14T21:17:21.6584832Z ``get_state_dict`` can also process a module that is not parallelized. In
2025-08-14T21:17:21.6585395Z such a case, ``get_state_dict`` only performs one function -- converting the
2025-08-14T21:17:21.6585887Z optimizer parameter IDs to the canonical FQNs.
2025-08-14T21:17:21.6586139Z 
2025-08-14T21:17:21.6586223Z Example:
2025-08-14T21:17:21.6586453Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.6586721Z     >>> import torch
2025-08-14T21:17:21.6587102Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:21.6587659Z     >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-08-14T21:17:21.6588205Z     >>> from torch.distributed.checkpoint.state_dict import get_state_dict
2025-08-14T21:17:21.6588548Z 
2025-08-14T21:17:21.6588674Z     >>> fsdp_model = FSDP(copy.deepcopy(model))
2025-08-14T21:17:21.6589102Z     >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-08-14T21:17:21.6589525Z     >>> ddp_model = DDP(copy.deepcopy(model))
2025-08-14T21:17:21.6589942Z     >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-08-14T21:17:21.6590230Z 
2025-08-14T21:17:21.6590234Z 
2025-08-14T21:17:21.6590470Z     >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim)
2025-08-14T21:17:21.6590999Z     >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict(
2025-08-14T21:17:21.6591465Z     ...     fsdp_model, fsdp_optim
2025-08-14T21:17:21.6591753Z     ... )
2025-08-14T21:17:21.6591884Z 
2025-08-14T21:17:21.6592095Z     >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(),
2025-08-14T21:17:21.6592533Z     >>> # the asserts will fail.
2025-08-14T21:17:21.6592857Z     >>> assert ddp_state_dict == fsdp_state_dict
2025-08-14T21:17:21.6593238Z     >>> assert ddp_optim_state == fsdp_optim_state_dict
2025-08-14T21:17:21.6593504Z 
2025-08-14T21:17:21.6593508Z 
2025-08-14T21:17:21.6593590Z Args:
2025-08-14T21:17:21.6593853Z     model (nn.Module): the nn.Module to the model.
2025-08-14T21:17:21.6594281Z     optimizers (Union[None, Optimizer, Iterable[Optimizer]]):
2025-08-14T21:17:21.6594744Z         The optimizers that are used to optimize ``model``.
2025-08-14T21:17:21.6595370Z     submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters
2025-08-14T21:17:21.6595889Z         that belong to the submodules.
2025-08-14T21:17:21.6596269Z     options (StateDictOptions): the options to control how
2025-08-14T21:17:21.6596765Z         model state_dict and optimizer state_dict should be returned. See
2025-08-14T21:17:21.6597219Z         `StateDictOptions` for the details.
2025-08-14T21:17:21.6597447Z 
2025-08-14T21:17:21.6597530Z Returns:
2025-08-14T21:17:21.6597855Z     ``Tuple`` that contain model state_dict and optimizer state_dict.
2025-08-14T21:17:21.6598176Z 
2025-08-14T21:17:21.6598404Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType]
2025-08-14T21:17:21.6598746Z 
2025-08-14T21:17:21.6599010Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6599375Z 
2025-08-14T21:17:21.6614154Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69.
2025-08-14T21:17:21.6615625Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6616024Z 
2025-08-14T21:17:21.6616221Z Load a checkpoint into a distributed state dict in SPMD style.
2025-08-14T21:17:21.6616525Z 
2025-08-14T21:17:21.6616760Z Each rank must have the same keys in their ``state_dict`` provided to this
2025-08-14T21:17:21.6617322Z API. Mismatched keys may result in hangs or errors. If unsure, you can use
2025-08-14T21:17:21.6618055Z the ``utils._assert_same_keys`` API to check (but may incur communication
2025-08-14T21:17:21.6618485Z costs).
2025-08-14T21:17:21.6618599Z 
2025-08-14T21:17:21.6618793Z Each rank will try to read the least amount of data necessary
2025-08-14T21:17:21.6619314Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor`
2025-08-14T21:17:21.6619921Z or :class:`DTensor` instances, each rank only reads data for their local shards.
2025-08-14T21:17:21.6620285Z 
2025-08-14T21:17:21.6620557Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-08-14T21:17:21.6621223Z load will first call ``state_dict`` before attempting deserialization, followed by
2025-08-14T21:17:21.6621771Z ``load_state_dict`` once the deserialization is complete.
2025-08-14T21:17:21.6622295Z For each non-``Stateful`` object, load will deserialize the object, and then replace
2025-08-14T21:17:21.6622829Z it in the ``state_dict`` with the deserialized object.
2025-08-14T21:17:21.6623087Z 
2025-08-14T21:17:21.6623207Z .. warning::
2025-08-14T21:17:21.6623495Z     All tensors in ``state_dict`` must be allocated on their
2025-08-14T21:17:21.6623944Z     destination device *prior to* calling this function.
2025-08-14T21:17:21.6624214Z 
2025-08-14T21:17:21.6624450Z     All non-tensor data is loaded using `torch.load()` and modified in place
2025-08-14T21:17:21.6624887Z     on state_dict.
2025-08-14T21:17:21.6625027Z 
2025-08-14T21:17:21.6625116Z .. warning::
2025-08-14T21:17:21.6625453Z     Users must call `load_state_dict` on the root module to ensure load
2025-08-14T21:17:21.6625957Z     pos-processing and non-tensor data properly propagates.
2025-08-14T21:17:21.6626246Z 
2025-08-14T21:17:21.6626327Z .. note:
2025-08-14T21:17:21.6626672Z     If no process group is initialized, this function will assume the intent
2025-08-14T21:17:21.6627242Z     is to load a checkpoint into the local process. This can be useful in the
2025-08-14T21:17:21.6627832Z     case of local inference, and when using regular Tensors (as opposed to DTensor
2025-08-14T21:17:21.6628286Z      or ShardedTensor)
2025-08-14T21:17:21.6628455Z 
2025-08-14T21:17:21.6628537Z .. note:
2025-08-14T21:17:21.6628795Z     Rank 0 is assumed to be the coordinator rank.
2025-08-14T21:17:21.6629039Z 
2025-08-14T21:17:21.6629120Z Args:
2025-08-14T21:17:21.6629455Z     state_dict (Dict[str, Any]): The state_dict to load the checkpoint into.
2025-08-14T21:17:21.6629937Z     checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:21.6630482Z         The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:21.6631023Z         depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:21.6631587Z         It can also be a key if the storage is a key-value store.
2025-08-14T21:17:21.6631971Z         (Default: ``None``)
2025-08-14T21:17:21.6632267Z     storage_reader (Optional[StorageReader]):
2025-08-14T21:17:21.6632722Z         Instance of StorageWriter used to perform reads. If this is not
2025-08-14T21:17:21.6633252Z         specified, DCP will automatically infer the reader based on the
2025-08-14T21:17:21.6633763Z         checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:21.6634194Z         be raised. (Default: ``None``)
2025-08-14T21:17:21.6634524Z     planner (Optional[LoadPlanner]):
2025-08-14T21:17:21.6634939Z         Instance of LoadPlanner. If this is not specified, the default
2025-08-14T21:17:21.6635372Z         planner will be used. (Default: ``None``)
2025-08-14T21:17:21.6635745Z     process_group (Optional[ProcessGroup]):
2025-08-14T21:17:21.6636172Z         ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:21.6636559Z         (Default: ``None``)
2025-08-14T21:17:21.6636947Z     no_dist (bool): If ``True``, this function will assume the intent is to load
2025-08-14T21:17:21.6637531Z         a checkpoint without using cross-rank synchronization. (Default: ``False``)
2025-08-14T21:17:21.6638018Z Returns:
2025-08-14T21:17:21.6638259Z     None.
2025-08-14T21:17:21.6638380Z 
2025-08-14T21:17:21.6638478Z Examples
2025-08-14T21:17:21.6638701Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.6638965Z     >>> my_model = MyModule()
2025-08-14T21:17:21.6639287Z     >>> optimizer = Adagrad(my_model.parameters())
2025-08-14T21:17:21.6639663Z     >>> model_state_dict = my_model.state_dict()
2025-08-14T21:17:21.6640124Z     >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader(
2025-08-14T21:17:21.6640575Z     ...     "/checkpoint/1"
2025-08-14T21:17:21.6640840Z     ... )
2025-08-14T21:17:21.6640957Z 
2025-08-14T21:17:21.6641112Z     >>> torch.distributed.checkpoint.load_state_dict(
2025-08-14T21:17:21.6641491Z     >>>     state_dict=model_state_dict,
2025-08-14T21:17:21.6641838Z     >>>     storage_reader=fs_storage_reader,
2025-08-14T21:17:21.6642139Z     >>> )
2025-08-14T21:17:21.6642267Z 
2025-08-14T21:17:21.6642464Z     >>> # module.load_state_dict() function might have customized steps
2025-08-14T21:17:21.6642912Z     >>> # to flush the state_dict, must call it to
2025-08-14T21:17:21.6643255Z     >>> # ensure correct behavior.
2025-08-14T21:17:21.6643574Z     >>> my_model.load_state_dict(model_state_dict)
2025-08-14T21:17:21.6643822Z 
2025-08-14T21:17:21.6643915Z .. note::
2025-08-14T21:17:21.6644239Z     load_state_dict uses collectives to coordinate reads across ranks.
2025-08-14T21:17:21.6644784Z     For NCCL-based process groups, internal tensor representations of
2025-08-14T21:17:21.6645349Z     objects must be moved to the GPU device before communication takes place.
2025-08-14T21:17:21.6645917Z     In this case, the device used is given by ``torch.cuda.current_device()``
2025-08-14T21:17:21.6646472Z     and it is the user's responsibility to ensure that this is set so that each
2025-08-14T21:17:21.6647006Z     rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-08-14T21:17:21.6647300Z 
2025-08-14T21:17:21.6647559Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6647928Z 
2025-08-14T21:17:21.6653402Z msg = Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97.
2025-08-14T21:17:21.6654407Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6654804Z 
2025-08-14T21:17:21.6654925Z Save a distributed model in SPMD style.
2025-08-14T21:17:21.6655151Z 
2025-08-14T21:17:21.6655362Z This function is different from ``torch.save()`` as it handles
2025-08-14T21:17:21.6656114Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards.
2025-08-14T21:17:21.6656507Z 
2025-08-14T21:17:21.6656771Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-08-14T21:17:21.6657307Z save will call ``state_dict`` before serialization.
2025-08-14T21:17:21.6657567Z 
2025-08-14T21:17:21.6657683Z .. warning::
2025-08-14T21:17:21.6658057Z     There is no guarantees of Backwards Compatibility across PyTorch versions
2025-08-14T21:17:21.6658527Z     for saved state_dicts.
2025-08-14T21:17:21.6658702Z 
2025-08-14T21:17:21.6658807Z .. warning::
2025-08-14T21:17:21.6659153Z     If using the `process_group` argument, make sure that only its ranks
2025-08-14T21:17:21.6659837Z     call `save_state_dict` and that all data in state_dict belong to it.
2025-08-14T21:17:21.6660204Z 
2025-08-14T21:17:21.6660349Z .. note::
2025-08-14T21:17:21.6661095Z     When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of
2025-08-14T21:17:21.6661763Z     the shard_group should be calling `save_state_dict` and the corresponding process
2025-08-14T21:17:21.6662265Z     group needs to be passed in.
2025-08-14T21:17:21.6662465Z 
2025-08-14T21:17:21.6662568Z .. note::
2025-08-14T21:17:21.6662949Z     If no process group is available, this function assumes the intention is to save the
2025-08-14T21:17:21.6663452Z      state_dict in the local process.
2025-08-14T21:17:21.6663731Z 
2025-08-14T21:17:21.6663850Z .. note:
2025-08-14T21:17:21.6664114Z     Rank 0 is assumed to be the coordinator rank.
2025-08-14T21:17:21.6664362Z 
2025-08-14T21:17:21.6664366Z 
2025-08-14T21:17:21.6664449Z Args:
2025-08-14T21:17:21.6664724Z     state_dict (Dict[str, Any]): The state_dict to save.
2025-08-14T21:17:21.6665134Z     checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:21.6665591Z         The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:21.6666132Z         depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:21.6666623Z         It can also be a key if the storage is a key-value store.
2025-08-14T21:17:21.6667039Z         (Default: ``None``)
2025-08-14T21:17:21.6667348Z     storage_writer (Optional[StorageWriter]):
2025-08-14T21:17:21.6667790Z         Instance of StorageWriter used to perform writes. If this is not
2025-08-14T21:17:21.6668323Z         specified, DCP will automatically infer the writer based on the
2025-08-14T21:17:21.6668853Z         checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:21.6669273Z         be raised. (Default: ``None``)
2025-08-14T21:17:21.6669604Z     planner (Optional[SavePlanner]):
2025-08-14T21:17:21.6670026Z         Instance of SavePlanner. If this is not specified, the default
2025-08-14T21:17:21.6670473Z         planner will be used. (Default: ``None``)
2025-08-14T21:17:21.6670829Z     process_group (Optional[ProcessGroup]):
2025-08-14T21:17:21.6671256Z         ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:21.6671725Z         (Default: ``None``)
2025-08-14T21:17:21.6671982Z     no_dist (bool):
2025-08-14T21:17:21.6672302Z         If ``True``, this function will assume the intent is to load
2025-08-14T21:17:21.6672714Z         a checkpoint on a single rank/process.
2025-08-14T21:17:21.6673040Z         (Default: ``False``)
2025-08-14T21:17:21.6673483Z     use_collectives (bool): If ``False``, this function will assume the intent is to save
2025-08-14T21:17:21.6674046Z         a checkpoint without using cross-rank synchronization.
2025-08-14T21:17:21.6674419Z         (Default: ``True``)
2025-08-14T21:17:21.6674824Z         This configuration is experimental and should be used with caution.
2025-08-14T21:17:21.6675437Z         It will change the format of the saved checkpoint and may not be backward compatible.
2025-08-14T21:17:21.6675825Z 
2025-08-14T21:17:21.6675922Z Returns:
2025-08-14T21:17:21.6676193Z     Metadata: Metadata object for the saved checkpoint.
2025-08-14T21:17:21.6676540Z 
2025-08-14T21:17:21.6676630Z Example:
2025-08-14T21:17:21.6676862Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:21.6677133Z     >>> my_model = MyModule()
2025-08-14T21:17:21.6677329Z 
2025-08-14T21:17:21.6677439Z     >>> state_dict = {"model": my_model}
2025-08-14T21:17:21.6677666Z 
2025-08-14T21:17:21.6677899Z     >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-08-14T21:17:21.6678357Z     ...     "/checkpoint/1"
2025-08-14T21:17:21.6678609Z     ... )
2025-08-14T21:17:21.6678861Z     >>> torch.distributed.checkpoint.save(
2025-08-14T21:17:21.6679204Z     >>>     state_dict=state_dict,
2025-08-14T21:17:21.6679510Z     >>>     storage_writer=fs_storage_writer,
2025-08-14T21:17:21.6679827Z     >>> )
2025-08-14T21:17:21.6679943Z 
2025-08-14T21:17:21.6680040Z .. note::
2025-08-14T21:17:21.6680366Z     save_state_dict uses collectives to coordinate writes across ranks.
2025-08-14T21:17:21.6680913Z     For NCCL-based process groups, internal tensor representations of
2025-08-14T21:17:21.6681479Z     objects must be moved to the GPU device before communication takes place.
2025-08-14T21:17:21.6682048Z     In this case, the device used is given by ``torch.cuda.current_device()``
2025-08-14T21:17:21.6682585Z     and it is the user's responsibility to ensure that this is set so that
2025-08-14T21:17:21.6683111Z     each rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-08-14T21:17:21.6683469Z 
2025-08-14T21:17:21.6683729Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6684122Z 
2025-08-14T21:17:21.6684757Z msg = Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230.
2025-08-14T21:17:21.6685744Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.6686391Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the
2025-08-14T21:17:21.6687071Z     staging storage (defaults to CPU memory), and then calls the `save` in a separate thread.
2025-08-14T21:17:21.6687473Z 
2025-08-14T21:17:21.6687577Z     .. warning::
2025-08-14T21:17:21.6687873Z         This feature is experimental and subject to change.
2025-08-14T21:17:21.6688294Z         MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED
2025-08-14T21:17:21.6688548Z 
2025-08-14T21:17:21.6688642Z     Args:
2025-08-14T21:17:21.6688912Z         state_dict (Dict[str, Any]): The state_dict to save.
2025-08-14T21:17:21.6689333Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:21.6689807Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:21.6690331Z             depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:21.6690827Z             It can also be a key if the storage is a key-value store.
2025-08-14T21:17:21.6691211Z             (Default: ``None``)
2025-08-14T21:17:21.6691535Z         storage_writer (Optional[StorageWriter]):
2025-08-14T21:17:21.6691983Z             Instance of StorageWriter used to perform 'stage' and  'save'. If
2025-08-14T21:17:21.6692556Z             this is not specified, DCP will automatically infer the writer based on the
2025-08-14T21:17:21.6693122Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:21.6693546Z             be raised. (Default: ``None``)
2025-08-14T21:17:21.6693890Z         planner (Optional[SavePlanner]):
2025-08-14T21:17:21.6694319Z             Instance of SavePlanner. If this is not specified, the default
2025-08-14T21:17:21.6694771Z             planner will be used. (Default: ``None``)
2025-08-14T21:17:21.6695140Z         process_group (Optional[ProcessGroup]):
2025-08-14T21:17:21.6695568Z             ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:21.6695968Z             (Default: ``None``)
2025-08-14T21:17:21.6696305Z         async_checkpointer_type (AsyncCheckpointerType):
2025-08-14T21:17:21.6696810Z             whether to do checkpoint in separate thread or process
2025-08-14T21:17:21.6697248Z             (Default: ``AsyncCheckpointerType.THREAD``)
2025-08-14T21:17:21.6697606Z         async_stager (AsyncStager):
2025-08-14T21:17:21.6698077Z             provides staging implementation. If storage_writer implements AsyncStager
2025-08-14T21:17:21.6698677Z             and async_stager is provided, async_stager will be used for staging
2025-08-14T21:17:21.6699110Z         no_dist (bool):
2025-08-14T21:17:21.6699439Z             If ``True``, this function will assume the intent is to save
2025-08-14T21:17:21.6699861Z             a checkpoint on a single rank/process.
2025-08-14T21:17:21.6700212Z             (Default: ``False``)
2025-08-14T21:17:21.6700708Z         use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``)
2025-08-14T21:17:21.6701376Z             This configuration is experimental and should be used with caution.
2025-08-14T21:17:21.6702003Z             It will change the format of the saved checkpoint and may not be backward compatible.
2025-08-14T21:17:21.6702394Z 
2025-08-14T21:17:21.6702496Z     Returns:
2025-08-14T21:17:21.6702835Z         Future: A future holding the resultant Metadata object from `save`.
2025-08-14T21:17:21.6703179Z 
2025-08-14T21:17:21.6703264Z     Example:
2025-08-14T21:17:21.6703499Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:21.6703809Z         >>> my_model = MyModule()
2025-08-14T21:17:21.6704013Z 
2025-08-14T21:17:21.6704149Z         >>> state_dict = {"model": my_model}
2025-08-14T21:17:21.6704382Z 
2025-08-14T21:17:21.6704617Z         >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-08-14T21:17:21.6705076Z         ...     "/checkpoint/1"
2025-08-14T21:17:21.6705333Z         ... )
2025-08-14T21:17:21.6705674Z         >>> checkpoint_future = torch.distributed.checkpoint.async_save(
2025-08-14T21:17:21.6706117Z         >>>     state_dict=state_dict,
2025-08-14T21:17:21.6706441Z         >>>     storage_writer=fs_storage_writer,
2025-08-14T21:17:21.6706758Z         >>> )
2025-08-14T21:17:21.6706972Z         >>>
2025-08-14T21:17:21.6707185Z         >>> # ... do some work ...
2025-08-14T21:17:21.6707466Z         >>>
2025-08-14T21:17:21.6707699Z         >>> checkpoint_future.result()
2025-08-14T21:17:21.6707910Z 
2025-08-14T21:17:21.6707989Z     
2025-08-14T21:17:21.6708361Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.6708745Z 
2025-08-14T21:17:21.7010167Z msg = Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94.
2025-08-14T21:17:21.7011256Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.7011633Z 
2025-08-14T21:17:21.7011856Z Initialize rendezvous event object and record its operations.
2025-08-14T21:17:21.7012171Z 
2025-08-14T21:17:21.7012254Z Args:
2025-08-14T21:17:21.7012521Z     run_id (str): The run id of the rendezvous.
2025-08-14T21:17:21.7012913Z     message (str): The message describing the event.
2025-08-14T21:17:21.7013415Z     node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED).
2025-08-14T21:17:21.7013982Z     name (str): Event name. (E.g. Current action being performed).
2025-08-14T21:17:21.7014398Z     hostname (str): Hostname of the node.
2025-08-14T21:17:21.7014774Z     pid (Optional[int]): The process id of the node.
2025-08-14T21:17:21.7015268Z     master_endpoint (str): The master endpoint for the rendezvous store, if known.
2025-08-14T21:17:21.7015902Z     local_id (Optional[int]):  The local_id of the node, if defined in dynamic_rendezvous.py
2025-08-14T21:17:21.7016452Z     rank (Optional[int]): The rank of the node, if known.
2025-08-14T21:17:21.7016799Z Returns:
2025-08-14T21:17:21.7017005Z     None
2025-08-14T21:17:21.7017211Z Example:
2025-08-14T21:17:21.7017475Z     >>> # See DynamicRendezvousHandler class
2025-08-14T21:17:21.7017966Z     >>> def _record(
2025-08-14T21:17:21.7018214Z     ...     self,
2025-08-14T21:17:21.7018456Z     ...     message: str,
2025-08-14T21:17:21.7018754Z     ...     node_state: NodeState = NodeState.RUNNING,
2025-08-14T21:17:21.7019116Z     ...     rank: Optional[int] = None,
2025-08-14T21:17:21.7019426Z     ... ) -> None:
2025-08-14T21:17:21.7019682Z     ...     construct_and_record_rdzv_event(
2025-08-14T21:17:21.7020081Z     ...         name=f"{self.__class__.__name__}.{get_method_name()}",
2025-08-14T21:17:21.7020626Z     ...         run_id=self._settings.run_id,
2025-08-14T21:17:21.7021018Z     ...         message=message,
2025-08-14T21:17:21.7021317Z     ...         node_state=node_state,
2025-08-14T21:17:21.7021646Z     ...         hostname=self._this_node.addr,
2025-08-14T21:17:21.7021975Z     ...         pid=self._this_node.pid,
2025-08-14T21:17:21.7022315Z     ...         local_id=self._this_node.local_id,
2025-08-14T21:17:21.7022650Z     ...         rank=rank,
2025-08-14T21:17:21.7022901Z     ...     )
2025-08-14T21:17:21.7023034Z 
2025-08-14T21:17:21.7023283Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.7023662Z 
2025-08-14T21:17:21.9025368Z msg = Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114.
2025-08-14T21:17:21.9026383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9026984Z 
2025-08-14T21:17:21.9027222Z This configures FSDP-native mixed precision training.
2025-08-14T21:17:21.9027501Z 
2025-08-14T21:17:21.9027608Z Attributes:
2025-08-14T21:17:21.9027966Z     param_dtype (Optional[torch.dtype]): This specifies the dtype for model
2025-08-14T21:17:21.9028526Z         parameters during forward and backward and thus the dtype for
2025-08-14T21:17:21.9029070Z         forward and backward computation. Outside forward and backward, the
2025-08-14T21:17:21.9029615Z         *sharded* parameters are kept in full precision (e.g. for the
2025-08-14T21:17:21.9030123Z         optimizer step), and for model checkpointing, the parameters are
2025-08-14T21:17:21.9030608Z         always saved in full precision. (Default: ``None``)
2025-08-14T21:17:21.9031096Z     reduce_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-08-14T21:17:21.9031724Z         gradient reduction (i.e. reduce-scatter or all-reduce). If this is
2025-08-14T21:17:21.9032243Z         ``None`` but ``param_dtype`` is not ``None``, then this takes on
2025-08-14T21:17:21.9032746Z         the ``param_dtype`` value, still running gradient reduction in low
2025-08-14T21:17:21.9033289Z         precision. This is permitted to differ from ``param_dtype``, e.g.
2025-08-14T21:17:21.9033926Z         to force gradient reduction to run in full precision. (Default:
2025-08-14T21:17:21.9034483Z         ``None``)
2025-08-14T21:17:21.9034961Z     buffer_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-08-14T21:17:21.9035915Z         buffers. FSDP does not shard buffers. Rather, FSDP casts them to
2025-08-14T21:17:21.9036509Z         ``buffer_dtype`` in the first forward pass and keeps them in that
2025-08-14T21:17:21.9037039Z         dtype thereafter. For model checkpointing, the buffers are saved
2025-08-14T21:17:21.9037542Z         in full precision except for ``LOCAL_STATE_DICT``. (Default:
2025-08-14T21:17:21.9037928Z         ``None``)
2025-08-14T21:17:21.9038271Z     keep_low_precision_grads (bool): If ``False``, then FSDP upcasts
2025-08-14T21:17:21.9038809Z         gradients to full precision after the backward pass in preparation
2025-08-14T21:17:21.9039340Z         for the optimizer step. If ``True``, then FSDP keeps the gradients
2025-08-14T21:17:21.9039878Z         in the dtype used for gradient reduction, which can save memory if
2025-08-14T21:17:21.9040414Z         using a custom optimizer that supports running in low precision.
2025-08-14T21:17:21.9040831Z         (Default: ``False``)
2025-08-14T21:17:21.9041383Z     cast_forward_inputs (bool): If ``True``, then this FSDP module casts
2025-08-14T21:17:21.9041925Z         its forward args and kwargs to ``param_dtype``. This is to ensure
2025-08-14T21:17:21.9042467Z         that parameter and input dtypes match for forward computation, as
2025-08-14T21:17:21.9042995Z         required by many ops. This may need to be set to ``True`` when only
2025-08-14T21:17:21.9043546Z         applying mixed precision to some but not all FSDP modules, in which
2025-08-14T21:17:21.9044109Z         case a mixed-precision FSDP submodule needs to recast its inputs.
2025-08-14T21:17:21.9044532Z         (Default: ``False``)
2025-08-14T21:17:21.9044940Z     cast_root_forward_inputs (bool): If ``True``, then the root FSDP module
2025-08-14T21:17:21.9045487Z         casts its forward args and kwargs to ``param_dtype``, overriding
2025-08-14T21:17:21.9046004Z         the value of ``cast_forward_inputs``. For non-root FSDP modules,
2025-08-14T21:17:21.9046451Z         this does not do anything. (Default: ``True``)
2025-08-14T21:17:21.9046933Z     _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies
2025-08-14T21:17:21.9047456Z         module classes to ignore for mixed precision when using an
2025-08-14T21:17:21.9047932Z         ``auto_wrap_policy``: Modules of these classes will have FSDP
2025-08-14T21:17:21.9048444Z         applied to them separately with mixed precision disabled (meaning
2025-08-14T21:17:21.9048702Z         that the final FSDP construction would deviate from the specified
2025-08-14T21:17:21.9048930Z         policy). If ``auto_wrap_policy`` is not specified, then this does
2025-08-14T21:17:21.9049126Z         not do anything. This API is experimental and subject to change.
2025-08-14T21:17:21.9049245Z         (Default: ``(_BatchNorm,)``)
2025-08-14T21:17:21.9049251Z 
2025-08-14T21:17:21.9049431Z .. note:: This API is experimental and subject to change.
2025-08-14T21:17:21.9049437Z 
2025-08-14T21:17:21.9049656Z .. note:: Only floating point tensors are cast to their specified dtypes.
2025-08-14T21:17:21.9049678Z 
2025-08-14T21:17:21.9049860Z .. note:: In ``summon_full_params``, parameters are forced to full
2025-08-14T21:17:21.9049974Z     precision, but buffers are not.
2025-08-14T21:17:21.9049979Z 
2025-08-14T21:17:21.9050196Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when
2025-08-14T21:17:21.9050402Z     their inputs are in a low precision like ``float16`` or ``bfloat16``.
2025-08-14T21:17:21.9050631Z     Disabling FSDP's mixed precision for those norm modules only means that
2025-08-14T21:17:21.9050852Z     the affine parameters are kept in ``float32``. However, this incurs
2025-08-14T21:17:21.9051084Z     separate all-gathers and reduce-scatters for those norm modules, which
2025-08-14T21:17:21.9051311Z     may be inefficient, so if the workload permits, the user should prefer
2025-08-14T21:17:21.9051456Z     to still apply mixed precision to those modules.
2025-08-14T21:17:21.9051460Z 
2025-08-14T21:17:21.9051665Z .. note:: By default, if the user passes a model with any ``_BatchNorm``
2025-08-14T21:17:21.9051881Z     modules and specifies an ``auto_wrap_policy``, then the batch norm
2025-08-14T21:17:21.9052103Z     modules will have FSDP applied to them separately with mixed precision
2025-08-14T21:17:21.9052274Z     disabled. See the ``_module_classes_to_ignore`` argument.
2025-08-14T21:17:21.9052290Z 
2025-08-14T21:17:21.9052493Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and
2025-08-14T21:17:21.9052705Z     ``cast_forward_inputs=False`` by default. For the root FSDP instance,
2025-08-14T21:17:21.9052889Z     its ``cast_root_forward_inputs`` takes precedence over its
2025-08-14T21:17:21.9053063Z     ``cast_forward_inputs``. For non-root FSDP instances, their
2025-08-14T21:17:21.9053275Z     ``cast_root_forward_inputs`` values are ignored. The default setting is
2025-08-14T21:17:21.9053504Z     sufficient for the typical case where each FSDP instance has the same
2025-08-14T21:17:21.9053790Z     ``MixedPrecision`` configuration and only needs to cast inputs to the
2025-08-14T21:17:21.9053984Z     ``param_dtype`` at the beginning of the model's forward pass.
2025-08-14T21:17:21.9053988Z 
2025-08-14T21:17:21.9054189Z .. note:: For nested FSDP instances with different ``MixedPrecision``
2025-08-14T21:17:21.9054422Z     configurations, we recommend setting individual ``cast_forward_inputs``
2025-08-14T21:17:21.9054637Z     values to configure casting inputs or not before each instance's
2025-08-14T21:17:21.9054834Z     forward. In such a case, since the casts happen before each FSDP
2025-08-14T21:17:21.9055052Z     instance's forward, a parent FSDP instance should have its non-FSDP
2025-08-14T21:17:21.9055292Z     submodules run before its FSDP submodules to avoid the activation dtype
2025-08-14T21:17:21.9055499Z     being changed due to a different ``MixedPrecision`` configuration.
2025-08-14T21:17:21.9055503Z 
2025-08-14T21:17:21.9055611Z     Example::
2025-08-14T21:17:21.9055616Z 
2025-08-14T21:17:21.9055750Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9055918Z         >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3))
2025-08-14T21:17:21.9056029Z         >>> model[1] = FSDP(
2025-08-14T21:17:21.9056121Z         >>>     model[1],
2025-08-14T21:17:21.9056424Z         >>>     mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True),
2025-08-14T21:17:21.9056522Z         >>> )
2025-08-14T21:17:21.9056650Z         >>> model = FSDP(
2025-08-14T21:17:21.9056777Z         >>>     model,
2025-08-14T21:17:21.9057080Z         >>>     mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True),
2025-08-14T21:17:21.9057163Z         >>> )
2025-08-14T21:17:21.9057167Z 
2025-08-14T21:17:21.9057388Z     The above shows a working example. On the other hand, if ``model[1]``
2025-08-14T21:17:21.9057585Z     were replaced with ``model[0]``, meaning that the submodule using
2025-08-14T21:17:21.9057804Z     different ``MixedPrecision`` ran its forward first, then ``model[1]``
2025-08-14T21:17:21.9058039Z     would incorrectly see ``float16`` activations instead of ``bfloat16``
2025-08-14T21:17:21.9058123Z     ones.
2025-08-14T21:17:21.9058127Z 
2025-08-14T21:17:21.9058131Z 
2025-08-14T21:17:21.9058395Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9058399Z 
2025-08-14T21:17:21.9059010Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295.
2025-08-14T21:17:21.9059289Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9059293Z 
2025-08-14T21:17:21.9059499Z ``FullStateDictConfig`` is a config class meant to be used with
2025-08-14T21:17:21.9059693Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both
2025-08-14T21:17:21.9059908Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state
2025-08-14T21:17:21.9060132Z dicts to save GPU memory and CPU memory, respectively. This config class
2025-08-14T21:17:21.9060348Z is meant to be used via the :func:`state_dict_type` context manager as
2025-08-14T21:17:21.9060437Z follows:
2025-08-14T21:17:21.9060441Z 
2025-08-14T21:17:21.9060568Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9060821Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:21.9060947Z     >>> fsdp = FSDP(model, auto_wrap_policy=...)
2025-08-14T21:17:21.9061150Z     >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True)
2025-08-14T21:17:21.9061380Z     >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg):
2025-08-14T21:17:21.9061490Z     >>>     state = fsdp.state_dict()
2025-08-14T21:17:21.9061709Z     >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0.
2025-08-14T21:17:21.9061943Z     >>> # To reload checkpoint for inference, finetuning, transfer learning, etc:
2025-08-14T21:17:21.9062229Z     >>> model = model_fn()  # Initialize model in preparation for wrapping with FSDP
2025-08-14T21:17:21.9062345Z     >>> if dist.get_rank() == 0:
2025-08-14T21:17:21.9062526Z     >>> # Load checkpoint only on rank 0 to avoid memory redundancy
2025-08-14T21:17:21.9062663Z     >>>     state_dict = torch.load("my_checkpoint.pt")
2025-08-14T21:17:21.9062794Z     >>>     model.load_state_dict(state_dict)
2025-08-14T21:17:21.9063026Z     >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument
2025-08-14T21:17:21.9063279Z     >>> # communicates loaded checkpoint states from rank 0 to rest of the world.
2025-08-14T21:17:21.9063369Z     >>> fsdp = FSDP(
2025-08-14T21:17:21.9063455Z     ...     model,
2025-08-14T21:17:21.9063597Z     ...     device_id=torch.cuda.current_device(),
2025-08-14T21:17:21.9063697Z     ...     auto_wrap_policy=...,
2025-08-14T21:17:21.9063799Z     ...     sync_module_states=True,
2025-08-14T21:17:21.9063895Z     ... )
2025-08-14T21:17:21.9064104Z     >>> # After this point, all ranks have FSDP model with loaded checkpoint.
2025-08-14T21:17:21.9064111Z 
2025-08-14T21:17:21.9064199Z Attributes:
2025-08-14T21:17:21.9064408Z     rank0_only (bool): If ``True``, then only rank 0 saves the full state
2025-08-14T21:17:21.9064604Z         dict, and nonzero ranks save an empty dict. If ``False``, then all
2025-08-14T21:17:21.9064771Z         ranks save the full state dict. (Default: ``False``)
2025-08-14T21:17:21.9064776Z 
2025-08-14T21:17:21.9065056Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9065087Z 
2025-08-14T21:17:21.9165551Z msg = Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634.
2025-08-14T21:17:21.9165841Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9166109Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-08-14T21:17:21.9166114Z 
2025-08-14T21:17:21.9166405Z         Also takes (optional) configuration for the model's and optimizer's state dict.
2025-08-14T21:17:21.9166610Z         The target module does not have to be a FSDP module. If the target
2025-08-14T21:17:21.9166831Z         module is a FSDP module, its ``state_dict_type`` will also be changed.
2025-08-14T21:17:21.9166836Z 
2025-08-14T21:17:21.9167040Z         .. note:: This API should be called for only the top-level (root)
2025-08-14T21:17:21.9167129Z             module.
2025-08-14T21:17:21.9167139Z 
2025-08-14T21:17:21.9167354Z         .. note:: This API enables users to transparently use the conventional
2025-08-14T21:17:21.9167540Z             ``state_dict`` API to take model checkpoints in cases where the
2025-08-14T21:17:21.9167756Z             root FSDP module is wrapped by another ``nn.Module``. For example,
2025-08-14T21:17:21.9167960Z             the following will ensure ``state_dict`` is called on all non-FSDP
2025-08-14T21:17:21.9168193Z             instances, while dispatching into `sharded_state_dict` implementation
2025-08-14T21:17:21.9168293Z             for FSDP:
2025-08-14T21:17:21.9168297Z 
2025-08-14T21:17:21.9168385Z         Example::
2025-08-14T21:17:21.9168389Z 
2025-08-14T21:17:21.9168532Z             >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9168637Z             >>> model = DDP(FSDP(...))
2025-08-14T21:17:21.9168758Z             >>> FSDP.set_state_dict_type(
2025-08-14T21:17:21.9168908Z             >>>     model,
2025-08-14T21:17:21.9169042Z             >>>     StateDictType.SHARDED_STATE_DICT,
2025-08-14T21:17:21.9169284Z             >>>     state_dict_config = ShardedStateDictConfig(offload_to_cpu=True),
2025-08-14T21:17:21.9169645Z             >>>     optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True),
2025-08-14T21:17:21.9169769Z             >>> )
2025-08-14T21:17:21.9169965Z             >>> param_state_dict = model.state_dict()
2025-08-14T21:17:21.9170302Z             >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-08-14T21:17:21.9170595Z 
2025-08-14T21:17:21.9170744Z         Args:
2025-08-14T21:17:21.9170892Z             module (torch.nn.Module): Root module.
2025-08-14T21:17:21.9171124Z             state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-08-14T21:17:21.9171360Z             state_dict_config (Optional[StateDictConfig]): the configuration for the
2025-08-14T21:17:21.9171487Z                 target ``state_dict_type``.
2025-08-14T21:17:21.9171739Z             optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration
2025-08-14T21:17:21.9171855Z                 for the optimizer state dict.
2025-08-14T21:17:21.9171873Z 
2025-08-14T21:17:21.9171957Z         Returns:
2025-08-14T21:17:21.9172178Z             A StateDictSettings that include the previous state_dict type and
2025-08-14T21:17:21.9172303Z             configuration for the module.
2025-08-14T21:17:21.9172386Z         
2025-08-14T21:17:21.9172640Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9172645Z 
2025-08-14T21:17:21.9173479Z msg = Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792.
2025-08-14T21:17:21.9173742Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9174050Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-08-14T21:17:21.9174097Z 
2025-08-14T21:17:21.9174417Z         This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of
2025-08-14T21:17:21.9174547Z         :meth:`set_state_dict_type` for the detail.
2025-08-14T21:17:21.9174568Z 
2025-08-14T21:17:21.9174663Z         Example::
2025-08-14T21:17:21.9174667Z 
2025-08-14T21:17:21.9174797Z             >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9174917Z             >>> model = DDP(FSDP(...))
2025-08-14T21:17:21.9175031Z             >>> with FSDP.state_dict_type(
2025-08-14T21:17:21.9175121Z             >>>     model,
2025-08-14T21:17:21.9175262Z             >>>     StateDictType.SHARDED_STATE_DICT,
2025-08-14T21:17:21.9175346Z             >>> ):
2025-08-14T21:17:21.9175466Z             >>>     checkpoint = model.state_dict()
2025-08-14T21:17:21.9175484Z 
2025-08-14T21:17:21.9175564Z         Args:
2025-08-14T21:17:21.9175688Z             module (torch.nn.Module): Root module.
2025-08-14T21:17:21.9175934Z             state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-08-14T21:17:21.9176163Z             state_dict_config (Optional[StateDictConfig]): the model ``state_dict``
2025-08-14T21:17:21.9176320Z                 configuration for the target ``state_dict_type``.
2025-08-14T21:17:21.9176562Z             optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer
2025-08-14T21:17:21.9176759Z                ``state_dict`` configuration for the target ``state_dict_type``.
2025-08-14T21:17:21.9176846Z         
2025-08-14T21:17:21.9177108Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9177113Z 
2025-08-14T21:17:21.9222996Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805.
2025-08-14T21:17:21.9223299Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9223312Z 
2025-08-14T21:17:21.9223555Z Transform the state-dict of an optimizer corresponding to a sharded model.
2025-08-14T21:17:21.9223561Z 
2025-08-14T21:17:21.9223769Z The given state-dict can be transformed to one of three types:
2025-08-14T21:17:21.9224071Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict.
2025-08-14T21:17:21.9224076Z 
2025-08-14T21:17:21.9224308Z For full optimizer state_dict, all states are unflattened and not sharded.
2025-08-14T21:17:21.9224741Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to
2025-08-14T21:17:21.9224833Z avoid OOM.
2025-08-14T21:17:21.9224837Z 
2025-08-14T21:17:21.9225087Z For sharded optimizer state_dict, all states are unflattened but sharded.
2025-08-14T21:17:21.9225290Z CPU only can be specified via :meth:`state_dict_type` to further save
2025-08-14T21:17:21.9225377Z memory.
2025-08-14T21:17:21.9225384Z 
2025-08-14T21:17:21.9225627Z For local state_dict, no transformation will be performed. But a state
2025-08-14T21:17:21.9225975Z will be converted from nn.Tensor to ShardedTensor to represent its sharding
2025-08-14T21:17:21.9226103Z nature (this is not supported yet).
2025-08-14T21:17:21.9226126Z 
2025-08-14T21:17:21.9226258Z Example::
2025-08-14T21:17:21.9226262Z 
2025-08-14T21:17:21.9226396Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9226649Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:21.9226815Z     >>> from torch.distributed.fsdp import StateDictType
2025-08-14T21:17:21.9227064Z     >>> from torch.distributed.fsdp import FullStateDictConfig
2025-08-14T21:17:21.9227283Z     >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-08-14T21:17:21.9227385Z     >>> # Save a checkpoint
2025-08-14T21:17:21.9227484Z     >>> model, optim = ...
2025-08-14T21:17:21.9227606Z     >>> FSDP.set_state_dict_type(
2025-08-14T21:17:21.9227748Z     >>>     model,
2025-08-14T21:17:21.9227962Z     >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:21.9228092Z     >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9228251Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9228336Z     >>> )
2025-08-14T21:17:21.9228447Z     >>> state_dict = model.state_dict()
2025-08-14T21:17:21.9228634Z     >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-08-14T21:17:21.9228780Z     >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-08-14T21:17:21.9228880Z     >>> # Load a checkpoint
2025-08-14T21:17:21.9228991Z     >>> model, optim = ...
2025-08-14T21:17:21.9229139Z     >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-08-14T21:17:21.9229246Z     >>> FSDP.set_state_dict_type(
2025-08-14T21:17:21.9229345Z     >>>     model,
2025-08-14T21:17:21.9229460Z     >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:21.9229600Z     >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9229742Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9229828Z     >>> )
2025-08-14T21:17:21.9229954Z     >>> model.load_state_dict(state_dict)
2025-08-14T21:17:21.9230102Z     >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:21.9230213Z     >>>     model, optim, optim_state_dict
2025-08-14T21:17:21.9230306Z     >>> )
2025-08-14T21:17:21.9230428Z     >>> optim.load_state_dict(optim_state_dict)
2025-08-14T21:17:21.9230433Z 
2025-08-14T21:17:21.9230514Z Args:
2025-08-14T21:17:21.9230722Z     model (torch.nn.Module): Root module (which may or may not be a
2025-08-14T21:17:21.9230920Z         :class:`FullyShardedDataParallel` instance) whose parameters
2025-08-14T21:17:21.9231061Z         were passed into the optimizer ``optim``.
2025-08-14T21:17:21.9231238Z     optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-08-14T21:17:21.9231328Z         parameters.
2025-08-14T21:17:21.9231648Z     optim_state_dict (Dict[str, Any]): the target optimizer state_dict to
2025-08-14T21:17:21.9231863Z         transform. If the value is None, optim.state_dict() will be used. (
2025-08-14T21:17:21.9231959Z         Default: ``None``)
2025-08-14T21:17:21.9232208Z     group (dist.ProcessGroup): Model's process group across which parameters
2025-08-14T21:17:21.9232395Z         are sharded or ``None`` if using the default process group. (
2025-08-14T21:17:21.9232500Z         Default: ``None``)
2025-08-14T21:17:21.9232505Z 
2025-08-14T21:17:21.9232589Z Returns:
2025-08-14T21:17:21.9232850Z     Dict[str, Any]: A :class:`dict` containing the optimizer state for
2025-08-14T21:17:21.9233032Z     ``model``. The sharding of the optimizer state is based on
2025-08-14T21:17:21.9233129Z     ``state_dict_type``.
2025-08-14T21:17:21.9233133Z 
2025-08-14T21:17:21.9233387Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9233404Z 
2025-08-14T21:17:21.9234247Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903.
2025-08-14T21:17:21.9234510Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9234515Z 
2025-08-14T21:17:21.9234883Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model.
2025-08-14T21:17:21.9234888Z 
2025-08-14T21:17:21.9235057Z Given a ``optim_state_dict`` that is transformed through
2025-08-14T21:17:21.9235284Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer
2025-08-14T21:17:21.9235493Z state_dict that can be loaded to ``optim`` which is the optimizer for
2025-08-14T21:17:21.9235679Z ``model``. ``model`` must be sharded by FullyShardedDataParallel.
2025-08-14T21:17:21.9235684Z 
2025-08-14T21:17:21.9235819Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:21.9236054Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:21.9236240Z     >>> from torch.distributed.fsdp import StateDictType
2025-08-14T21:17:21.9236461Z     >>> from torch.distributed.fsdp import FullStateDictConfig
2025-08-14T21:17:21.9236659Z     >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-08-14T21:17:21.9236768Z     >>> # Save a checkpoint
2025-08-14T21:17:21.9236865Z     >>> model, optim = ...
2025-08-14T21:17:21.9236968Z     >>> FSDP.set_state_dict_type(
2025-08-14T21:17:21.9237065Z     >>>     model,
2025-08-14T21:17:21.9237182Z     >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:21.9237313Z     >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9237469Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9237550Z     >>> )
2025-08-14T21:17:21.9237661Z     >>> state_dict = model.state_dict()
2025-08-14T21:17:21.9237786Z     >>> original_osd = optim.state_dict()
2025-08-14T21:17:21.9237911Z     >>> optim_state_dict = FSDP.optim_state_dict(
2025-08-14T21:17:21.9238010Z     >>>     model,
2025-08-14T21:17:21.9238096Z     >>>     optim,
2025-08-14T21:17:21.9238208Z     >>>     optim_state_dict=original_osd
2025-08-14T21:17:21.9238303Z     >>> )
2025-08-14T21:17:21.9238446Z     >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-08-14T21:17:21.9238544Z     >>> # Load a checkpoint
2025-08-14T21:17:21.9238653Z     >>> model, optim = ...
2025-08-14T21:17:21.9238801Z     >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-08-14T21:17:21.9238906Z     >>> FSDP.set_state_dict_type(
2025-08-14T21:17:21.9239003Z     >>>     model,
2025-08-14T21:17:21.9239122Z     >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:21.9239248Z     >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9239403Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:21.9239486Z     >>> )
2025-08-14T21:17:21.9239612Z     >>> model.load_state_dict(state_dict)
2025-08-14T21:17:21.9239759Z     >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:21.9239872Z     >>>     model, optim, optim_state_dict
2025-08-14T21:17:21.9239969Z     >>> )
2025-08-14T21:17:21.9240093Z     >>> optim.load_state_dict(optim_state_dict)
2025-08-14T21:17:21.9240098Z 
2025-08-14T21:17:21.9240179Z Args:
2025-08-14T21:17:21.9240383Z     model (torch.nn.Module): Root module (which may or may not be a
2025-08-14T21:17:21.9240583Z         :class:`FullyShardedDataParallel` instance) whose parameters
2025-08-14T21:17:21.9240711Z         were passed into the optimizer ``optim``.
2025-08-14T21:17:21.9240954Z     optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-08-14T21:17:21.9241051Z         parameters.
2025-08-14T21:17:21.9241273Z     optim_state_dict (Dict[str, Any]): The optimizer states to be loaded.
2025-08-14T21:17:21.9241471Z     is_named_optimizer (bool): Is this optimizer a NamedOptimizer or
2025-08-14T21:17:21.9241660Z         KeyedOptimizer. Only set to True if ``optim`` is TorchRec's
2025-08-14T21:17:21.9241846Z         KeyedOptimizer or torch.distributed's NamedOptimizer.
2025-08-14T21:17:21.9242042Z     load_directly (bool): If this is set to True, this API will also
2025-08-14T21:17:21.9242241Z         call optim.load_state_dict(result) before returning the result.
2025-08-14T21:17:21.9242471Z         Otherwise, users are responsible to call ``optim.load_state_dict()``
2025-08-14T21:17:21.9242569Z         (Default: ``False``)
2025-08-14T21:17:21.9242818Z     group (dist.ProcessGroup): Model's process group across which parameters
2025-08-14T21:17:21.9242998Z         are sharded or ``None`` if using the default process group. (
2025-08-14T21:17:21.9243098Z         Default: ``None``)
2025-08-14T21:17:21.9243103Z 
2025-08-14T21:17:21.9243363Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9243367Z 
2025-08-14T21:17:21.9788580Z msg = Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129.
2025-08-14T21:17:21.9789080Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9789138Z 
2025-08-14T21:17:21.9789366Z RemoteModule instance can only be created after RPC initialization.
2025-08-14T21:17:21.9789407Z 
2025-08-14T21:17:21.9789614Z It creates a user-specified module on a specified remote node.
2025-08-14T21:17:21.9789847Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-08-14T21:17:21.9789955Z executed on the remote node.
2025-08-14T21:17:21.9790210Z It takes care of autograd recording to ensure the backward pass propagates
2025-08-14T21:17:21.9790363Z gradients back to the corresponding remote module.
2025-08-14T21:17:21.9790736Z It can be shared across processors using `RPC framework <https://pytorch.org/docs/stable/rpc.html>`__,
2025-08-14T21:17:21.9790932Z without incurring any overheads of copying the actual module,
2025-08-14T21:17:21.9791131Z which is equivalent to an :class:`~torch.distributed.rpc.RRef`
2025-08-14T21:17:21.9791254Z pointing to the remote module.
2025-08-14T21:17:21.9791260Z 
2025-08-14T21:17:21.9791513Z The arguments of ``forward_async`` and ``forward`` are the same as
2025-08-14T21:17:21.9791714Z the ``forward`` method of the module returned by the ``module_cls``.
2025-08-14T21:17:21.9791733Z 
2025-08-14T21:17:21.9792039Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now.
2025-08-14T21:17:21.9792044Z 
2025-08-14T21:17:21.9792293Z Particularly, to create a hybrid model, typically the local modules should be
2025-08-14T21:17:21.9792683Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``).
2025-08-14T21:17:21.9792775Z Hybrid Example:
2025-08-14T21:17:21.9792888Z         >>> class HybridModel(nn.Module):
2025-08-14T21:17:21.9793015Z         >>>     def __init__(self) -> None:
2025-08-14T21:17:21.9793124Z         >>>         nn.Module.__init__(self)
2025-08-14T21:17:21.9793274Z         >>>         self.remote_embedding = RemoteModule(...)
2025-08-14T21:17:21.9793401Z         >>>         self.local_linear = nn.Linear(...)
2025-08-14T21:17:21.9793405Z 
2025-08-14T21:17:21.9793601Z For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-08-14T21:17:21.9793857Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``,
2025-08-14T21:17:21.9794062Z the generated ``RemoteModule`` will have 2 methods in signature of
2025-08-14T21:17:21.9794191Z ``def forward(input: Tensor) -> Tensor:`` and
2025-08-14T21:17:21.9794497Z ``def forward_async(input: Tensor) -> Future[Tensor]:``.
2025-08-14T21:17:21.9794502Z 
2025-08-14T21:17:21.9794611Z .. note::
2025-08-14T21:17:21.9794768Z     If the remote module is placed on a cuda device,
2025-08-14T21:17:21.9795002Z     any input CPU tensors will be automatically moved to the same cuda device,
2025-08-14T21:17:21.9795400Z     and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend.
2025-08-14T21:17:21.9795407Z 
2025-08-14T21:17:21.9795505Z Args:
2025-08-14T21:17:21.9795801Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:21.9796103Z         The device can be a local device or a remote device specified by one of the following remote
2025-08-14T21:17:21.9796191Z         formats:
2025-08-14T21:17:21.9796195Z 
2025-08-14T21:17:21.9796334Z             1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-08-14T21:17:21.9796557Z             2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-08-14T21:17:21.9796569Z 
2025-08-14T21:17:21.9796936Z         In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:21.9797056Z     module_cls (nn.Module): For example,
2025-08-14T21:17:21.9797176Z         >>> class MyModule(nn.Module):
2025-08-14T21:17:21.9797278Z         >>>     def forward(input):
2025-08-14T21:17:21.9797431Z         >>>         return input + 1
2025-08-14T21:17:21.9797581Z         >>>
2025-08-14T21:17:21.9797684Z         >>> module_cls = MyModule
2025-08-14T21:17:21.9797983Z     args (Sequence, optional): args to be passed to ``module_cls``.
2025-08-14T21:17:21.9798174Z     kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-08-14T21:17:21.9798455Z     _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-08-14T21:17:21.9798872Z         to be created. The type object should be decorated by @torch.jit.interface.
2025-08-14T21:17:21.9799309Z         If not provided, the generated RemoteModule is not torchscript-able.
2025-08-14T21:17:21.9799610Z         Warning, this is an experimental API and susceptible to frequent changes.
2025-08-14T21:17:21.9799615Z 
2025-08-14T21:17:21.9799703Z Returns:
2025-08-14T21:17:21.9799944Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:21.9800185Z     user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-08-14T21:17:21.9800456Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:21.9800597Z     on the user-provided module on the remote side.
2025-08-14T21:17:21.9800602Z 
2025-08-14T21:17:21.9800704Z Example::
2025-08-14T21:17:21.9800856Z     Run the following code in two different processes:
2025-08-14T21:17:21.9800860Z 
2025-08-14T21:17:21.9800984Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:21.9801073Z     >>> # On worker 0:
2025-08-14T21:17:21.9801181Z     >>> import torch
2025-08-14T21:17:21.9801322Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9801427Z     >>> from torch import nn, Tensor
2025-08-14T21:17:21.9801648Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:21.9801746Z     >>>
2025-08-14T21:17:21.9801883Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:21.9802006Z     >>> remote_linear_module = RemoteModule(
2025-08-14T21:17:21.9802144Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:21.9802233Z     >>> )
2025-08-14T21:17:21.9802350Z     >>> input = torch.randn(128, 20)
2025-08-14T21:17:21.9802502Z     >>> ret_fut = remote_linear_module.forward_async(input)
2025-08-14T21:17:21.9802602Z     >>> ret = ret_fut.wait()
2025-08-14T21:17:21.9802715Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9802719Z 
2025-08-14T21:17:21.9802811Z     >>> # On worker 1:
2025-08-14T21:17:21.9802899Z     >>> import torch
2025-08-14T21:17:21.9803039Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9803122Z     >>>
2025-08-14T21:17:21.9803335Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:21.9803444Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9803449Z 
2025-08-14T21:17:21.9803704Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9803708Z 
2025-08-14T21:17:21.9804458Z msg = Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506.
2025-08-14T21:17:21.9804727Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9804732Z 
2025-08-14T21:17:21.9805197Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef.
2025-08-14T21:17:21.9805204Z 
2025-08-14T21:17:21.9805701Z This alternate initialization method can be particularly useful if we want to create multiple
2025-08-14T21:17:21.9806098Z RemoteModule instances that share the same underlying module and reduce memory consumption.
2025-08-14T21:17:21.9806109Z 
2025-08-14T21:17:21.9806424Z Moreover, this also provides a workaround for passing script RemoteModule over RPC,
2025-08-14T21:17:21.9806691Z which is not supported. The recommended way is as follows:
2025-08-14T21:17:21.9806698Z 
2025-08-14T21:17:21.9806893Z     1. the sender creates a RemoteModule;
2025-08-14T21:17:21.9807163Z     2. the sender sends its ``module_rref`` over RPC;
2025-08-14T21:17:21.9807831Z     3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``.
2025-08-14T21:17:21.9807881Z 
2025-08-14T21:17:21.9807978Z Example::
2025-08-14T21:17:21.9808134Z     Run the following code in two different processes:
2025-08-14T21:17:21.9808138Z 
2025-08-14T21:17:21.9808265Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:21.9808354Z     >>> # On worker 0:
2025-08-14T21:17:21.9808450Z     >>> import torch
2025-08-14T21:17:21.9808591Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9808703Z     >>> from torch import nn, Tensor
2025-08-14T21:17:21.9808943Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:21.9809214Z     >>>
2025-08-14T21:17:21.9809352Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:21.9809479Z     >>> remote_module = RemoteModule(
2025-08-14T21:17:21.9809604Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:21.9809691Z     >>> )
2025-08-14T21:17:21.9809794Z     >>>
2025-08-14T21:17:21.9809908Z     >>> remote_module1 = rpc.rpc_sync(
2025-08-14T21:17:21.9810004Z     >>>     "worker1/cpu",
2025-08-14T21:17:21.9810140Z     >>>     RemoteModule.init_from_module_rref,
2025-08-14T21:17:21.9810291Z     >>>     ("worker1/cpu", remote_module1.get_module_rref()),
2025-08-14T21:17:21.9810371Z     >>> )
2025-08-14T21:17:21.9810477Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9810481Z 
2025-08-14T21:17:21.9810569Z     >>> # On worker 1:
2025-08-14T21:17:21.9810670Z     >>> import torch
2025-08-14T21:17:21.9810795Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9810877Z     >>>
2025-08-14T21:17:21.9811025Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:21.9811117Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9811122Z 
2025-08-14T21:17:21.9811203Z Args:
2025-08-14T21:17:21.9811510Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:21.9811801Z         The device can be a local device or a remote device specified by one of the following remote
2025-08-14T21:17:21.9811901Z         formats:
2025-08-14T21:17:21.9811905Z 
2025-08-14T21:17:21.9812045Z             1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-08-14T21:17:21.9812195Z             2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-08-14T21:17:21.9812200Z 
2025-08-14T21:17:21.9812457Z         In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:21.9812831Z     module_rref (RRef[nn.Module]): The module reference shared by both the caller and
2025-08-14T21:17:21.9812942Z         the created remote module.
2025-08-14T21:17:21.9813235Z     _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-08-14T21:17:21.9813470Z         to be created. The type object should be decorated by @torch.jit.interface.
2025-08-14T21:17:21.9813701Z         If not provided, the generated RemoteModule is not torchscript-able.
2025-08-14T21:17:21.9813936Z         Warning, this is an experimental API and susceptible to frequent changes.
2025-08-14T21:17:21.9813944Z 
2025-08-14T21:17:21.9814030Z Returns:
2025-08-14T21:17:21.9814289Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:21.9814521Z     user-provided ``module_rref``, it has a blocking ``forward`` method and an
2025-08-14T21:17:21.9814807Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:21.9814947Z     on the user-provided module on the remote side.
2025-08-14T21:17:21.9814955Z 
2025-08-14T21:17:21.9815207Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9815211Z 
2025-08-14T21:17:21.9815871Z msg = Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598.
2025-08-14T21:17:21.9816131Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:21.9816234Z 
2025-08-14T21:17:21.9816466Z     A RemoteModule instance can only be created after RPC initialization.
2025-08-14T21:17:21.9816470Z 
2025-08-14T21:17:21.9816661Z     It creates a user-specified module on a specified remote node.
2025-08-14T21:17:21.9816902Z     It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-08-14T21:17:21.9817009Z     executed on the remote node.
2025-08-14T21:17:21.9817241Z     It takes care of autograd recording to ensure the backward pass propagates
2025-08-14T21:17:21.9817415Z     gradients back to the corresponding remote module.
2025-08-14T21:17:21.9817419Z 
2025-08-14T21:17:21.9817640Z     It generates two methods ``forward_async`` and ``forward`` based on the
2025-08-14T21:17:21.9817867Z     signature of the ``forward`` method of ``module_cls``. ``forward_async``
2025-08-14T21:17:21.9818115Z     runs asynchronously and returns a Future. The arguments of ``forward_async``
2025-08-14T21:17:21.9818315Z     and ``forward`` are the same as the ``forward`` method of the module
2025-08-14T21:17:21.9818440Z     returned by the ``module_cls``.
2025-08-14T21:17:21.9818445Z 
2025-08-14T21:17:21.9818644Z     For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-08-14T21:17:21.9818895Z     that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``,
2025-08-14T21:17:21.9819129Z     the generated ``RemoteModule`` will have 2 methods with the signatures:
2025-08-14T21:17:21.9819133Z 
2025-08-14T21:17:21.9819260Z     | ``def forward(input: Tensor) -> Tensor:``
2025-08-14T21:17:21.9819436Z     | ``def forward_async(input: Tensor) -> Future[Tensor]:``
2025-08-14T21:17:21.9819440Z 
2025-08-14T21:17:21.9819523Z Args:
2025-08-14T21:17:21.9819818Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:21.9820171Z         The format should be "<workername>/<device>", where the device field can be parsed as torch.device type.
2025-08-14T21:17:21.9820310Z         E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0".
2025-08-14T21:17:21.9820565Z         In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:21.9820807Z     module_cls (nn.Module): Class for the module to be created remotely. For example,
2025-08-14T21:17:21.9820811Z 
2025-08-14T21:17:21.9820921Z         >>> class MyModule(nn.Module):
2025-08-14T21:17:21.9821039Z         >>>     def forward(input):
2025-08-14T21:17:21.9821139Z         >>>         return input + 1
2025-08-14T21:17:21.9821221Z         >>>
2025-08-14T21:17:21.9821385Z         >>> module_cls = MyModule
2025-08-14T21:17:21.9821389Z 
2025-08-14T21:17:21.9821589Z     args (Sequence, optional): args to be passed to ``module_cls``.
2025-08-14T21:17:21.9821792Z     kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-08-14T21:17:21.9821796Z 
2025-08-14T21:17:21.9821878Z Returns:
2025-08-14T21:17:21.9822124Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:21.9822367Z     user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-08-14T21:17:21.9822636Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:21.9822779Z     on the user-provided module on the remote side.
2025-08-14T21:17:21.9822795Z 
2025-08-14T21:17:21.9822885Z Example::
2025-08-14T21:17:21.9823035Z     Run the following code in two different processes:
2025-08-14T21:17:21.9823040Z 
2025-08-14T21:17:21.9823166Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:21.9823262Z     >>> # On worker 0:
2025-08-14T21:17:21.9823352Z     >>> import torch
2025-08-14T21:17:21.9823490Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9823594Z     >>> from torch import nn, Tensor
2025-08-14T21:17:21.9823813Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:21.9823910Z     >>>
2025-08-14T21:17:21.9824049Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:21.9824216Z     >>> remote_linear_module = RemoteModule(
2025-08-14T21:17:21.9824367Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:21.9824450Z     >>> )
2025-08-14T21:17:21.9824567Z     >>> input = torch.randn(128, 20)
2025-08-14T21:17:21.9824718Z     >>> ret_fut = remote_linear_module.forward_async(input)
2025-08-14T21:17:21.9824819Z     >>> ret = ret_fut.wait()
2025-08-14T21:17:21.9824925Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9824929Z 
2025-08-14T21:17:21.9825020Z     >>> # On worker 1:
2025-08-14T21:17:21.9825115Z     >>> import torch
2025-08-14T21:17:21.9825251Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:21.9825333Z     >>>
2025-08-14T21:17:21.9825481Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:21.9825575Z     >>> rpc.shutdown()
2025-08-14T21:17:21.9825578Z 
2025-08-14T21:17:21.9825768Z     Furthermore, a more practical example that is combined with
2025-08-14T21:17:21.9826274Z     `DistributedDataParallel <https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel>`__ (DDP)
2025-08-14T21:17:21.9826603Z     can be found in this `tutorial <https://pytorch.org/tutorials/advanced/rpc_ddp_tutorial.html>`__.
2025-08-14T21:17:21.9826608Z 
2025-08-14T21:17:21.9826860Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:21.9826880Z 
2025-08-14T21:17:22.0048288Z msg = Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129.
2025-08-14T21:17:22.0049319Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.0049714Z 
2025-08-14T21:17:22.0049957Z DistributedOptimizer takes remote references to parameters scattered
2025-08-14T21:17:22.0050560Z across workers and applies the given optimizer locally for each parameter.
2025-08-14T21:17:22.0050915Z 
2025-08-14T21:17:22.0051162Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order
2025-08-14T21:17:22.0051668Z to retrieve the gradients for specific parameters.
2025-08-14T21:17:22.0051941Z 
2025-08-14T21:17:22.0052038Z Concurrent calls to
2025-08-14T21:17:22.0052398Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`,
2025-08-14T21:17:22.0052864Z either from the same or different clients, will
2025-08-14T21:17:22.0053334Z be serialized on each worker -- as each worker's optimizer can only work
2025-08-14T21:17:22.0053885Z on one set of gradients at a time. However, there is no guarantee that
2025-08-14T21:17:22.0054607Z the full forward-backward-optimizer sequence will execute for one client
2025-08-14T21:17:22.0055184Z at a time. This means that the gradients being applied may not correspond
2025-08-14T21:17:22.0055751Z to the latest forward pass executed on a given worker. Also, there is no
2025-08-14T21:17:22.0056212Z guaranteed ordering across workers.
2025-08-14T21:17:22.0056421Z 
2025-08-14T21:17:22.0056699Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled
2025-08-14T21:17:22.0057309Z by default, so that optimizer updates are not blocked by the Python Global
2025-08-14T21:17:22.0057905Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed
2025-08-14T21:17:22.0058512Z Model Parallel). This feature is currently enabled for most optimizers. You
2025-08-14T21:17:22.0059112Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support
2025-08-14T21:17:22.0059597Z for your own custom optimizers.
2025-08-14T21:17:22.0059805Z 
2025-08-14T21:17:22.0059889Z Args:
2025-08-14T21:17:22.0060211Z     optimizer_class (optim.Optimizer): the class of optimizer to
2025-08-14T21:17:22.0060624Z         instantiate on each worker.
2025-08-14T21:17:22.0061047Z     params_rref (list[RRef]): list of RRefs to local or remote parameters
2025-08-14T21:17:22.0061473Z         to optimize.
2025-08-14T21:17:22.0061831Z     args: arguments to pass to the optimizer constructor on each worker.
2025-08-14T21:17:22.0062438Z     kwargs: arguments to pass to the optimizer constructor on each worker.
2025-08-14T21:17:22.0062820Z 
2025-08-14T21:17:22.0062934Z Example::
2025-08-14T21:17:22.0063163Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:22.0063570Z     >>> import torch.distributed.autograd as dist_autograd
2025-08-14T21:17:22.0063975Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:22.0064304Z     >>> from torch import optim
2025-08-14T21:17:22.0076859Z     >>> from torch.distributed.optim import DistributedOptimizer
2025-08-14T21:17:22.0077351Z     >>>
2025-08-14T21:17:22.0077619Z     >>> with dist_autograd.context() as context_id:
2025-08-14T21:17:22.0077978Z     >>>   # Forward pass.
2025-08-14T21:17:22.0078357Z     >>>   rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3))
2025-08-14T21:17:22.0078884Z     >>>   rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1))
2025-08-14T21:17:22.0079324Z     >>>   loss = rref1.to_here() + rref2.to_here()
2025-08-14T21:17:22.0079662Z     >>>
2025-08-14T21:17:22.0079885Z     >>>   # Backward pass.
2025-08-14T21:17:22.0080201Z     >>>   dist_autograd.backward(context_id, [loss.sum()])
2025-08-14T21:17:22.0080558Z     >>>
2025-08-14T21:17:22.0080769Z     >>>   # Optimizer.
2025-08-14T21:17:22.0081040Z     >>>   dist_optim = DistributedOptimizer(
2025-08-14T21:17:22.0081369Z     >>>      optim.SGD,
2025-08-14T21:17:22.0081629Z     >>>      [rref1, rref2],
2025-08-14T21:17:22.0081884Z     >>>      lr=0.05,
2025-08-14T21:17:22.0082126Z     >>>   )
2025-08-14T21:17:22.0082370Z     >>>   dist_optim.step(context_id)
2025-08-14T21:17:22.0082581Z 
2025-08-14T21:17:22.0082763Z __ https://github.com/pytorch/tutorials/pull/1465
2025-08-14T21:17:22.0083027Z 
2025-08-14T21:17:22.0083281Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.0083663Z 
2025-08-14T21:17:22.0084395Z msg = Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9.
2025-08-14T21:17:22.0085477Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.0085855Z 
2025-08-14T21:17:22.0086254Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-08-14T21:17:22.0086901Z This optimizer runs local optimizer at every step.
2025-08-14T21:17:22.0087506Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied.
2025-08-14T21:17:22.0087971Z 
2025-08-14T21:17:22.0088190Z Args:
2025-08-14T21:17:22.0088421Z     optim: The local optimizer.
2025-08-14T21:17:22.0088829Z     averager: A model averager instance to run post-localSGD algorithm.
2025-08-14T21:17:22.0089176Z 
2025-08-14T21:17:22.0089275Z Example::
2025-08-14T21:17:22.0089398Z 
2025-08-14T21:17:22.0089537Z     >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:22.0089857Z     >>> import torch
2025-08-14T21:17:22.0090127Z     >>> import torch.distributed as dist
2025-08-14T21:17:22.0090632Z     >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-08-14T21:17:22.0091133Z     >>> import torch.nn as nn
2025-08-14T21:17:22.0091509Z     >>> from torch.distributed.optim import PostLocalSGDOptimizer
2025-08-14T21:17:22.0092092Z     >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-08-14T21:17:22.0092598Z     >>>   PostLocalSGDState,
2025-08-14T21:17:22.0092879Z     >>>   post_localSGD_hook,
2025-08-14T21:17:22.0093153Z     >>> )
2025-08-14T21:17:22.0093364Z     >>>
2025-08-14T21:17:22.0093630Z     >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:22.0094044Z     >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:22.0094386Z     >>> )
2025-08-14T21:17:22.0094583Z     >>>
2025-08-14T21:17:22.0094848Z     >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:22.0095403Z     >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-08-14T21:17:22.0096082Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:22.0096434Z     >>>
2025-08-14T21:17:22.0096764Z     >>> # Create a post-localSGD optimizer that wraps a local optimizer.
2025-08-14T21:17:22.0097342Z     >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as
2025-08-14T21:17:22.0097872Z     >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:22.0098373Z     >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01)
2025-08-14T21:17:22.0098832Z     >>> opt = PostLocalSGDOptimizer(
2025-08-14T21:17:22.0099161Z     >>>     optim=local_optim,
2025-08-14T21:17:22.0099588Z     >>>     averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-08-14T21:17:22.0100039Z     >>> )
2025-08-14T21:17:22.0100249Z     >>>
2025-08-14T21:17:22.0100586Z     >>> # In the first 100 steps, DDP runs global gradient averaging at every step.
2025-08-14T21:17:22.0101244Z     >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default),
2025-08-14T21:17:22.0102050Z     >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer.
2025-08-14T21:17:22.0102644Z     >>> for step in range(0, 200):
2025-08-14T21:17:22.0102949Z     >>>    opt.zero_grad()
2025-08-14T21:17:22.0103239Z     >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:22.0103567Z     >>>    loss.backward()
2025-08-14T21:17:22.0103821Z     >>>    opt.step()
2025-08-14T21:17:22.0103992Z 
2025-08-14T21:17:22.0104244Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.0104613Z 
2025-08-14T21:17:22.0192851Z msg = Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284.
2025-08-14T21:17:22.0193970Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.0194368Z 
2025-08-14T21:17:22.0194785Z Wrap an arbitrary :class:`optim.Optimizer <torch.optim.Optimizer>` and shards its states across ranks in the group.
2025-08-14T21:17:22.0195306Z 
2025-08-14T21:17:22.0195555Z The sharing is done as described by `ZeRO <https://arxiv.org/abs/1910.02054>`_.
2025-08-14T21:17:22.0195931Z 
2025-08-14T21:17:22.0196076Z The local optimizer instance in each rank is only
2025-08-14T21:17:22.0196578Z responsible for updating approximately ``1 / world_size`` parameters and
2025-08-14T21:17:22.0197328Z hence only needs to keep ``1 / world_size`` optimizer states. After
2025-08-14T21:17:22.0197884Z parameters are updated locally, each rank will broadcast its parameters to
2025-08-14T21:17:22.0198436Z all other peers to keep all model replicas in the same state.
2025-08-14T21:17:22.0198934Z ``ZeroRedundancyOptimizer`` can be used in conjunction with
2025-08-14T21:17:22.0199490Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak
2025-08-14T21:17:22.0199976Z memory consumption.
2025-08-14T21:17:22.0200127Z 
2025-08-14T21:17:22.0200399Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number
2025-08-14T21:17:22.0201011Z of parameters at each rank. Each parameter belongs to a single rank and is
2025-08-14T21:17:22.0201593Z not divided among ranks. The partition is arbitrary and might not match the
2025-08-14T21:17:22.0202086Z the parameter registration or usage order.
2025-08-14T21:17:22.0202320Z 
2025-08-14T21:17:22.0202421Z Arguments:
2025-08-14T21:17:22.0202736Z     params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s
2025-08-14T21:17:22.0203238Z         or :class:`dict` s giving all parameters, which will be sharded
2025-08-14T21:17:22.0203645Z         across ranks.
2025-08-14T21:17:22.0203802Z 
2025-08-14T21:17:22.0203908Z Keyword Args:
2025-08-14T21:17:22.0204258Z     optimizer_class (:class:`torch.nn.Optimizer`): the class of the local
2025-08-14T21:17:22.0204758Z         optimizer.
2025-08-14T21:17:22.0205121Z     process_group (``ProcessGroup``, optional): ``torch.distributed``
2025-08-14T21:17:22.0205687Z         ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by
2025-08-14T21:17:22.0206155Z         :meth:`torch.distributed.init_process_group`).
2025-08-14T21:17:22.0206653Z     parameters_as_bucket_view (bool, optional): if ``True``, parameters are
2025-08-14T21:17:22.0207208Z         packed into buckets to speed up communication, and ``param.data``
2025-08-14T21:17:22.0207752Z         fields point to bucket views at different offsets; if ``False``,
2025-08-14T21:17:22.0208288Z         each individual parameter is communicated separately, and each
2025-08-14T21:17:22.0208768Z         ``params.data`` stays intact (default: ``False``).
2025-08-14T21:17:22.0209451Z     overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is
2025-08-14T21:17:22.0209968Z         overlapped with :class:`DistributedDataParallel` 's gradient
2025-08-14T21:17:22.0210514Z         synchronization; this requires (1) either a functional optimizer
2025-08-14T21:17:22.0211024Z         for the ``optimizer_class`` argument or one with a functional
2025-08-14T21:17:22.0211508Z         equivalent and (2) registering a DDP communication hook
2025-08-14T21:17:22.0212010Z         constructed from one of the functions in ``ddp_zero_hook.py``;
2025-08-14T21:17:22.0212497Z         parameters are packed into buckets matching those in
2025-08-14T21:17:22.0212926Z         :class:`DistributedDataParallel`, meaning that the
2025-08-14T21:17:22.0213359Z         ``parameters_as_bucket_view`` argument is ignored.
2025-08-14T21:17:22.0213812Z         If ``False``, :meth:`step` runs disjointly after the backward pass
2025-08-14T21:17:22.0214205Z         (per normal).
2025-08-14T21:17:22.0214470Z         (default: ``False``)
2025-08-14T21:17:22.0214864Z     **defaults: any trailing arguments, which are forwarded to the local
2025-08-14T21:17:22.0215289Z         optimizer.
2025-08-14T21:17:22.0215431Z 
2025-08-14T21:17:22.0215539Z Example::
2025-08-14T21:17:22.0215676Z 
2025-08-14T21:17:22.0215773Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:22.0216053Z     >>> import torch.nn as nn
2025-08-14T21:17:22.0216436Z     >>> from torch.distributed.optim import ZeroRedundancyOptimizer
2025-08-14T21:17:22.0216959Z     >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-08-14T21:17:22.0217504Z     >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)])
2025-08-14T21:17:22.0217958Z     >>> ddp = DDP(model, device_ids=[rank])
2025-08-14T21:17:22.0218419Z     >>> opt = ZeroRedundancyOptimizer(
2025-08-14T21:17:22.0218751Z     >>>     ddp.parameters(),
2025-08-14T21:17:22.0219066Z     >>>     optimizer_class=torch.optim.Adam,
2025-08-14T21:17:22.0219376Z     >>>     lr=0.01
2025-08-14T21:17:22.0219604Z     >>> )
2025-08-14T21:17:22.0219833Z     >>> ddp(inputs).sum().backward()
2025-08-14T21:17:22.0220121Z     >>> opt.step()
2025-08-14T21:17:22.0220274Z 
2025-08-14T21:17:22.0220366Z .. warning::
2025-08-14T21:17:22.0220709Z     Currently, ``ZeroRedundancyOptimizer`` requires that all of the
2025-08-14T21:17:22.0221171Z     passed-in parameters are the same dense type.
2025-08-14T21:17:22.0221437Z 
2025-08-14T21:17:22.0221525Z .. warning::
2025-08-14T21:17:22.0221871Z     If you pass ``overlap_with_ddp=True``, be wary of the following: Given
2025-08-14T21:17:22.0222407Z     the way that overlapping :class:`DistributedDataParallel` with
2025-08-14T21:17:22.0222948Z     :class:`ZeroRedundancyOptimizer` is currently implemented, the first
2025-08-14T21:17:22.0223528Z     two or three training iterations do not perform parameter updates in
2025-08-14T21:17:22.0224077Z     the optimizer step, depending on if ``static_graph=False`` or
2025-08-14T21:17:22.0224561Z     ``static_graph=True``, respectively. This is because it needs
2025-08-14T21:17:22.0225055Z     information about the gradient bucketing strategy used by
2025-08-14T21:17:22.0225581Z     :class:`DistributedDataParallel`, which is not finalized until the
2025-08-14T21:17:22.0226165Z     second forward pass if ``static_graph=False`` or until the third
2025-08-14T21:17:22.0226728Z     forward pass if ``static_graph=True``. To adjust for this, one option
2025-08-14T21:17:22.0227168Z     is to prepend dummy inputs.
2025-08-14T21:17:22.0227359Z 
2025-08-14T21:17:22.0227624Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change.
2025-08-14T21:17:22.0227992Z 
2025-08-14T21:17:22.0228244Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.0228625Z 
2025-08-14T21:17:22.0441059Z msg = Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29.
2025-08-14T21:17:22.0442078Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.0442462Z 
2025-08-14T21:17:22.0442707Z Custom reducer class that can be used to specify a custom operation that
2025-08-14T21:17:22.0443235Z reduces losses of multiple microbatches into one value.
2025-08-14T21:17:22.0443523Z 
2025-08-14T21:17:22.0443609Z Example:
2025-08-14T21:17:22.0443832Z >>> # xdoctest: +SKIP
2025-08-14T21:17:22.0444101Z >>> sum_reducer = _CustomReducer(
2025-08-14T21:17:22.0444394Z >>>     torch.tensor(0.0),
2025-08-14T21:17:22.0444670Z >>>     lambda a, b: a + b
2025-08-14T21:17:22.0444926Z >>> )
2025-08-14T21:17:22.0445037Z 
2025-08-14T21:17:22.0445287Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.0445670Z 
2025-08-14T21:17:22.0977244Z msg = Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6.
2025-08-14T21:17:22.0978997Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.0979392Z 
2025-08-14T21:17:22.0979635Z A decorator for a function indicating that the return value of the function
2025-08-14T21:17:22.0980218Z is guaranteed to be a :class:`~torch.futures.Future` object and this
2025-08-14T21:17:22.0980800Z function can run asynchronously on the RPC callee. More specifically, the
2025-08-14T21:17:22.0981393Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped
2025-08-14T21:17:22.0981993Z function and installs subsequent processing steps as a callback to that
2025-08-14T21:17:22.0982579Z :class:`~torch.futures.Future`. The installed callback will read the value
2025-08-14T21:17:22.0983136Z from the :class:`~torch.futures.Future` when completed and send the
2025-08-14T21:17:22.0983850Z value back as the RPC response. That also means the returned
2025-08-14T21:17:22.0984388Z :class:`~torch.futures.Future` only exists on the callee side and is never
2025-08-14T21:17:22.0984964Z sent through RPC. This decorator is useful when the wrapped function's
2025-08-14T21:17:22.0985493Z (``fn``) execution needs to pause and resume due to, e.g., containing
2025-08-14T21:17:22.0986037Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals.
2025-08-14T21:17:22.0986396Z 
2025-08-14T21:17:22.0986627Z .. note:: To enable asynchronous execution, applications must pass the
2025-08-14T21:17:22.0987193Z     function object returned by this decorator to RPC APIs. If RPC detected
2025-08-14T21:17:22.0987754Z     attributes installed by this decorator, it knows that this function
2025-08-14T21:17:22.0988282Z     returns a ``Future`` object and will handle that accordingly.
2025-08-14T21:17:22.0988801Z     However, this does not mean this decorator has to be outmost one when
2025-08-14T21:17:22.0989365Z     defining a function. For example, when combined with ``@staticmethod``
2025-08-14T21:17:22.0989930Z     or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the
2025-08-14T21:17:22.0990469Z     inner decorator to allow the target function be recognized as a static
2025-08-14T21:17:22.0991040Z     or class function. This target function can still execute asynchronously
2025-08-14T21:17:22.0991750Z     because, when accessed, the static or class method preserves attributes
2025-08-14T21:17:22.0992300Z     installed by ``@rpc.functions.async_execution``.
2025-08-14T21:17:22.0992579Z 
2025-08-14T21:17:22.0992584Z 
2025-08-14T21:17:22.0992676Z Example::
2025-08-14T21:17:22.0993005Z     The returned :class:`~torch.futures.Future` object can come from
2025-08-14T21:17:22.0993461Z     :meth:`~torch.distributed.rpc.rpc_async`,
2025-08-14T21:17:22.0993922Z     :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future`
2025-08-14T21:17:22.0994448Z     constructor. The example below shows directly using the
2025-08-14T21:17:22.0994871Z     :class:`~torch.futures.Future` returned by
2025-08-14T21:17:22.0995220Z     :meth:`~torch.futures.Future.then`.
2025-08-14T21:17:22.0995455Z 
2025-08-14T21:17:22.0995575Z     >>> from torch.distributed import rpc
2025-08-14T21:17:22.0995894Z     >>>
2025-08-14T21:17:22.0996114Z     >>> # omitting setup and shutdown RPC
2025-08-14T21:17:22.0996424Z     >>>
2025-08-14T21:17:22.0996638Z     >>> # On all workers
2025-08-14T21:17:22.0996922Z     >>> @rpc.functions.async_execution
2025-08-14T21:17:22.0997244Z     >>> def async_add_chained(to, x, y, z):
2025-08-14T21:17:22.0997658Z     >>>     # This function runs on "worker1" and returns immediately when
2025-08-14T21:17:22.0998163Z     >>>     # the callback is installed through the `then(cb)` API. In the
2025-08-14T21:17:22.0998642Z     >>>     # mean time, the `rpc_async` to "worker2" can run concurrently.
2025-08-14T21:17:22.0999104Z     >>>     # When the return value of that `rpc_async` arrives at
2025-08-14T21:17:22.0999570Z     >>>     # "worker1", "worker1" will run the lambda function accordingly
2025-08-14T21:17:22.1000051Z     >>>     # and set the value for the previously returned `Future`, which
2025-08-14T21:17:22.1000540Z     >>>     # will then trigger RPC to send the result back to "worker0".
2025-08-14T21:17:22.1001011Z     >>>     return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:22.1001407Z     >>>         lambda fut: fut.wait() + z
2025-08-14T21:17:22.1001700Z     >>>     )
2025-08-14T21:17:22.1001913Z     >>>
2025-08-14T21:17:22.1002117Z     >>> # On worker0
2025-08-14T21:17:22.1002354Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:22.1002622Z     >>> ret = rpc.rpc_sync(
2025-08-14T21:17:22.1002889Z     >>>     "worker1",
2025-08-14T21:17:22.1003133Z     >>>     async_add_chained,
2025-08-14T21:17:22.1003434Z     >>>     args=("worker2", torch.ones(2), 1, 1)
2025-08-14T21:17:22.1003751Z     >>> )
2025-08-14T21:17:22.1003977Z     >>> print(ret)  # prints tensor([3., 3.])
2025-08-14T21:17:22.1004303Z 
2025-08-14T21:17:22.1004616Z     When combined with TorchScript decorators, this decorator must be the
2025-08-14T21:17:22.1005099Z     outmost one.
2025-08-14T21:17:22.1005239Z 
2025-08-14T21:17:22.1005358Z     >>> from torch import Tensor
2025-08-14T21:17:22.1005660Z     >>> from torch.futures import Future
2025-08-14T21:17:22.1006009Z     >>> from torch.distributed import rpc
2025-08-14T21:17:22.1006323Z     >>>
2025-08-14T21:17:22.1006541Z     >>> # omitting setup and shutdown RPC
2025-08-14T21:17:22.1006852Z     >>>
2025-08-14T21:17:22.1007067Z     >>> # On all workers
2025-08-14T21:17:22.1007322Z     >>> @torch.jit.script
2025-08-14T21:17:22.1007639Z     >>> def script_add(x: Tensor, y: Tensor) -> Tensor:
2025-08-14T21:17:22.1007993Z     >>>     return x + y
2025-08-14T21:17:22.1008231Z     >>>
2025-08-14T21:17:22.1008464Z     >>> @rpc.functions.async_execution
2025-08-14T21:17:22.1008783Z     >>> @torch.jit.script
2025-08-14T21:17:22.1009308Z     >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]:
2025-08-14T21:17:22.1009748Z     >>>     return rpc.rpc_async(to, script_add, (x, y))
2025-08-14T21:17:22.1010091Z     >>>
2025-08-14T21:17:22.1010304Z     >>> # On worker0
2025-08-14T21:17:22.1010543Z     >>> ret = rpc.rpc_sync(
2025-08-14T21:17:22.1010814Z     >>>     "worker1",
2025-08-14T21:17:22.1011057Z     >>>     async_add,
2025-08-14T21:17:22.1011318Z     >>>     args=("worker2", torch.ones(2), 1)
2025-08-14T21:17:22.1011716Z     >>> )
2025-08-14T21:17:22.1012000Z     >>> print(ret)  # prints tensor([2., 2.])
2025-08-14T21:17:22.1012222Z 
2025-08-14T21:17:22.1012439Z     When combined with static or class method, this decorator must be the
2025-08-14T21:17:22.1012868Z     inner one.
2025-08-14T21:17:22.1012998Z 
2025-08-14T21:17:22.1013125Z     >>> from torch.distributed import rpc
2025-08-14T21:17:22.1013440Z     >>>
2025-08-14T21:17:22.1013660Z     >>> # omitting setup and shutdown RPC
2025-08-14T21:17:22.1013968Z     >>>
2025-08-14T21:17:22.1014185Z     >>> # On all workers
2025-08-14T21:17:22.1014452Z     >>> class AsyncExecutionClass:
2025-08-14T21:17:22.1014745Z     >>>
2025-08-14T21:17:22.1014961Z     >>>     @staticmethod
2025-08-14T21:17:22.1015232Z     >>>     @rpc.functions.async_execution
2025-08-14T21:17:22.1015578Z     >>>     def static_async_add(to, x, y, z):
2025-08-14T21:17:22.1015979Z     >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:22.1016371Z     >>>             lambda fut: fut.wait() + z
2025-08-14T21:17:22.1016681Z     >>>         )
2025-08-14T21:17:22.1016903Z     >>>
2025-08-14T21:17:22.1017101Z     >>>     @classmethod
2025-08-14T21:17:22.1017382Z     >>>     @rpc.functions.async_execution
2025-08-14T21:17:22.1017726Z     >>>     def class_async_add(cls, to, x, y, z):
2025-08-14T21:17:22.1018082Z     >>>         ret_fut = torch.futures.Future()
2025-08-14T21:17:22.1018455Z     >>>         rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:22.1018877Z     >>>             lambda fut: ret_fut.set_result(fut.wait() + z)
2025-08-14T21:17:22.1019232Z     >>>         )
2025-08-14T21:17:22.1019460Z     >>>         return ret_fut
2025-08-14T21:17:22.1019729Z     >>>
2025-08-14T21:17:22.1019965Z     >>>     @rpc.functions.async_execution
2025-08-14T21:17:22.1020304Z     >>>     def bound_async_add(self, to, x, y, z):
2025-08-14T21:17:22.1020714Z     >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:22.1021118Z     >>>             lambda fut: fut.wait() + z
2025-08-14T21:17:22.1021421Z     >>>         )
2025-08-14T21:17:22.1021648Z     >>>
2025-08-14T21:17:22.1021855Z     >>> # On worker0
2025-08-14T21:17:22.1022092Z     >>> ret = rpc.rpc_sync(
2025-08-14T21:17:22.1022360Z     >>>     "worker1",
2025-08-14T21:17:22.1022648Z     >>>     AsyncExecutionClass.static_async_add,
2025-08-14T21:17:22.1023011Z     >>>     args=("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:22.1023318Z     >>> )
2025-08-14T21:17:22.1023558Z     >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:22.1023964Z     >>>
2025-08-14T21:17:22.1024175Z     >>> ret = rpc.rpc_sync(
2025-08-14T21:17:22.1024451Z     >>>     "worker1",
2025-08-14T21:17:22.1024737Z     >>>     AsyncExecutionClass.class_async_add,
2025-08-14T21:17:22.1025147Z     >>>     args=("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:22.1025572Z     >>> )
2025-08-14T21:17:22.1025816Z     >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:22.1026105Z 
2025-08-14T21:17:22.1026266Z     This decorator also works with RRef helpers, i.e., .
2025-08-14T21:17:22.1026689Z     :meth:`torch.distributed.rpc.RRef.rpc_sync`,
2025-08-14T21:17:22.1027096Z     :meth:`torch.distributed.rpc.RRef.rpc_async`, and
2025-08-14T21:17:22.1027502Z     :meth:`torch.distributed.rpc.RRef.remote`.
2025-08-14T21:17:22.1027746Z 
2025-08-14T21:17:22.1027863Z     >>> from torch.distributed import rpc
2025-08-14T21:17:22.1028176Z     >>>
2025-08-14T21:17:22.1028426Z     >>> # reuse the AsyncExecutionClass class above
2025-08-14T21:17:22.1028821Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:22.1029298Z     >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:22.1029758Z     >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:22.1030059Z     >>>
2025-08-14T21:17:22.1030327Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:22.1030828Z     >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait()
2025-08-14T21:17:22.1031376Z     >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:22.1031775Z     >>>
2025-08-14T21:17:22.1032043Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:22.1032545Z     >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here()
2025-08-14T21:17:22.1033005Z     >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:22.1033271Z 
2025-08-14T21:17:22.1033522Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.1033901Z 
2025-08-14T21:17:22.1034615Z msg = Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113.
2025-08-14T21:17:22.1035701Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.1036079Z 
2025-08-14T21:17:22.1036295Z Set device mapping between each RPC caller and callee pair. This
2025-08-14T21:17:22.1036790Z function can be called multiple times to incrementally add
2025-08-14T21:17:22.1037203Z device placement configurations.
2025-08-14T21:17:22.1037404Z 
2025-08-14T21:17:22.1037496Z Args:
2025-08-14T21:17:22.1037704Z     to (str): Callee name.
2025-08-14T21:17:22.1038075Z     device_map (Dict of int, str, or torch.device): Device placement
2025-08-14T21:17:22.1038572Z         mappings from this worker to the callee. This map must be
2025-08-14T21:17:22.1038960Z         invertible.
2025-08-14T21:17:22.1039101Z 
2025-08-14T21:17:22.1039184Z Example:
2025-08-14T21:17:22.1039424Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:22.1039734Z     >>> # both workers
2025-08-14T21:17:22.1039970Z     >>> def add(x, y):
2025-08-14T21:17:22.1040263Z     >>>     print(x)  # tensor([1., 1.], device='cuda:1')
2025-08-14T21:17:22.1040619Z     >>>     return x + y, (x + y).to(2)
2025-08-14T21:17:22.1040904Z     >>>
2025-08-14T21:17:22.1041110Z     >>> # on worker 0
2025-08-14T21:17:22.1041405Z     >>> options = TensorPipeRpcBackendOptions(
2025-08-14T21:17:22.1041747Z     >>>     num_worker_threads=8,
2025-08-14T21:17:22.1042056Z     >>>     device_maps={"worker1": {0: 1}}
2025-08-14T21:17:22.1042407Z     >>> # maps worker0's cuda:0 to worker1's cuda:1
2025-08-14T21:17:22.1042723Z     >>> )
2025-08-14T21:17:22.1042974Z     >>> options.set_device_map("worker1", {1: 2})
2025-08-14T21:17:22.1043345Z     >>> # maps worker0's cuda:1 to worker1's cuda:2
2025-08-14T21:17:22.1043671Z     >>>
2025-08-14T21:17:22.1043868Z     >>> rpc.init_rpc(
2025-08-14T21:17:22.1044185Z     >>>     "worker0",
2025-08-14T21:17:22.1044431Z     >>>     rank=0,
2025-08-14T21:17:22.1044657Z     >>>     world_size=2,
2025-08-14T21:17:22.1044956Z     >>>     backend=rpc.BackendType.TENSORPIPE,
2025-08-14T21:17:22.1045392Z     >>>     rpc_backend_options=options
2025-08-14T21:17:22.1045806Z     >>> )
2025-08-14T21:17:22.1046016Z     >>>
2025-08-14T21:17:22.1046228Z     >>> x = torch.ones(2)
2025-08-14T21:17:22.1046560Z     >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1))
2025-08-14T21:17:22.1047012Z     >>> # The first argument will be moved to cuda:1 on worker1. When
2025-08-14T21:17:22.1047501Z     >>> # sending the return value back, it will follow the invert of
2025-08-14T21:17:22.1047981Z     >>> # the device map, and hence will be moved back to cuda:0 and
2025-08-14T21:17:22.1048363Z     >>> # cuda:1 on worker0
2025-08-14T21:17:22.1048682Z     >>> print(rets[0])  # tensor([2., 2.], device='cuda:0')
2025-08-14T21:17:22.1049086Z     >>> print(rets[1])  # tensor([2., 2.], device='cuda:1')
2025-08-14T21:17:22.1049346Z 
2025-08-14T21:17:22.1049612Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.1049978Z 
2025-08-14T21:17:22.1069506Z msg = Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19.
2025-08-14T21:17:22.1070633Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.1071136Z 
2025-08-14T21:17:22.1071339Z It has the same API as ``torch.autograd.profiler.profile`` class,
2025-08-14T21:17:22.1072004Z except that it enables profiling on all threads running RPC server request callbacks.
2025-08-14T21:17:22.1072402Z 
2025-08-14T21:17:22.1072697Z Context manager that manages autograd profiler state and holds a summary of results.
2025-08-14T21:17:22.1073325Z Under the hood it just records events of functions being executed in C++ and
2025-08-14T21:17:22.1073925Z exposes those events to Python. You can wrap any code into it and it will
2025-08-14T21:17:22.1074408Z only report runtime of PyTorch functions.
2025-08-14T21:17:22.1074904Z Note: profiler is thread local and is automatically propagated into the async tasks
2025-08-14T21:17:22.1075306Z 
2025-08-14T21:17:22.1075390Z Args:
2025-08-14T21:17:22.1075787Z     enabled (bool, optional): Setting this to False makes this context manager a no-op.
2025-08-14T21:17:22.1076289Z         Default: ``True``.
2025-08-14T21:17:22.1076463Z 
2025-08-14T21:17:22.1076748Z     use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API.
2025-08-14T21:17:22.1077362Z         Adds approximately 4us of overhead to each tensor operation.
2025-08-14T21:17:22.1077777Z         Default: ``False``
2025-08-14T21:17:22.1077944Z 
2025-08-14T21:17:22.1078172Z     record_shapes (bool, optional): If shapes recording is set, information
2025-08-14T21:17:22.1078765Z         about input dimensions will be collected. This allows one to see which
2025-08-14T21:17:22.1079329Z         dimensions have been used under the hood and further group by them
2025-08-14T21:17:22.1079881Z         using prof.key_averages(group_by_input_shape=True). Please note that
2025-08-14T21:17:22.1080431Z         shape recording might skew your profiling data. It is recommended to
2025-08-14T21:17:22.1081015Z         use separate runs with and without shape recording to validate the timing.
2025-08-14T21:17:22.1081600Z         Most likely the skew will be negligible for bottom most events (in a case
2025-08-14T21:17:22.1082156Z         of nested function calls). But for higher level functions the total
2025-08-14T21:17:22.1082695Z         self cpu time might be artificially increased because of the shape
2025-08-14T21:17:22.1083114Z         collection.
2025-08-14T21:17:22.1083254Z 
2025-08-14T21:17:22.1083531Z     profile_memory (bool, optional): Whether to report memory usage, default: ``False``
2025-08-14T21:17:22.1083916Z 
2025-08-14T21:17:22.1084014Z .. warning::
2025-08-14T21:17:22.1084423Z     Enabling memory profiling incurs additional profiler overhead
2025-08-14T21:17:22.1084737Z 
2025-08-14T21:17:22.1084837Z .. warning::
2025-08-14T21:17:22.1085244Z     Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`),
2025-08-14T21:17:22.1085860Z     one cannot use the profiler with ``use_cuda = True`` to benchmark
2025-08-14T21:17:22.1086417Z     DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading,
2025-08-14T21:17:22.1086941Z     please use ``use_cuda = False`` or ``num_workers = 0``.
2025-08-14T21:17:22.1087212Z 
2025-08-14T21:17:22.1087299Z Example:
2025-08-14T21:17:22.1087527Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:22.1087793Z     >>> # On worker 0:
2025-08-14T21:17:22.1088035Z     >>> import torch
2025-08-14T21:17:22.1088315Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:22.1088690Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:22.1089059Z     >>> x, y = torch.tensor(1), torch.tensor(2)
2025-08-14T21:17:22.1089409Z     >>> outer_profile_rref = rpc.remote(
2025-08-14T21:17:22.1089793Z     ...     dst_worker_name, rpc._server_process_global_profile
2025-08-14T21:17:22.1090153Z     ... )
2025-08-14T21:17:22.1090390Z     >>> outer_profile_rref.rpc_sync().__enter__()
2025-08-14T21:17:22.1090782Z     >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y))
2025-08-14T21:17:22.1091187Z     >>> inner_profile_rref = rpc.remote(
2025-08-14T21:17:22.1091588Z     ...     dst_worker_name, rpc._server_process_global_profile
2025-08-14T21:17:22.1091950Z     ... )
2025-08-14T21:17:22.1092199Z     >>> inner_profile_rref.rpc_sync().__enter__()
2025-08-14T21:17:22.1092577Z     >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y))
2025-08-14T21:17:22.1093036Z     >>> inner_profile_rref.rpc_sync().__exit__(None, None, None)
2025-08-14T21:17:22.1093506Z     >>> outer_profile_rref.rpc_sync().__exit__(None, None, None)
2025-08-14T21:17:22.1093962Z     >>> print(inner_profile_rref.rpc_sync().key_averages())
2025-08-14T21:17:22.1094464Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1095130Z     Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-08-14T21:17:22.1095780Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1096317Z     sub        85.06%           76.275us         100.00%          89.667us         89.667us         1
2025-08-14T21:17:22.1096801Z     empty      14.94%           13.392us         14.94%           13.392us         13.392us         1
2025-08-14T21:17:22.1097334Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1097789Z     Self CPU time total: 89.667us
2025-08-14T21:17:22.1098152Z     >>> print(outer_profile_rref.rpc_sync().key_averages())
2025-08-14T21:17:22.1098641Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1099290Z     Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-08-14T21:17:22.1099936Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1100449Z     sub        35.65%           76.275us         41.91%           89.667us         89.667us         1
2025-08-14T21:17:22.1100937Z     empty      12.67%           27.101us         12.67%           27.101us         13.551us         2
2025-08-14T21:17:22.1101426Z     add        51.68%           110.550us        58.09%           124.259us        124.259us        1
2025-08-14T21:17:22.1101951Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:22.1102394Z     Self CPU time total: 213.926us
2025-08-14T21:17:22.1102772Z     >>> rpc.shutdown()
2025-08-14T21:17:22.1102931Z 
2025-08-14T21:17:22.1103031Z     >>> # On worker 1:
2025-08-14T21:17:22.1103314Z     >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:22.1103675Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:22.1104086Z     >>> # wait for worker 0 to finish work, and then shutdown.
2025-08-14T21:17:22.1104458Z     >>> rpc.shutdown()
2025-08-14T21:17:22.1104615Z 
2025-08-14T21:17:22.1104870Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.1105249Z 
2025-08-14T21:17:22.2352147Z msg = Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35.
2025-08-14T21:17:22.2353307Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.2353694Z 
2025-08-14T21:17:22.2354034Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s
2025-08-14T21:17:22.2354739Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting
2025-08-14T21:17:22.2355431Z the local components of :class:`DTensor`, call the function, and wrap the outputs to
2025-08-14T21:17:22.2356036Z :class:`DTensor` according to the ``out_placements``.
2025-08-14T21:17:22.2356361Z 
2025-08-14T21:17:22.2356447Z Args:
2025-08-14T21:17:22.2356974Z     func (Callable): the function to be applied on each local shard of
2025-08-14T21:17:22.2357498Z         :class:`DTensor` s.
2025-08-14T21:17:22.2357957Z     out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]):
2025-08-14T21:17:22.2358628Z         the desired placements of the :class:`DTensor` s in ``func``'s flattened output.
2025-08-14T21:17:22.2359274Z         If the flattened ``output`` is a single value, the ``out_placements`` should be
2025-08-14T21:17:22.2359925Z         of type `PlacementType`. Otherwise if the flattened ``output`` has multiple
2025-08-14T21:17:22.2360607Z         values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1
2025-08-14T21:17:22.2361167Z         mapping to the flattened ``output``.
2025-08-14T21:17:22.2361663Z         Besides, for :class:`Tensor` output, we use `PlacementType` as its
2025-08-14T21:17:22.2362269Z         placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType`
2025-08-14T21:17:22.2362820Z         should be `None`.
2025-08-14T21:17:22.2363294Z         Note that the only exception is when no :class:`DTensor` argument is passed
2025-08-14T21:17:22.2363939Z         in. In this case, even if `out_placements` is not `None`, the result function
2025-08-14T21:17:22.2364535Z         should ignore the desired placements because the function is not running with
2025-08-14T21:17:22.2365095Z         :class:`DTensor` s.
2025-08-14T21:17:22.2365503Z     in_placements (Tuple[`PlacementType`, ...], optional):
2025-08-14T21:17:22.2366088Z         the required placements of the :class:`DTensor` s in the flattened inputs of ``func``.
2025-08-14T21:17:22.2366777Z         If ``in_placements`` is specified, :meth:`local_map` would examine whether the
2025-08-14T21:17:22.2367433Z         placements of each :class:`DTensor` argument is the same as the required
2025-08-14T21:17:22.2368038Z         placements or not. If the placements are not the same and
2025-08-14T21:17:22.2368634Z         ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if
2025-08-14T21:17:22.2369326Z         ``redistribute_inputs`` is ``True``, the argument will be first redistributed to
2025-08-14T21:17:22.2370001Z         the required sharding placements before passing its local tensor to ``func``.
2025-08-14T21:17:22.2370726Z         The only exception is when required placements are not ``None`` and the
2025-08-14T21:17:22.2371462Z         argument is a :class:`torch.Tensor`. In this case, the placements examination
2025-08-14T21:17:22.2372419Z         will be skipped and the argument will be directly passed to ``func``.
2025-08-14T21:17:22.2373343Z         If ``in_placements`` is ``None``, no placements examination will be performed.
2025-08-14T21:17:22.2373801Z         Default: None
2025-08-14T21:17:22.2374136Z     in_grad_placements (Tuple[`PlacementType`, ...], optional):
2025-08-14T21:17:22.2374662Z         the placements hint of the :class:`DTensor` s gradient corresponds
2025-08-14T21:17:22.2375214Z         to the flattened input DTensor. This argument is the hint that user
2025-08-14T21:17:22.2375758Z         can give to :meth:`to_local` in case the gradient layout of the
2025-08-14T21:17:22.2376265Z         local tensor input does not match its :class:`DTensor` input layout.
2025-08-14T21:17:22.2376806Z         If not specified, we will assume the gradient layout of the local
2025-08-14T21:17:22.2377347Z         tensor input remains the same as the original :class:`DTensor` input
2025-08-14T21:17:22.2377850Z         and use that for gradient computation. Default: None.
2025-08-14T21:17:22.2378285Z     device_mesh (:class:`DeviceMesh`, optional):
2025-08-14T21:17:22.2378760Z         the device mesh that the output :class:`DTensor` s are placed on. If not
2025-08-14T21:17:22.2379373Z         specified, this will be inferred from the first input :class:`DTensor`'s device
2025-08-14T21:17:22.2379853Z         mesh. Default: None.
2025-08-14T21:17:22.2380057Z 
2025-08-14T21:17:22.2380148Z Keyword Args:
2025-08-14T21:17:22.2380470Z     redistribute_inputs (bool, optional):
2025-08-14T21:17:22.2380996Z         the bool value indicating whether to reshard the input :class:`DTensor` s when
2025-08-14T21:17:22.2381269Z         their placements are different from the required input placements. If this
2025-08-14T21:17:22.2381495Z         value is ``False`` and some :class:`DTensor` input has a different placement,
2025-08-14T21:17:22.2381647Z         an exception will be raised. Default: False.
2025-08-14T21:17:22.2381653Z 
2025-08-14T21:17:22.2381739Z Returns:
2025-08-14T21:17:22.2382002Z     A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor`
2025-08-14T21:17:22.2382255Z     and returns a :class:`DTensor` constructed from the return value of ``func``.
2025-08-14T21:17:22.2382260Z 
2025-08-14T21:17:22.2382351Z Raises:
2025-08-14T21:17:22.2382595Z     AssertionError: For any non-DTensor output, we require its corresponding
2025-08-14T21:17:22.2382870Z         output placement in ``out_placements`` be None. An AssertionError will be raised
2025-08-14T21:17:22.2382981Z         if this is not the case.
2025-08-14T21:17:22.2382985Z 
2025-08-14T21:17:22.2383266Z     ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs
2025-08-14T21:17:22.2383420Z         a redistribution according to ``in_placements``.
2025-08-14T21:17:22.2383425Z 
2025-08-14T21:17:22.2383510Z Example:
2025-08-14T21:17:22.2383636Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:22.2383775Z     >>> def mm_allreduce_forward(device_mesh, W, X):
2025-08-14T21:17:22.2383899Z     >>>     partial_sum_tensor = torch.mm(W, X)
2025-08-14T21:17:22.2384159Z     >>>     reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh)
2025-08-14T21:17:22.2384265Z     >>>     return reduced_tensor
2025-08-14T21:17:22.2384362Z     >>>
2025-08-14T21:17:22.2384488Z     >>> W = torch.randn(12, 8, requires_grad=False)
2025-08-14T21:17:22.2384613Z     >>> X = torch.randn(8, 16, requires_grad=False)
2025-08-14T21:17:22.2384725Z     >>> Y = torch.mm(W, X)
2025-08-14T21:17:22.2384919Z     >>> row_wise = [Shard(0)]  # row-wise sharding placements on 1-d mesh
2025-08-14T21:17:22.2385104Z     >>> col_wise = [Shard(1)]  # col-wise sharding placements on 1-d mesh
2025-08-14T21:17:22.2385200Z     >>>
2025-08-14T21:17:22.2385477Z     >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion
2025-08-14T21:17:22.2385615Z     >>> local_mm_allreduce_forward = local_map(
2025-08-14T21:17:22.2385718Z     >>>     mm_allreduce_forward,
2025-08-14T21:17:22.2385904Z     >>>     out_placements=[Replicate()],
2025-08-14T21:17:22.2386038Z     >>>     in_placements=[col_wise, row_wise],
2025-08-14T21:17:22.2386141Z     >>>     device_mesh=device_mesh,
2025-08-14T21:17:22.2386227Z     >>> )
2025-08-14T21:17:22.2386323Z     >>>
2025-08-14T21:17:22.2386430Z     >>> W_dt = distribute_tensor(
2025-08-14T21:17:22.2386534Z     ...     W, device_mesh, (col_wise)
2025-08-14T21:17:22.2386658Z     ... )  # col-wisely sharded W tensor
2025-08-14T21:17:22.2386761Z     >>> X_dt = distribute_tensor(
2025-08-14T21:17:22.2386865Z     ...     X, device_mesh, (row_wise)
2025-08-14T21:17:22.2386989Z     ... )  # row-wisely sharded X tensor
2025-08-14T21:17:22.2387102Z     >>> Y_dt = local_mm_allreduce_forward(
2025-08-14T21:17:22.2387218Z     ...     device_mesh, W_dt, X_dt
2025-08-14T21:17:22.2387364Z     ... )  # apply local_mm_allreduce_forward to DTensors
2025-08-14T21:17:22.2387369Z 
2025-08-14T21:17:22.2387578Z .. note:: This API is currently experimental and subject to change
2025-08-14T21:17:22.2387583Z 
2025-08-14T21:17:22.2387847Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.2387852Z 
2025-08-14T21:17:22.2388599Z msg = Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25.
2025-08-14T21:17:22.2388870Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.2388913Z 
2025-08-14T21:17:22.2389224Z :meth:`register_sharding` is an experimental API that allows users to register sharding
2025-08-14T21:17:22.2389472Z strategies for an operator when the tensor inputs and outputs are DTensor.
2025-08-14T21:17:22.2389722Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``,
2025-08-14T21:17:22.2389963Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2)
2025-08-14T21:17:22.2390254Z when users would like to overwrite default sharding strategies of existing operators.
2025-08-14T21:17:22.2390259Z 
2025-08-14T21:17:22.2390340Z Args:
2025-08-14T21:17:22.2390469Z     op (Union[OpOverload, List[OpOverload]]):
2025-08-14T21:17:22.2390673Z         An op or a list of ops to register the customized sharding function.
2025-08-14T21:17:22.2390678Z 
2025-08-14T21:17:22.2390760Z Returns:
2025-08-14T21:17:22.2391040Z     A function decorator which can be used to wrap a function that defines the sharding
2025-08-14T21:17:22.2391317Z     strategy for the operator specified in ``op``. The defined sharding strategy will be
2025-08-14T21:17:22.2391727Z     registered to DTensor and will override the default sharding strategy if DTensor has
2025-08-14T21:17:22.2392047Z     already implemented the operator. The customized sharding function takes the same inputs
2025-08-14T21:17:22.2392287Z     as the original op (except that if an arg is a :class:`torch.Tensor`, it will be
2025-08-14T21:17:22.2392577Z     replaced by a tensor-like object that DTensor uses internally). The function should
2025-08-14T21:17:22.2392850Z     return a sequence of 2-tuples, each specifying acceptable output placements and its
2025-08-14T21:17:22.2392965Z     corresponding input placements.
2025-08-14T21:17:22.2392970Z 
2025-08-14T21:17:22.2393074Z Example:
2025-08-14T21:17:22.2393188Z     >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:22.2393318Z     >>> @register_sharding(aten._softmax.default)
2025-08-14T21:17:22.2393488Z     >>> def custom_softmax_sharding(x, dim, half_to_float):
2025-08-14T21:17:22.2393629Z     >>>     softmax_dim = dim if dim >= 0 else dim + x.ndim
2025-08-14T21:17:22.2393749Z     >>>     acceptable_shardings = []
2025-08-14T21:17:22.2393834Z     >>>
2025-08-14T21:17:22.2394008Z     >>>     all_replicate = ([Replicate()], [Replicate(), None, None])
2025-08-14T21:17:22.2394159Z     >>>     acceptable_shardings.append(all_replicate)
2025-08-14T21:17:22.2394240Z     >>>
2025-08-14T21:17:22.2394355Z     >>>     for sharding_dim in range(x.ndim):
2025-08-14T21:17:22.2394557Z     >>>         if sharding_dim != softmax_dim:
2025-08-14T21:17:22.2394657Z     >>>             all_sharded = (
2025-08-14T21:17:22.2394767Z     >>>                 [Shard(sharding_dim)],
2025-08-14T21:17:22.2394900Z     >>>                 [Shard(sharding_dim), None, None],
2025-08-14T21:17:22.2394984Z     >>>             )
2025-08-14T21:17:22.2395125Z     >>>             acceptable_shardings.append(all_sharded)
2025-08-14T21:17:22.2395221Z     >>>
2025-08-14T21:17:22.2395330Z     >>>     return acceptable_shardings
2025-08-14T21:17:22.2395336Z 
2025-08-14T21:17:22.2395549Z .. note:: This API is currently experimental and subject to change
2025-08-14T21:17:22.2395554Z 
2025-08-14T21:17:22.2395803Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.2395807Z 
2025-08-14T21:17:22.2640817Z msg = Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428.
2025-08-14T21:17:22.2641108Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.2641115Z 
2025-08-14T21:17:22.2641500Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to
2025-08-14T21:17:22.2641833Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``.
2025-08-14T21:17:22.2641997Z 
2025-08-14T21:17:22.2642088Z Keyword Args:
2025-08-14T21:17:22.2642382Z     input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:22.2642710Z         The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-08-14T21:17:22.2643090Z         DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-08-14T21:17:22.2643219Z         as a placeholder. default: None.
2025-08-14T21:17:22.2643447Z     desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:22.2643839Z         The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:22.2644306Z         have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-08-14T21:17:22.2644510Z     input_kwarg_layouts (Dict[str, Placement]):
2025-08-14T21:17:22.2644967Z         The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-08-14T21:17:22.2645067Z         default: None
2025-08-14T21:17:22.2645304Z     desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-08-14T21:17:22.2645881Z         The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:22.2646170Z         have the desired DTensor layouts. default: None.
2025-08-14T21:17:22.2646348Z     use_local_output (bool, optional):
2025-08-14T21:17:22.2646709Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-08-14T21:17:22.2646794Z Returns:
2025-08-14T21:17:22.2647120Z     A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs.
2025-08-14T21:17:22.2647125Z 
2025-08-14T21:17:22.2647224Z Example::
2025-08-14T21:17:22.2647400Z     >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:22.2647965Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput
2025-08-14T21:17:22.2648313Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:22.2648408Z     >>> ...
2025-08-14T21:17:22.2648713Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:22.2648837Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:22.2648931Z     >>>
2025-08-14T21:17:22.2649367Z     >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor
2025-08-14T21:17:22.2649533Z     >>> # and then redistributed to Replicated DTensor.
2025-08-14T21:17:22.2649636Z     >>> parallelize_module(
2025-08-14T21:17:22.2649788Z     >>>     block, # this can be a submodule or module
2025-08-14T21:17:22.2649891Z     >>>     tp_mesh,
2025-08-14T21:17:22.2649994Z     >>>     parallelize_plan={
2025-08-14T21:17:22.2650112Z     >>>         "attn": PrepareModuleInput(
2025-08-14T21:17:22.2650266Z     >>>             input_layouts=(Shard(0), None, None, ...),
2025-08-14T21:17:22.2650434Z     >>>             desired_input_layouts=(Replicate(), None, None, ...)
2025-08-14T21:17:22.2650520Z     >>>         ),
2025-08-14T21:17:22.2650620Z     >>>     }
2025-08-14T21:17:22.2650702Z     >>> )
2025-08-14T21:17:22.2650706Z 
2025-08-14T21:17:22.2650974Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.2650978Z 
2025-08-14T21:17:22.2651664Z msg = Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597.
2025-08-14T21:17:22.2651937Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.2651941Z 
2025-08-14T21:17:22.2652542Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to
2025-08-14T21:17:22.2652954Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``.
2025-08-14T21:17:22.2653030Z 
2025-08-14T21:17:22.2653131Z Keyword Args:
2025-08-14T21:17:22.2653308Z     output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:22.2653834Z         The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-08-14T21:17:22.2654546Z         DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-08-14T21:17:22.2654792Z         ``None`` need to be specified as a placeholder.
2025-08-14T21:17:22.2655002Z     desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:22.2655391Z         The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-08-14T21:17:22.2655506Z         have the desired DTensor layouts.
2025-08-14T21:17:22.2655634Z     use_local_output (bool, optional):
2025-08-14T21:17:22.2655997Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-08-14T21:17:22.2656099Z Returns:
2025-08-14T21:17:22.2656392Z     A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs.
2025-08-14T21:17:22.2656397Z 
2025-08-14T21:17:22.2656492Z Example::
2025-08-14T21:17:22.2656613Z     >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:22.2656928Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput
2025-08-14T21:17:22.2657124Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:22.2657221Z     >>> ...
2025-08-14T21:17:22.2657526Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:22.2657666Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:22.2657749Z     >>>
2025-08-14T21:17:22.2658151Z     >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor
2025-08-14T21:17:22.2658306Z     >>> # and then redistributed to Sharded DTensor.
2025-08-14T21:17:22.2658406Z     >>> parallelize_module(
2025-08-14T21:17:22.2658539Z     >>>     block, # this can be a submodule or module
2025-08-14T21:17:22.2658642Z     >>>     tp_mesh,
2025-08-14T21:17:22.2658775Z     >>>     parallelize_plan = PrepareModuleOutput(
2025-08-14T21:17:22.2658888Z     >>>         output_layouts=Replicate(),
2025-08-14T21:17:22.2659017Z     >>>         desired_output_layouts=Shard(0)
2025-08-14T21:17:22.2659099Z     >>>     )
2025-08-14T21:17:22.2659272Z     >>> )
2025-08-14T21:17:22.2659276Z 
2025-08-14T21:17:22.2659531Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.2659536Z 
2025-08-14T21:17:22.2660262Z msg = Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705.
2025-08-14T21:17:22.2660525Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.2660531Z 
2025-08-14T21:17:22.2660963Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module
2025-08-14T21:17:22.2661396Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution
2025-08-14T21:17:22.2661771Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of
2025-08-14T21:17:22.2661993Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`.
2025-08-14T21:17:22.2661997Z 
2025-08-14T21:17:22.2662085Z Keyword Args:
2025-08-14T21:17:22.2662281Z     input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:22.2662619Z         The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-08-14T21:17:22.2662972Z         DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-08-14T21:17:22.2663152Z         as a placeholder. default: None.
2025-08-14T21:17:22.2663383Z     desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:22.2663759Z         The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:22.2664162Z         have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-08-14T21:17:22.2664297Z     input_kwarg_layouts (Dict[str, Placement]):
2025-08-14T21:17:22.2664673Z         The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-08-14T21:17:22.2664775Z         default: None
2025-08-14T21:17:22.2664933Z     desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-08-14T21:17:22.2665309Z         The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:22.2665458Z         have the desired DTensor layouts. default: None.
2025-08-14T21:17:22.2665568Z     use_local_input (bool, optional):
2025-08-14T21:17:22.2665937Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-08-14T21:17:22.2666100Z     output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:22.2666436Z         The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-08-14T21:17:22.2666829Z         DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-08-14T21:17:22.2666971Z         ``None`` need to be specified as a placeholder.
2025-08-14T21:17:22.2667175Z     desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:22.2667561Z         The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-08-14T21:17:22.2667676Z         have the desired DTensor layouts.
2025-08-14T21:17:22.2667802Z     use_local_output (bool, optional):
2025-08-14T21:17:22.2668160Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-08-14T21:17:22.2668255Z Returns:
2025-08-14T21:17:22.2668618Z     A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs.
2025-08-14T21:17:22.2668623Z 
2025-08-14T21:17:22.2668710Z Example::
2025-08-14T21:17:22.2668876Z     >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:22.2669215Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput
2025-08-14T21:17:22.2669404Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:22.2669498Z     >>> ...
2025-08-14T21:17:22.2669798Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:22.2669935Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:22.2670019Z     >>>
2025-08-14T21:17:22.2670351Z     >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor
2025-08-14T21:17:22.2670716Z     >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated
2025-08-14T21:17:22.2670923Z     >>> # as Replicated DTensor and then redistributed to Sharded DTensor.
2025-08-14T21:17:22.2671023Z     >>> parallelize_module(
2025-08-14T21:17:22.2671169Z     >>>     block, # this can be a submodule or module
2025-08-14T21:17:22.2671256Z     >>>     tp_mesh,
2025-08-14T21:17:22.2671359Z     >>>     parallelize_plan={
2025-08-14T21:17:22.2671598Z     >>>         "attn": PrepareModuleInputOutput(
2025-08-14T21:17:22.2671737Z     >>>             input_layouts=(Shard(0), None, None, ...),
2025-08-14T21:17:22.2671920Z     >>>             desired_input_layouts=(Replicate(), None, None, ...),
2025-08-14T21:17:22.2672072Z     >>>             output_layouts=Replicate(),
2025-08-14T21:17:22.2672247Z     >>>             desired_output_layouts=Shard(0),
2025-08-14T21:17:22.2672342Z     >>>         ),
2025-08-14T21:17:22.2672427Z     >>>     }
2025-08-14T21:17:22.2672509Z     >>> )
2025-08-14T21:17:22.2672513Z 
2025-08-14T21:17:22.2672786Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.2672791Z 
2025-08-14T21:17:22.3390270Z msg = Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56.
2025-08-14T21:17:22.3390558Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.3390566Z 
2025-08-14T21:17:22.3390879Z Creates a multivariate normal distribution with covariance matrix having a low-rank form
2025-08-14T21:17:22.3391114Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`::
2025-08-14T21:17:22.3391123Z 
2025-08-14T21:17:22.3391302Z     covariance_matrix = cov_factor @ cov_factor.T + cov_diag
2025-08-14T21:17:22.3391306Z 
2025-08-14T21:17:22.3391470Z Example:
2025-08-14T21:17:22.3391629Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-08-14T21:17:22.3391766Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:22.3391882Z     >>> m = LowRankMultivariateNormal(
2025-08-14T21:17:22.3392073Z     ...     torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2)
2025-08-14T21:17:22.3392157Z     ... )
2025-08-14T21:17:22.3392469Z     >>> m.sample()  # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]`
2025-08-14T21:17:22.3392573Z     tensor([-0.2102, -0.5429])
2025-08-14T21:17:22.3392578Z 
2025-08-14T21:17:22.3392658Z Args:
2025-08-14T21:17:22.3392903Z     loc (Tensor): mean of the distribution with shape `batch_shape + event_shape`
2025-08-14T21:17:22.3393156Z     cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape
2025-08-14T21:17:22.3393276Z         `batch_shape + event_shape + (rank,)`
2025-08-14T21:17:22.3393539Z     cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape
2025-08-14T21:17:22.3393645Z         `batch_shape + event_shape`
2025-08-14T21:17:22.3393650Z 
2025-08-14T21:17:22.3393742Z Note:
2025-08-14T21:17:22.3394007Z     The computation for determinant and inverse of covariance matrix is avoided when
2025-08-14T21:17:22.3394243Z     `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity
2025-08-14T21:17:22.3394687Z     <https://en.wikipedia.org/wiki/Woodbury_matrix_identity>`_ and
2025-08-14T21:17:22.3394981Z     `matrix determinant lemma <https://en.wikipedia.org/wiki/Matrix_determinant_lemma>`_.
2025-08-14T21:17:22.3395229Z     Thanks to these formulas, we just need to compute the determinant and inverse of
2025-08-14T21:17:22.3395369Z     the small size "capacitance" matrix::
2025-08-14T21:17:22.3395374Z 
2025-08-14T21:17:22.3395557Z         capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor
2025-08-14T21:17:22.3395564Z 
2025-08-14T21:17:22.3395829Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.3395833Z 
2025-08-14T21:17:22.3415453Z msg = Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15.
2025-08-14T21:17:22.3415746Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.3415752Z 
2025-08-14T21:17:22.3415984Z The `MixtureSameFamily` distribution implements a (batch of) mixture
2025-08-14T21:17:22.3416241Z distribution where all component are from different parameterizations of
2025-08-14T21:17:22.3416451Z the same distribution type. It is parameterized by a `Categorical`
2025-08-14T21:17:22.3416646Z "selecting distribution" (over `k` component) and a component
2025-08-14T21:17:22.3416865Z distribution, i.e., a `Distribution` with a rightmost batch shape
2025-08-14T21:17:22.3417179Z (equal to `[k]`) which indexes each (batch of) component.
2025-08-14T21:17:22.3417184Z 
2025-08-14T21:17:22.3417280Z Examples::
2025-08-14T21:17:22.3417284Z 
2025-08-14T21:17:22.3417414Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:22.3417613Z     >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally
2025-08-14T21:17:22.3417738Z     >>> # weighted normal distributions
2025-08-14T21:17:22.3417851Z     >>> mix = D.Categorical(torch.ones(5,))
2025-08-14T21:17:22.3417999Z     >>> comp = D.Normal(torch.randn(5,), torch.rand(5,))
2025-08-14T21:17:22.3418129Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:22.3418133Z 
2025-08-14T21:17:22.3418330Z     >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally
2025-08-14T21:17:22.3418457Z     >>> # weighted bivariate normal distributions
2025-08-14T21:17:22.3418585Z     >>> mix = D.Categorical(torch.ones(5,))
2025-08-14T21:17:22.3418693Z     >>> comp = D.Independent(D.Normal(
2025-08-14T21:17:22.3418833Z     ...          torch.randn(5,2), torch.rand(5,2)), 1)
2025-08-14T21:17:22.3418953Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:22.3418957Z 
2025-08-14T21:17:22.3419136Z     >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each
2025-08-14T21:17:22.3419347Z     >>> # consisting of 5 random weighted bivariate normal distributions
2025-08-14T21:17:22.3419463Z     >>> mix = D.Categorical(torch.rand(3,5))
2025-08-14T21:17:22.3419572Z     >>> comp = D.Independent(D.Normal(
2025-08-14T21:17:22.3419720Z     ...         torch.randn(3,5,2), torch.rand(3,5,2)), 1)
2025-08-14T21:17:22.3419837Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:22.3419841Z 
2025-08-14T21:17:22.3419937Z Args:
2025-08-14T21:17:22.3420141Z     mixture_distribution: `torch.distributions.Categorical`-like
2025-08-14T21:17:22.3420329Z         instance. Manages the probability of selecting component.
2025-08-14T21:17:22.3420510Z         The number of categories must match the rightmost batch
2025-08-14T21:17:22.3420702Z         dimension of the `component_distribution`. Must have either
2025-08-14T21:17:22.3420842Z         scalar `batch_shape` or `batch_shape` matching
2025-08-14T21:17:22.3420988Z         `component_distribution.batch_shape[:-1]`
2025-08-14T21:17:22.3421203Z     component_distribution: `torch.distributions.Distribution`-like
2025-08-14T21:17:22.3421392Z         instance. Right-most batch dimension indexes component.
2025-08-14T21:17:22.3421396Z 
2025-08-14T21:17:22.3421724Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.3421729Z 
2025-08-14T21:17:22.3575133Z msg = Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120.
2025-08-14T21:17:22.3575429Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.3575435Z 
2025-08-14T21:17:22.3575618Z Creates a RelaxedBernoulli distribution, parametrized by
2025-08-14T21:17:22.3575836Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`
2025-08-14T21:17:22.3576055Z (but not both). This is a relaxed version of the `Bernoulli` distribution,
2025-08-14T21:17:22.3576234Z so the values are in (0, 1), and has reparametrizable samples.
2025-08-14T21:17:22.3576251Z 
2025-08-14T21:17:22.3576348Z Example::
2025-08-14T21:17:22.3576353Z 
2025-08-14T21:17:22.3576489Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:22.3576631Z     >>> m = RelaxedBernoulli(torch.tensor([2.2]),
2025-08-14T21:17:22.3576761Z     ...                      torch.tensor([0.1, 0.2, 0.3, 0.99]))
2025-08-14T21:17:22.3576849Z     >>> m.sample()
2025-08-14T21:17:22.3576974Z     tensor([ 0.2951,  0.3442,  0.8918,  0.9021])
2025-08-14T21:17:22.3576979Z 
2025-08-14T21:17:22.3577060Z Args:
2025-08-14T21:17:22.3577199Z     temperature (Tensor): relaxation temperature
2025-08-14T21:17:22.3577382Z     probs (Number, Tensor): the probability of sampling `1`
2025-08-14T21:17:22.3578008Z     logits (Number, Tensor): the log-odds of sampling `1`
2025-08-14T21:17:22.3578058Z 
2025-08-14T21:17:22.3578326Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.3578331Z 
2025-08-14T21:17:22.3596096Z msg = Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109.
2025-08-14T21:17:22.3596395Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.3596413Z 
2025-08-14T21:17:22.3596630Z Creates a RelaxedOneHotCategorical distribution parametrized by
2025-08-14T21:17:22.3596823Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`.
2025-08-14T21:17:22.3597077Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so
2025-08-14T21:17:22.3597241Z its samples are on simplex, and are reparametrizable.
2025-08-14T21:17:22.3597248Z 
2025-08-14T21:17:22.3597356Z Example::
2025-08-14T21:17:22.3597366Z 
2025-08-14T21:17:22.3597504Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:22.3597659Z     >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]),
2025-08-14T21:17:22.3597801Z     ...                              torch.tensor([0.1, 0.2, 0.3, 0.4]))
2025-08-14T21:17:22.3597892Z     >>> m.sample()
2025-08-14T21:17:22.3598007Z     tensor([ 0.1294,  0.2324,  0.3859,  0.2523])
2025-08-14T21:17:22.3598012Z 
2025-08-14T21:17:22.3598109Z Args:
2025-08-14T21:17:22.3598251Z     temperature (Tensor): relaxation temperature
2025-08-14T21:17:22.3598383Z     probs (Tensor): event probabilities
2025-08-14T21:17:22.3598570Z     logits (Tensor): unnormalized log probability for each event
2025-08-14T21:17:22.3598574Z 
2025-08-14T21:17:22.3598826Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.3598830Z 
2025-08-14T21:17:22.7825619Z msg = Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245.
2025-08-14T21:17:22.7827123Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.7827939Z Return a new dict with new, potentially nested, key value pair
2025-08-14T21:17:22.7828266Z 
2025-08-14T21:17:22.7828411Z     >>> purchase = {
2025-08-14T21:17:22.7828704Z     ...     "name": "Alice",
2025-08-14T21:17:22.7829089Z     ...     "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:22.7830145Z     ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:22.7830553Z     ... }
2025-08-14T21:17:22.7830891Z     >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00])  # doctest: +SKIP
2025-08-14T21:17:22.7831321Z     {'credit card': '5555-1234-1234-1234',
2025-08-14T21:17:22.7831706Z      'name': 'Alice',
2025-08-14T21:17:22.7832156Z      'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}}
2025-08-14T21:17:22.7832523Z     
2025-08-14T21:17:22.7832896Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.7833755Z 
2025-08-14T21:17:22.7834494Z msg = Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261.
2025-08-14T21:17:22.7835532Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.7836070Z Update value in a (potentially) nested dictionary
2025-08-14T21:17:22.7836332Z 
2025-08-14T21:17:22.7836417Z     inputs:
2025-08-14T21:17:22.7836674Z     d - dictionary on which to operate
2025-08-14T21:17:22.7837120Z     keys - list or tuple giving the location of the value to be changed in d
2025-08-14T21:17:22.7837575Z     func - function to operate on that value
2025-08-14T21:17:22.7837819Z 
2025-08-14T21:17:22.7838008Z     If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the
2025-08-14T21:17:22.7838561Z     original dictionary with v replaced by func(v), but does not mutate the
2025-08-14T21:17:22.7839211Z     original dictionary.
2025-08-14T21:17:22.7839384Z 
2025-08-14T21:17:22.7839593Z     If k0 is not a key in d, update_in creates nested dictionaries to the depth
2025-08-14T21:17:22.7840148Z     specified by the keys, with the innermost value set to func(default).
2025-08-14T21:17:22.7840496Z 
2025-08-14T21:17:22.7840597Z     >>> inc = lambda x: x + 1
2025-08-14T21:17:22.7840893Z     >>> update_in({"a": 0}, ["a"], inc)
2025-08-14T21:17:22.7841183Z     {'a': 1}
2025-08-14T21:17:22.7841322Z 
2025-08-14T21:17:22.7841421Z     >>> transaction = {
2025-08-14T21:17:22.7841683Z     ...     "name": "Alice",
2025-08-14T21:17:22.7842040Z     ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:22.7842469Z     ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:22.7842783Z     ... }
2025-08-14T21:17:22.7843111Z     >>> update_in(transaction, ["purchase", "costs"], sum)  # doctest: +SKIP
2025-08-14T21:17:22.7843560Z     {'credit card': '5555-1234-1234-1234',
2025-08-14T21:17:22.7843870Z      'name': 'Alice',
2025-08-14T21:17:22.7844197Z      'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}
2025-08-14T21:17:22.7844477Z 
2025-08-14T21:17:22.7844599Z     >>> # updating a value when k0 is not in d
2025-08-14T21:17:22.7844967Z     >>> update_in({}, [1, 2, 3], str, default="bar")
2025-08-14T21:17:22.7845305Z     {1: {2: {3: 'bar'}}}
2025-08-14T21:17:22.7845575Z     >>> update_in({1: "foo"}, [2, 3, 4], inc, 0)
2025-08-14T21:17:22.7845908Z     {1: 'foo', 2: {3: {4: 1}}}
2025-08-14T21:17:22.7846174Z     
2025-08-14T21:17:22.7846529Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.7846915Z 
2025-08-14T21:17:22.7847553Z msg = Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320.
2025-08-14T21:17:22.7848571Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.7849125Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys.
2025-08-14T21:17:22.7849399Z 
2025-08-14T21:17:22.7849579Z     If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless
2025-08-14T21:17:22.7850087Z     ``no_default`` is specified, then it raises KeyError or IndexError.
2025-08-14T21:17:22.7850415Z 
2025-08-14T21:17:22.7850622Z     ``get_in`` is a generalization of ``operator.getitem`` for nested data
2025-08-14T21:17:22.7851088Z     structures such as dictionaries and lists.
2025-08-14T21:17:22.7851393Z 
2025-08-14T21:17:22.7851490Z     >>> transaction = {
2025-08-14T21:17:22.7851756Z     ...     "name": "Alice",
2025-08-14T21:17:22.7852128Z     ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:22.7852544Z     ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:22.7852861Z     ... }
2025-08-14T21:17:22.7853126Z     >>> get_in(["purchase", "items", 0], transaction)
2025-08-14T21:17:22.7853455Z     'Apple'
2025-08-14T21:17:22.7853693Z     >>> get_in(["name"], transaction)
2025-08-14T21:17:22.7853988Z     'Alice'
2025-08-14T21:17:22.7854242Z     >>> get_in(["purchase", "total"], transaction)
2025-08-14T21:17:22.7854623Z     >>> get_in(["purchase", "items", "apple"], transaction)
2025-08-14T21:17:22.7855020Z     >>> get_in(["purchase", "items", 10], transaction)
2025-08-14T21:17:22.7855406Z     >>> get_in(["purchase", "total"], transaction, 0)
2025-08-14T21:17:22.7855729Z     0
2025-08-14T21:17:22.7855959Z     >>> get_in(["y"], {}, no_default=True)
2025-08-14T21:17:22.7856299Z     Traceback (most recent call last):
2025-08-14T21:17:22.7856592Z         ...
2025-08-14T21:17:22.7856810Z     KeyError: 'y'
2025-08-14T21:17:22.7856950Z 
2025-08-14T21:17:22.7857047Z     See Also:
2025-08-14T21:17:22.7857282Z         itertoolz.get
2025-08-14T21:17:22.7857531Z         operator.getitem
2025-08-14T21:17:22.7857791Z     
2025-08-14T21:17:22.7858164Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.7858612Z 
2025-08-14T21:17:22.7859282Z msg = Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373.
2025-08-14T21:17:22.7860303Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:22.7860806Z Group a collection by a key function
2025-08-14T21:17:22.7861019Z 
2025-08-14T21:17:22.7861199Z     >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"]
2025-08-14T21:17:22.7861618Z     >>> groupby(len, names)  # doctest: +SKIP
2025-08-14T21:17:22.7862010Z     {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}
2025-08-14T21:17:22.7862299Z 
2025-08-14T21:17:22.7862407Z     >>> iseven = lambda x: x % 2 == 0
2025-08-14T21:17:22.7862794Z     >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8])  # doctest: +SKIP
2025-08-14T21:17:22.7863182Z     {False: [1, 3, 5, 7], True: [2, 4, 6, 8]}
2025-08-14T21:17:22.7863418Z 
2025-08-14T21:17:22.7863564Z     Non-callable keys imply grouping on a member.
2025-08-14T21:17:22.7863827Z 
2025-08-14T21:17:22.7863918Z     >>> groupby(
2025-08-14T21:17:22.7864151Z     ...     "gender",
2025-08-14T21:17:22.7864384Z     ...     [
2025-08-14T21:17:22.7864639Z     ...         {"name": "Alice", "gender": "F"},
2025-08-14T21:17:22.7864988Z     ...         {"name": "Bob", "gender": "M"},
2025-08-14T21:17:22.7865328Z     ...         {"name": "Charlie", "gender": "M"},
2025-08-14T21:17:22.7865649Z     ...     ],
2025-08-14T21:17:22.7865891Z     ... )  # doctest:+SKIP
2025-08-14T21:17:22.7866167Z     {'F': [{'gender': 'F', 'name': 'Alice'}],
2025-08-14T21:17:22.7866509Z      'M': [{'gender': 'M', 'name': 'Bob'},
2025-08-14T21:17:22.7866843Z            {'gender': 'M', 'name': 'Charlie'}]}
2025-08-14T21:17:22.7867066Z 
2025-08-14T21:17:22.7867206Z     Not to be confused with ``itertools.groupby``
2025-08-14T21:17:22.7867464Z 
2025-08-14T21:17:22.7867551Z     See Also:
2025-08-14T21:17:22.7867772Z         countby
2025-08-14T21:17:22.7867998Z     
2025-08-14T21:17:22.7868356Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:22.7868736Z 
2025-08-14T21:17:23.1167880Z msg = Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142.
2025-08-14T21:17:23.1168868Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.1169512Z Return the recommended gain value for the given nonlinearity function.
2025-08-14T21:17:23.1170092Z 
2025-08-14T21:17:23.1170206Z     The values are as follows:
2025-08-14T21:17:23.1170394Z 
2025-08-14T21:17:23.1170527Z     ================= ====================================================
2025-08-14T21:17:23.1170865Z     nonlinearity      gain
2025-08-14T21:17:23.1171165Z     ================= ====================================================
2025-08-14T21:17:23.1171521Z     Linear / Identity :math:`1`
2025-08-14T21:17:23.1171820Z     Conv{1,2,3}D      :math:`1`
2025-08-14T21:17:23.1172104Z     Sigmoid           :math:`1`
2025-08-14T21:17:23.1172395Z     Tanh              :math:`\frac{5}{3}`
2025-08-14T21:17:23.1172721Z     ReLU              :math:`\sqrt{2}`
2025-08-14T21:17:23.1173110Z     Leaky Relu        :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}`
2025-08-14T21:17:23.1173531Z     SELU              :math:`\frac{3}{4}`
2025-08-14T21:17:23.1173862Z     ================= ====================================================
2025-08-14T21:17:23.1174095Z 
2025-08-14T21:17:23.1174207Z     .. warning::
2025-08-14T21:17:23.1174543Z         In order to implement `Self-Normalizing Neural Networks`_ ,
2025-08-14T21:17:23.1175094Z         you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``.
2025-08-14T21:17:23.1175636Z         This gives the initial weights a variance of ``1 / N``,
2025-08-14T21:17:23.1176136Z         which is necessary to induce a stable fixed point in the forward pass.
2025-08-14T21:17:23.1176763Z         In contrast, the default gain for ``SELU`` sacrifices the normalization
2025-08-14T21:17:23.1177355Z         effect for more stable gradient flow in rectangular layers.
2025-08-14T21:17:23.1177655Z 
2025-08-14T21:17:23.1177739Z     Args:
2025-08-14T21:17:23.1178066Z         nonlinearity: the non-linear function (`nn.functional` name)
2025-08-14T21:17:23.1178558Z         param: optional parameter for the non-linear function
2025-08-14T21:17:23.1178840Z 
2025-08-14T21:17:23.1178941Z     Examples:
2025-08-14T21:17:23.1179186Z         >>> gain = nn.init.calculate_gain(
2025-08-14T21:17:23.1179519Z         ...     "leaky_relu", 0.2
2025-08-14T21:17:23.1179841Z         ... )  # leaky_relu with negative_slope=0.2
2025-08-14T21:17:23.1180080Z 
2025-08-14T21:17:23.1180568Z     .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html
2025-08-14T21:17:23.1181243Z     
2025-08-14T21:17:23.1181617Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.1181992Z 
2025-08-14T21:17:23.3879916Z msg = Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=603.
2025-08-14T21:17:23.3880945Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.3881509Z Applies Batch Normalization over a N-Dimensional input.
2025-08-14T21:17:23.3881796Z 
2025-08-14T21:17:23.3882167Z     The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper
2025-08-14T21:17:23.3882861Z     `Batch Normalization: Accelerating Deep Network Training by Reducing
2025-08-14T21:17:23.3883540Z     Internal Covariate Shift <https://arxiv.org/abs/1502.03167>`__ .
2025-08-14T21:17:23.3883878Z 
2025-08-14T21:17:23.3884037Z     .. math::
2025-08-14T21:17:23.3884246Z 
2025-08-14T21:17:23.3884756Z         y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta
2025-08-14T21:17:23.3885299Z 
2025-08-14T21:17:23.3885531Z     The mean and standard-deviation are calculated per-dimension over all
2025-08-14T21:17:23.3886112Z     mini-batches of the same process groups. :math:`\gamma` and :math:`\beta`
2025-08-14T21:17:23.3886699Z     are learnable parameter vectors of size `C` (where `C` is the input size).
2025-08-14T21:17:23.3887239Z     By default, the elements of :math:`\gamma` are sampled from
2025-08-14T21:17:23.3887734Z     :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0.
2025-08-14T21:17:23.3888554Z     The standard-deviation is calculated via the biased estimator, equivalent to
2025-08-14T21:17:23.3889047Z     `torch.var(input, unbiased=False)`.
2025-08-14T21:17:23.3889284Z 
2025-08-14T21:17:23.3889523Z     Also by default, during training this layer keeps running estimates of its
2025-08-14T21:17:23.3890118Z     computed mean and variance, which are then used for normalization during
2025-08-14T21:17:23.3890712Z     evaluation. The running estimates are kept with a default :attr:`momentum`
2025-08-14T21:17:23.3891174Z     of 0.1.
2025-08-14T21:17:23.3891297Z 
2025-08-14T21:17:23.3891535Z     If :attr:`track_running_stats` is set to ``False``, this layer then does not
2025-08-14T21:17:23.3892102Z     keep running estimates, and batch statistics are instead used during
2025-08-14T21:17:23.3892536Z     evaluation time as well.
2025-08-14T21:17:23.3892732Z 
2025-08-14T21:17:23.3892823Z     .. note::
2025-08-14T21:17:23.3893184Z         This :attr:`momentum` argument is different from one used in optimizer
2025-08-14T21:17:23.3893742Z         classes and the conventional notion of momentum. Mathematically, the
2025-08-14T21:17:23.3894221Z         update rule for running statistics here is
2025-08-14T21:17:23.3894739Z         :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`,
2025-08-14T21:17:23.3895329Z         where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the
2025-08-14T21:17:23.3895810Z         new observed value.
2025-08-14T21:17:23.3896053Z 
2025-08-14T21:17:23.3896355Z     Because the Batch Normalization is done for each channel in the ``C`` dimension, computing
2025-08-14T21:17:23.3897028Z     statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch
2025-08-14T21:17:23.3897568Z     Normalization or Spatio-temporal Batch Normalization.
2025-08-14T21:17:23.3897867Z 
2025-08-14T21:17:23.3898010Z     Currently :class:`SyncBatchNorm` only supports
2025-08-14T21:17:23.3898563Z     :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use
2025-08-14T21:17:23.3899187Z     :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert
2025-08-14T21:17:23.3899712Z     :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping
2025-08-14T21:17:23.3900131Z     Network with DDP.
2025-08-14T21:17:23.3900286Z 
2025-08-14T21:17:23.3900381Z     Args:
2025-08-14T21:17:23.3900657Z         num_features: :math:`C` from an expected input of size
2025-08-14T21:17:23.3901039Z             :math:`(N, C, +)`
2025-08-14T21:17:23.3901411Z         eps: a value added to the denominator for numerical stability.
2025-08-14T21:17:23.3913087Z             Default: ``1e-5``
2025-08-14T21:17:23.3913501Z         momentum: the value used for the running_mean and running_var
2025-08-14T21:17:23.3914044Z             computation. Can be set to ``None`` for cumulative moving average
2025-08-14T21:17:23.3914492Z             (i.e. simple average). Default: 0.1
2025-08-14T21:17:23.3914948Z         affine: a boolean value that when set to ``True``, this module has
2025-08-14T21:17:23.3915430Z             learnable affine parameters. Default: ``True``
2025-08-14T21:17:23.3915916Z         track_running_stats: a boolean value that when set to ``True``, this
2025-08-14T21:17:23.3916470Z             module tracks the running mean and variance, and when set to ``False``,
2025-08-14T21:17:23.3917054Z             this module does not track such statistics, and initializes statistics
2025-08-14T21:17:23.3917610Z             buffers :attr:`running_mean` and :attr:`running_var` as ``None``.
2025-08-14T21:17:23.3918151Z             When these buffers are ``None``, this module always uses batch statistics.
2025-08-14T21:17:23.3918662Z             in both training and eval modes. Default: ``True``
2025-08-14T21:17:23.3919184Z         process_group: synchronization of stats happen within each process group
2025-08-14T21:17:23.3919784Z             individually. Default behavior is synchronization across the whole
2025-08-14T21:17:23.3920390Z             world
2025-08-14T21:17:23.3920550Z 
2025-08-14T21:17:23.3920636Z     Shape:
2025-08-14T21:17:23.3920883Z         - Input: :math:`(N, C, +)`
2025-08-14T21:17:23.3921227Z         - Output: :math:`(N, C, +)` (same shape as input)
2025-08-14T21:17:23.3921496Z 
2025-08-14T21:17:23.3921590Z     .. note::
2025-08-14T21:17:23.3921976Z         Synchronization of batchnorm statistics occurs only while training, i.e.
2025-08-14T21:17:23.3922554Z         synchronization is disabled when ``model.eval()`` is set or if
2025-08-14T21:17:23.3923000Z         ``self.training`` is otherwise ``False``.
2025-08-14T21:17:23.3923251Z 
2025-08-14T21:17:23.3923345Z     Examples::
2025-08-14T21:17:23.3923482Z 
2025-08-14T21:17:23.3923595Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.3923879Z         >>> # With Learnable Parameters
2025-08-14T21:17:23.3924212Z         >>> m = nn.SyncBatchNorm(100)
2025-08-14T21:17:23.3924550Z         >>> # creating process group (optional)
2025-08-14T21:17:23.3924921Z         >>> # ranks is a list of int identifying rank ids.
2025-08-14T21:17:23.3925279Z         >>> ranks = list(range(8))
2025-08-14T21:17:23.3925583Z         >>> r1, r2 = ranks[:4], ranks[4:]
2025-08-14T21:17:23.3925945Z         >>> # Note: every rank calls into new_group for every
2025-08-14T21:17:23.3926349Z         >>> # process group created, even if that rank is not
2025-08-14T21:17:23.3926720Z         >>> # part of the group.
2025-08-14T21:17:23.3927217Z         >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-08-14T21:17:23.3927829Z         >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-08-14T21:17:23.3928274Z         >>> # Without Learnable Parameters
2025-08-14T21:17:23.3928708Z         >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group)
2025-08-14T21:17:23.3929162Z         >>> input = torch.randn(20, 100, 35, 45, 10)
2025-08-14T21:17:23.3929491Z         >>> output = m(input)
2025-08-14T21:17:23.3929683Z 
2025-08-14T21:17:23.3929802Z         >>> # network is nn.BatchNorm layer
2025-08-14T21:17:23.3930308Z         >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group)
2025-08-14T21:17:23.3930862Z         >>> # only single gpu per process is currently supported
2025-08-14T21:17:23.3931363Z         >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel(
2025-08-14T21:17:23.3931816Z         >>>                         sync_bn_network,
2025-08-14T21:17:23.3932181Z         >>>                         device_ids=[args.local_rank],
2025-08-14T21:17:23.3932547Z         >>>                         output_device=args.local_rank)
2025-08-14T21:17:23.3932881Z     
2025-08-14T21:17:23.3933255Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.3933621Z 
2025-08-14T21:17:23.3934276Z msg = Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=830.
2025-08-14T21:17:23.3935308Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.3935999Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers.
2025-08-14T21:17:23.3936419Z 
2025-08-14T21:17:23.3936516Z         Args:
2025-08-14T21:17:23.3936883Z             module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers
2025-08-14T21:17:23.3937472Z             process_group (optional): process group to scope synchronization,
2025-08-14T21:17:23.3937919Z                 default is the whole world
2025-08-14T21:17:23.3938138Z 
2025-08-14T21:17:23.3938222Z         Returns:
2025-08-14T21:17:23.3938615Z             The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm`
2025-08-14T21:17:23.3939206Z             layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer,
2025-08-14T21:17:23.3939757Z             a new :class:`torch.nn.SyncBatchNorm` layer object will be returned
2025-08-14T21:17:23.3940223Z             instead.
2025-08-14T21:17:23.3940388Z 
2025-08-14T21:17:23.3940479Z         Example::
2025-08-14T21:17:23.3940621Z 
2025-08-14T21:17:23.3940752Z             >>> # Network with nn.BatchNorm layer
2025-08-14T21:17:23.3941117Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:23.3941494Z             >>> module = torch.nn.Sequential(
2025-08-14T21:17:23.3941851Z             >>>            torch.nn.Linear(20, 100),
2025-08-14T21:17:23.3942215Z             >>>            torch.nn.BatchNorm1d(100),
2025-08-14T21:17:23.3942540Z             >>>          ).cuda()
2025-08-14T21:17:23.3942853Z             >>> # creating process group (optional)
2025-08-14T21:17:23.3943230Z             >>> # ranks is a list of int identifying rank ids.
2025-08-14T21:17:23.3943585Z             >>> ranks = list(range(8))
2025-08-14T21:17:23.3943911Z             >>> r1, r2 = ranks[:4], ranks[4:]
2025-08-14T21:17:23.3944286Z             >>> # Note: every rank calls into new_group for every
2025-08-14T21:17:23.3944689Z             >>> # process group created, even if that rank is not
2025-08-14T21:17:23.3945061Z             >>> # part of the group.
2025-08-14T21:17:23.3945390Z             >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:23.3945869Z             >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-08-14T21:17:23.3946433Z             >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-08-14T21:17:23.3947114Z             >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group)
2025-08-14T21:17:23.3947524Z 
2025-08-14T21:17:23.3947619Z         
2025-08-14T21:17:23.3947983Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.3948362Z 
2025-08-14T21:17:23.4190015Z msg = Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=66.
2025-08-14T21:17:23.4190934Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.4191324Z 
2025-08-14T21:17:23.4191705Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`.
2025-08-14T21:17:23.4192131Z 
2025-08-14T21:17:23.4192415Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can
2025-08-14T21:17:23.4193026Z   be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively.
2025-08-14T21:17:23.4193389Z 
2025-08-14T21:17:23.4193706Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be
2025-08-14T21:17:23.4194393Z   a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input;  a `NamedShape`
2025-08-14T21:17:23.4194939Z   (tuple of `(name, size)` tuples) for `NamedTensor` input.
2025-08-14T21:17:23.4195219Z 
2025-08-14T21:17:23.4195305Z Shape:
2025-08-14T21:17:23.4195642Z     - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at
2025-08-14T21:17:23.4196234Z       dimension :attr:`dim` and :math:`*` means any number of dimensions including none.
2025-08-14T21:17:23.4196820Z     - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and
2025-08-14T21:17:23.4197273Z       :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`.
2025-08-14T21:17:23.4197525Z 
2025-08-14T21:17:23.4197606Z Args:
2025-08-14T21:17:23.4197879Z     dim (Union[int, str]): Dimension to be unflattened
2025-08-14T21:17:23.4198479Z     unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension
2025-08-14T21:17:23.4198959Z 
2025-08-14T21:17:23.4199047Z Examples:
2025-08-14T21:17:23.4199286Z     >>> input = torch.randn(2, 50)
2025-08-14T21:17:23.4199597Z     >>> # With tuple of ints
2025-08-14T21:17:23.4199871Z     >>> m = nn.Sequential(
2025-08-14T21:17:23.4200146Z     >>>     nn.Linear(50, 50),
2025-08-14T21:17:23.4200435Z     >>>     nn.Unflatten(1, (2, 5, 5))
2025-08-14T21:17:23.4200719Z     >>> )
2025-08-14T21:17:23.4201130Z     >>> output = m(input)
2025-08-14T21:17:23.4201404Z     >>> output.size()
2025-08-14T21:17:23.4201652Z     torch.Size([2, 2, 5, 5])
2025-08-14T21:17:23.4201934Z     >>> # With torch.Size
2025-08-14T21:17:23.4202205Z     >>> m = nn.Sequential(
2025-08-14T21:17:23.4202464Z     >>>     nn.Linear(50, 50),
2025-08-14T21:17:23.4202773Z     >>>     nn.Unflatten(1, torch.Size([2, 5, 5]))
2025-08-14T21:17:23.4203099Z     >>> )
2025-08-14T21:17:23.4203308Z     >>> output = m(input)
2025-08-14T21:17:23.4203580Z     >>> output.size()
2025-08-14T21:17:23.4203836Z     torch.Size([2, 2, 5, 5])
2025-08-14T21:17:23.4204127Z     >>> # With namedshape (tuple of tuples)
2025-08-14T21:17:23.4204508Z     >>> input = torch.randn(2, 50, names=("N", "features"))
2025-08-14T21:17:23.4204980Z     >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5)))
2025-08-14T21:17:23.4205413Z     >>> output = unflatten(input)
2025-08-14T21:17:23.4205697Z     >>> output.size()
2025-08-14T21:17:23.4205963Z     torch.Size([2, 2, 5, 5])
2025-08-14T21:17:23.4206137Z 
2025-08-14T21:17:23.4206398Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.4206765Z 
2025-08-14T21:17:23.4578536Z msg = Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1798.
2025-08-14T21:17:23.4579537Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.4580278Z Creates a criterion that measures the triplet loss given input
2025-08-14T21:17:23.4580792Z     tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor,
2025-08-14T21:17:23.4581306Z     positive, and negative examples, respectively), and a nonnegative,
2025-08-14T21:17:23.4581891Z     real-valued function ("distance function") used to compute the relationship
2025-08-14T21:17:23.4582487Z     between the anchor and positive example ("positive distance") and the
2025-08-14T21:17:23.4582992Z     anchor and negative example ("negative distance").
2025-08-14T21:17:23.4583254Z 
2025-08-14T21:17:23.4583463Z     The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``)
2025-08-14T21:17:23.4583891Z     can be described as:
2025-08-14T21:17:23.4584061Z 
2025-08-14T21:17:23.4584174Z     .. math::
2025-08-14T21:17:23.4584437Z         \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad
2025-08-14T21:17:23.4584852Z         l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\}
2025-08-14T21:17:23.4585131Z 
2025-08-14T21:17:23.4585377Z     where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function
2025-08-14T21:17:23.4586045Z     quantifying the closeness of two tensors, referred to as the :attr:`distance_function`;
2025-08-14T21:17:23.4586691Z     and :math:`margin` is a nonnegative margin representing the minimum difference
2025-08-14T21:17:23.4587300Z     between the positive and negative distances that is required for the loss to
2025-08-14T21:17:23.4587901Z     be 0.  The input tensors have :math:`N` elements each and can be of any shape
2025-08-14T21:17:23.4588374Z     that the distance function can handle.
2025-08-14T21:17:23.4588597Z 
2025-08-14T21:17:23.4588711Z     If :attr:`reduction` is not ``'none'``
2025-08-14T21:17:23.4589039Z     (default ``'mean'``), then:
2025-08-14T21:17:23.4589226Z 
2025-08-14T21:17:23.4589324Z     .. math::
2025-08-14T21:17:23.4589538Z         \ell(x, y) =
2025-08-14T21:17:23.4589809Z         \begin{cases}
2025-08-14T21:17:23.4590179Z             \operatorname{mean}(L), &  \text{if reduction} = \text{`mean';}\\
2025-08-14T21:17:23.4590691Z             \operatorname{sum}(L),  &  \text{if reduction} = \text{`sum'.}
2025-08-14T21:17:23.4591296Z         \end{cases}
2025-08-14T21:17:23.4591601Z 
2025-08-14T21:17:23.4591918Z     See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet
2025-08-14T21:17:23.4592531Z     loss for input tensors using the :math:`l_p` distance as the distance function.
2025-08-14T21:17:23.4593103Z 
2025-08-14T21:17:23.4593417Z     Args:
2025-08-14T21:17:23.4594078Z         distance_function (Callable, optional): A nonnegative, real-valued function that
2025-08-14T21:17:23.4594930Z             quantifies the closeness of two tensors. If not specified,
2025-08-14T21:17:23.4595411Z             `nn.PairwiseDistance` will be used.  Default: ``None``
2025-08-14T21:17:23.4595973Z         margin (float, optional): A nonnegative margin representing the minimum difference
2025-08-14T21:17:23.4596635Z             between the positive and negative distances required for the loss to be 0. Larger
2025-08-14T21:17:23.4597311Z             margins penalize cases where the negative examples are not distant enough from the
2025-08-14T21:17:23.4597891Z             anchors, relative to the positives. Default: :math:`1`.
2025-08-14T21:17:23.4598421Z         swap (bool, optional): Whether to use the distance swap described in the paper
2025-08-14T21:17:23.4599066Z             `Learning shallow convolutional feature descriptors with triplet losses` by
2025-08-14T21:17:23.4599684Z             V. Balntas, E. Riba et al. If True, and if the positive example is closer to the
2025-08-14T21:17:23.4600306Z             negative example than the anchor is, swaps the positive example and the anchor in
2025-08-14T21:17:23.4600819Z             the loss computation. Default: ``False``.
2025-08-14T21:17:23.4601350Z         reduction (str, optional): Specifies the (optional) reduction to apply to the output:
2025-08-14T21:17:23.4602379Z             ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-08-14T21:17:23.4602869Z             ``'mean'``: the sum of the output will be divided by the number of
2025-08-14T21:17:23.4603398Z             elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'``
2025-08-14T21:17:23.4603769Z 
2025-08-14T21:17:23.4603773Z 
2025-08-14T21:17:23.4603861Z     Shape:
2025-08-14T21:17:23.4604237Z         - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions
2025-08-14T21:17:23.4604716Z           as supported by the distance function.
2025-08-14T21:17:23.4605212Z         - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar
2025-08-14T21:17:23.4605677Z           otherwise.
2025-08-14T21:17:23.4605828Z 
2025-08-14T21:17:23.4605929Z     Examples:
2025-08-14T21:17:23.4606061Z 
2025-08-14T21:17:23.4606165Z     >>> # Initialize embeddings
2025-08-14T21:17:23.4606474Z     >>> embedding = nn.Embedding(1000, 128)
2025-08-14T21:17:23.4606846Z     >>> anchor_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:23.4607217Z     >>> positive_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:23.4607578Z     >>> negative_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:23.4607935Z     >>> anchor = embedding(anchor_ids)
2025-08-14T21:17:23.4608270Z     >>> positive = embedding(positive_ids)
2025-08-14T21:17:23.4608602Z     >>> negative = embedding(negative_ids)
2025-08-14T21:17:23.4608915Z     >>>
2025-08-14T21:17:23.4609433Z     >>> # Built-in Distance Function
2025-08-14T21:17:23.4609748Z     >>> triplet_loss = \
2025-08-14T21:17:23.4610190Z     >>>     nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance())
2025-08-14T21:17:23.4610754Z     >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:23.4611133Z     >>> output.backward()
2025-08-14T21:17:23.4611385Z     >>>
2025-08-14T21:17:23.4611613Z     >>> # Custom Distance Function
2025-08-14T21:17:23.4611922Z     >>> def l_infinity(x1, x2):
2025-08-14T21:17:23.4612255Z     >>>     return torch.max(torch.abs(x1 - x2), dim=1).values
2025-08-14T21:17:23.4612613Z     >>>
2025-08-14T21:17:23.4612928Z     >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time")
2025-08-14T21:17:23.4613320Z     >>> triplet_loss = (
2025-08-14T21:17:23.4613772Z     >>>     nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5))
2025-08-14T21:17:23.4614328Z     >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:23.4614804Z     >>> output.backward()
2025-08-14T21:17:23.4615054Z     >>>
2025-08-14T21:17:23.4615292Z     >>> # Custom Distance Function (Lambda)
2025-08-14T21:17:23.4615622Z     >>> triplet_loss = (
2025-08-14T21:17:23.4615912Z     >>>     nn.TripletMarginWithDistanceLoss(
2025-08-14T21:17:23.4616376Z     >>>         distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y)))
2025-08-14T21:17:23.4616866Z     >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:23.4617232Z     >>> output.backward()
2025-08-14T21:17:23.4617416Z 
2025-08-14T21:17:23.4617502Z     Reference:
2025-08-14T21:17:23.4617945Z         V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses:
2025-08-14T21:17:23.4618600Z         https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html
2025-08-14T21:17:23.4619010Z     
2025-08-14T21:17:23.4619383Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17))
2025-08-14T21:17:23.4619753Z 
2025-08-14T21:17:23.4620302Z msg = Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1933.
2025-08-14T21:17:23.4621170Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.4621699Z The Connectionist Temporal Classification loss.
2025-08-14T21:17:23.4621954Z 
2025-08-14T21:17:23.4622330Z     Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the
2025-08-14T21:17:23.4623269Z     probability of possible alignments of input to target, producing a loss value which is differentiable
2025-08-14T21:17:23.4624075Z     with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which
2025-08-14T21:17:23.4624833Z     limits the length of the target sequence such that it must be :math:`\leq` the input length.
2025-08-14T21:17:23.4625246Z 
2025-08-14T21:17:23.4625330Z     Args:
2025-08-14T21:17:23.4625625Z         blank (int, optional): blank label. Default :math:`0`.
2025-08-14T21:17:23.4626152Z         reduction (str, optional): Specifies the reduction to apply to the output:
2025-08-14T21:17:23.4626703Z             ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-08-14T21:17:23.4627203Z             ``'mean'``: the output losses will be divided by the target lengths and
2025-08-14T21:17:23.4627781Z             then the mean over the batch is taken, ``'sum'``: the output losses will be summed.
2025-08-14T21:17:23.4628254Z             Default: ``'mean'``
2025-08-14T21:17:23.4628545Z         zero_infinity (bool, optional):
2025-08-14T21:17:23.4628966Z             Whether to zero infinite losses and the associated gradients.
2025-08-14T21:17:23.4629378Z             Default: ``False``
2025-08-14T21:17:23.4629748Z             Infinite losses mainly occur when the inputs are too short
2025-08-14T21:17:23.4630151Z             to be aligned to the targets.
2025-08-14T21:17:23.4630379Z 
2025-08-14T21:17:23.4630467Z     Shape:
2025-08-14T21:17:23.4630784Z         - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`,
2025-08-14T21:17:23.4631202Z           where :math:`T = \text{input length}`,
2025-08-14T21:17:23.4631640Z           :math:`N = \text{batch size}`, and
2025-08-14T21:17:23.4632025Z           :math:`C = \text{number of classes (including blank)}`.
2025-08-14T21:17:23.4632515Z           The logarithmized probabilities of the outputs (e.g. obtained with
2025-08-14T21:17:23.4633006Z           :func:`torch.nn.functional.log_softmax`).
2025-08-14T21:17:23.4633386Z         - Targets: Tensor of size :math:`(N, S)` or
2025-08-14T21:17:23.4633790Z           :math:`(\operatorname{sum}(\text{target\_lengths}))`,
2025-08-14T21:17:23.4634177Z           where :math:`N = \text{batch size}` and
2025-08-14T21:17:23.4634577Z           :math:`S = \text{max target length, if shape is } (N, S)`.
2025-08-14T21:17:23.4635056Z           It represents the target sequences. Each element in the target
2025-08-14T21:17:23.4635662Z           sequence is a class index. And the target index cannot be blank (default=0).
2025-08-14T21:17:23.4636181Z           In the :math:`(N, S)` form, targets are padded to the
2025-08-14T21:17:23.4636595Z           length of the longest sequence, and stacked.
2025-08-14T21:17:23.4637042Z           In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form,
2025-08-14T21:17:23.4637487Z           the targets are assumed to be un-padded and
2025-08-14T21:17:23.4637863Z           concatenated within 1 dimension.
2025-08-14T21:17:23.4638300Z         - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-08-14T21:17:23.4638816Z           where :math:`N = \text{batch size}`. It represents the lengths of the
2025-08-14T21:17:23.4639348Z           inputs (must each be :math:`\leq T`). And the lengths are specified
2025-08-14T21:17:23.4639899Z           for each sequence to achieve masking under the assumption that sequences
2025-08-14T21:17:23.4640372Z           are padded to equal lengths.
2025-08-14T21:17:23.4640788Z         - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-08-14T21:17:23.4641333Z           where :math:`N = \text{batch size}`. It represents lengths of the targets.
2025-08-14T21:17:23.4641896Z           Lengths are specified for each sequence to achieve masking under the
2025-08-14T21:17:23.4642475Z           assumption that sequences are padded to equal lengths. If target shape is
2025-08-14T21:17:23.4643076Z           :math:`(N,S)`, target_lengths are effectively the stop index
2025-08-14T21:17:23.4643621Z           :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for
2025-08-14T21:17:23.4644171Z           each target in a batch. Lengths must each be :math:`\leq S`
2025-08-14T21:17:23.4644700Z           If the targets are given as a 1d tensor that is the concatenation of individual
2025-08-14T21:17:23.4645303Z           targets, the target_lengths must add up to the total length of the tensor.
2025-08-14T21:17:23.4645860Z         - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or
2025-08-14T21:17:23.4646388Z           ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or
2025-08-14T21:17:23.4646942Z           :math:`()` if input is unbatched, where :math:`N = \text{batch size}`.
2025-08-14T21:17:23.4647263Z 
2025-08-14T21:17:23.4647352Z     Examples:
2025-08-14T21:17:23.4647484Z 
2025-08-14T21:17:23.4647603Z         >>> # Target are to be padded
2025-08-14T21:17:23.4647919Z         >>> T = 50  # Input sequence length
2025-08-14T21:17:23.4648278Z         >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:23.4648625Z         >>> N = 16  # Batch size
2025-08-14T21:17:23.4649029Z         >>> S = 30  # Target sequence length of longest target in batch (padding length)
2025-08-14T21:17:23.4649560Z         >>> S_min = 10  # Minimum target length, for demonstration purposes
2025-08-14T21:17:23.4649949Z         >>>
2025-08-14T21:17:23.4650281Z         >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-08-14T21:17:23.4650794Z         >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-08-14T21:17:23.4651209Z         >>>
2025-08-14T21:17:23.4651527Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:23.4652046Z         >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long)
2025-08-14T21:17:23.4652468Z         >>>
2025-08-14T21:17:23.4652812Z         >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-08-14T21:17:23.4653267Z         >>> target_lengths = torch.randint(
2025-08-14T21:17:23.4653579Z         ...     low=S_min,
2025-08-14T21:17:23.4653840Z         ...     high=S,
2025-08-14T21:17:23.4654091Z         ...     size=(N,),
2025-08-14T21:17:23.4654351Z         ...     dtype=torch.long,
2025-08-14T21:17:23.4654634Z         ... )
2025-08-14T21:17:23.4654870Z         >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:23.4655314Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:23.4655722Z         >>> loss.backward()
2025-08-14T21:17:23.4655992Z         >>>
2025-08-14T21:17:23.4656188Z         >>>
2025-08-14T21:17:23.4656427Z         >>> # Target are to be un-padded
2025-08-14T21:17:23.4656760Z         >>> T = 50  # Input sequence length
2025-08-14T21:17:23.4657102Z         >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:23.4657450Z         >>> N = 16  # Batch size
2025-08-14T21:17:23.4657722Z         >>>
2025-08-14T21:17:23.4658043Z         >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-08-14T21:17:23.4658557Z         >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-08-14T21:17:23.4659104Z         >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-08-14T21:17:23.4659527Z         >>>
2025-08-14T21:17:23.4659832Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:23.4660389Z         >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long)
2025-08-14T21:17:23.4660856Z         >>> target = torch.randint(
2025-08-14T21:17:23.4661136Z         ...     low=1,
2025-08-14T21:17:23.4661379Z         ...     high=C,
2025-08-14T21:17:23.4661650Z         ...     size=(sum(target_lengths),),
2025-08-14T21:17:23.4661974Z         ...     dtype=torch.long,
2025-08-14T21:17:23.4662270Z         ... )
2025-08-14T21:17:23.4662528Z         >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:23.4662910Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:23.4663299Z         >>> loss.backward()
2025-08-14T21:17:23.4663558Z         >>>
2025-08-14T21:17:23.4663765Z         >>>
2025-08-14T21:17:23.4664067Z         >>> # Target are to be un-padded and unbatched (effectively N=1)
2025-08-14T21:17:23.4664480Z         >>> T = 50  # Input sequence length
2025-08-14T21:17:23.4664836Z         >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:23.4665162Z         >>>
2025-08-14T21:17:23.4665484Z         >>> # Initialize random batch of input vectors, for *size = (T,C)
2025-08-14T21:17:23.4665932Z         >>> # xdoctest: +SKIP("FIXME: error in doctest")
2025-08-14T21:17:23.4666379Z         >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_()
2025-08-14T21:17:23.4666849Z         >>> input_lengths = torch.tensor(T, dtype=torch.long)
2025-08-14T21:17:23.4667210Z         >>>
2025-08-14T21:17:23.4667526Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:23.4668061Z         >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long)
2025-08-14T21:17:23.4668521Z         >>> target = torch.randint(
2025-08-14T21:17:23.4668815Z         ...     low=1,
2025-08-14T21:17:23.4669047Z         ...     high=C,
2025-08-14T21:17:23.4669309Z         ...     size=(target_lengths,),
2025-08-14T21:17:23.4669624Z         ...     dtype=torch.long,
2025-08-14T21:17:23.4669908Z         ... )
2025-08-14T21:17:23.4670131Z         >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:23.4670516Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:23.4670918Z         >>> loss.backward()
2025-08-14T21:17:23.4671092Z 
2025-08-14T21:17:23.4671179Z     Reference:
2025-08-14T21:17:23.4671574Z         A. Graves et al.: Connectionist Temporal Classification:
2025-08-14T21:17:23.4672104Z         Labelling Unsegmented Sequence Data with Recurrent Neural Networks:
2025-08-14T21:17:23.4672612Z         https://www.cs.toronto.edu/~graves/icml_2006.pdf
2025-08-14T21:17:23.4672893Z 
2025-08-14T21:17:23.4672976Z     Note:
2025-08-14T21:17:23.4673344Z         In order to use CuDNN, the following must be satisfied: :attr:`targets` must be
2025-08-14T21:17:23.4673966Z         in concatenated format, all :attr:`input_lengths` must be `T`.  :math:`blank=0`,
2025-08-14T21:17:23.4674561Z         :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of
2025-08-14T21:17:23.4675077Z         dtype :attr:`torch.int32`.
2025-08-14T21:17:23.4675279Z 
2025-08-14T21:17:23.4675550Z         The regular implementation uses the (more common in PyTorch) `torch.long` dtype.
2025-08-14T21:17:23.4675951Z 
2025-08-14T21:17:23.4675955Z 
2025-08-14T21:17:23.4676040Z     Note:
2025-08-14T21:17:23.4676412Z         In some circumstances when using the CUDA backend with CuDNN, this operator
2025-08-14T21:17:23.4677041Z         may select a nondeterministic algorithm to increase performance. If this is
2025-08-14T21:17:23.4677651Z         undesirable, you can try to make the operation deterministic (potentially at
2025-08-14T21:17:23.4678252Z         a performance cost) by setting ``torch.backends.cudnn.deterministic =
2025-08-14T21:17:23.4678689Z         True``.
2025-08-14T21:17:23.4679016Z         Please see the notes on :doc:`/notes/randomness` for background.
2025-08-14T21:17:23.4679437Z     
2025-08-14T21:17:23.4679809Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.4680180Z 
2025-08-14T21:17:23.5174332Z msg = Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=410.
2025-08-14T21:17:23.5175284Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.5175825Z Computes a partial inverse of :class:`MaxPool2d`.
2025-08-14T21:17:23.5176198Z 
2025-08-14T21:17:23.5176472Z     :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost.
2025-08-14T21:17:23.5176911Z 
2025-08-14T21:17:23.5177149Z     :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d`
2025-08-14T21:17:23.5177723Z     including the indices of the maximal values and computes a partial inverse
2025-08-14T21:17:23.5178245Z     in which all non-maximal values are set to zero.
2025-08-14T21:17:23.5178498Z 
2025-08-14T21:17:23.5178595Z     Note:
2025-08-14T21:17:23.5179037Z         This operation may behave nondeterministically when the input indices has repeat values.
2025-08-14T21:17:23.5179863Z         See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information.
2025-08-14T21:17:23.5180363Z 
2025-08-14T21:17:23.5180606Z     .. note:: :class:`MaxPool2d` can map several input sizes to the same output
2025-08-14T21:17:23.5181125Z               sizes. Hence, the inversion process can get ambiguous.
2025-08-14T21:17:23.5181596Z               To accommodate this, you can provide the needed output size
2025-08-14T21:17:23.5182114Z               as an additional argument :attr:`output_size` in the forward call.
2025-08-14T21:17:23.5182561Z               See the Inputs and Example below.
2025-08-14T21:17:23.5182812Z 
2025-08-14T21:17:23.5182905Z     Args:
2025-08-14T21:17:23.5183199Z         kernel_size (int or tuple): Size of the max pooling window.
2025-08-14T21:17:23.5183669Z         stride (int or tuple): Stride of the max pooling window.
2025-08-14T21:17:23.5184091Z             It is set to :attr:`kernel_size` by default.
2025-08-14T21:17:23.5184523Z         padding (int or tuple): Padding that was added to the input
2025-08-14T21:17:23.5184816Z 
2025-08-14T21:17:23.5184900Z     Inputs:
2025-08-14T21:17:23.5185153Z         - `input`: the input Tensor to invert
2025-08-14T21:17:23.5185588Z         - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d`
2025-08-14T21:17:23.5186056Z         - `output_size` (optional): the targeted output size
2025-08-14T21:17:23.5186342Z 
2025-08-14T21:17:23.5186427Z     Shape:
2025-08-14T21:17:23.5186741Z         - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`.
2025-08-14T21:17:23.5187256Z         - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where
2025-08-14T21:17:23.5187585Z 
2025-08-14T21:17:23.5187675Z           .. math::
2025-08-14T21:17:23.5188090Z             H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]}
2025-08-14T21:17:23.5188469Z 
2025-08-14T21:17:23.5188662Z           .. math::
2025-08-14T21:17:23.5189049Z             W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]}
2025-08-14T21:17:23.5189431Z 
2025-08-14T21:17:23.5189593Z           or as given by :attr:`output_size` in the call operator
2025-08-14T21:17:23.5189880Z 
2025-08-14T21:17:23.5189968Z     Example::
2025-08-14T21:17:23.5190097Z 
2025-08-14T21:17:23.5190273Z         >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True)
2025-08-14T21:17:23.5190668Z         >>> unpool = nn.MaxUnpool2d(2, stride=2)
2025-08-14T21:17:23.5191040Z         >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.],
2025-08-14T21:17:23.5191472Z                                     [ 5.,  6.,  7.,  8.],
2025-08-14T21:17:23.5191814Z                                     [ 9., 10., 11., 12.],
2025-08-14T21:17:23.5192138Z                                     [13., 14., 15., 16.]]]])
2025-08-14T21:17:23.5192483Z         >>> output, indices = pool(input)
2025-08-14T21:17:23.5192830Z         >>> unpool(output, indices)
2025-08-14T21:17:23.5193131Z         tensor([[[[  0.,   0.,   0.,   0.],
2025-08-14T21:17:23.5193446Z                   [  0.,   6.,   0.,   8.],
2025-08-14T21:17:23.5193752Z                   [  0.,   0.,   0.,   0.],
2025-08-14T21:17:23.5194047Z                   [  0.,  14.,   0.,  16.]]]])
2025-08-14T21:17:23.5194470Z         >>> # Now using output_size to resolve an ambiguous size for the inverse
2025-08-14T21:17:23.5194979Z         >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.,  5.],
2025-08-14T21:17:23.5195385Z                                     [ 6.,  7.,  8.,  9., 10.],
2025-08-14T21:17:23.5195713Z                                     [11., 12., 13., 14., 15.],
2025-08-14T21:17:23.5196055Z                                     [16., 17., 18., 19., 20.]]]])
2025-08-14T21:17:23.5196398Z         >>> output, indices = pool(input)
2025-08-14T21:17:23.5196780Z         >>> # This call will not work without specifying output_size
2025-08-14T21:17:23.5197234Z         >>> unpool(output, indices, output_size=input.size())
2025-08-14T21:17:23.5197611Z         tensor([[[[ 0.,  0.,  0.,  0.,  0.],
2025-08-14T21:17:23.5197909Z                   [ 0.,  7.,  0.,  9.,  0.],
2025-08-14T21:17:23.5198213Z                   [ 0.,  0.,  0.,  0.,  0.],
2025-08-14T21:17:23.5198523Z                   [ 0., 17.,  0., 19.,  0.]]]])
2025-08-14T21:17:23.5198730Z 
2025-08-14T21:17:23.5198735Z 
2025-08-14T21:17:23.5198829Z     
2025-08-14T21:17:23.5199184Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.5199564Z 
2025-08-14T21:17:23.5469210Z msg = Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272.
2025-08-14T21:17:23.5470153Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.5470849Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings.
2025-08-14T21:17:23.5471280Z 
2025-08-14T21:17:23.5471710Z     For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`,
2025-08-14T21:17:23.5472251Z     and with 2D inputs, this class
2025-08-14T21:17:23.5472467Z 
2025-08-14T21:17:23.5472774Z         * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``,
2025-08-14T21:17:23.5473508Z         * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``,
2025-08-14T21:17:23.5474245Z         * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``.
2025-08-14T21:17:23.5474662Z 
2025-08-14T21:17:23.5475014Z     However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these
2025-08-14T21:17:23.5475578Z     operations.
2025-08-14T21:17:23.5475717Z 
2025-08-14T21:17:23.5475990Z     EmbeddingBag also supports per-sample weights as an argument to the forward
2025-08-14T21:17:23.5476776Z     pass. This scales the output of the Embedding before performing a weighted
2025-08-14T21:17:23.5477378Z     reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the
2025-08-14T21:17:23.5477994Z     only supported ``mode`` is ``"sum"``, which computes a weighted sum according to
2025-08-14T21:17:23.5478466Z     :attr:`per_sample_weights`.
2025-08-14T21:17:23.5478661Z 
2025-08-14T21:17:23.5478747Z     Args:
2025-08-14T21:17:23.5479055Z         num_embeddings (int): size of the dictionary of embeddings
2025-08-14T21:17:23.5479519Z         embedding_dim (int): the size of each embedding vector
2025-08-14T21:17:23.5480116Z         max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm`
2025-08-14T21:17:23.5480698Z                                     is renormalized to have norm :attr:`max_norm`.
2025-08-14T21:17:23.5481318Z         norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``.
2025-08-14T21:17:23.5482109Z         scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of
2025-08-14T21:17:23.5482722Z                                                 the words in the mini-batch. Default ``False``.
2025-08-14T21:17:23.5483179Z                                                 Note: this option is not supported when ``mode="max"``.
2025-08-14T21:17:23.5483792Z         mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag.
2025-08-14T21:17:23.5484450Z                                  ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights`
2025-08-14T21:17:23.5485004Z                                  into consideration. ``"mean"`` computes the average of the values
2025-08-14T21:17:23.5485526Z                                  in the bag, ``"max"`` computes the max value over each bag.
2025-08-14T21:17:23.5485938Z                                  Default: ``"mean"``
2025-08-14T21:17:23.5486494Z         sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See
2025-08-14T21:17:23.5487181Z                                  Notes for more details regarding sparse gradients. Note: this option is not
2025-08-14T21:17:23.5487697Z                                  supported when ``mode="max"``.
2025-08-14T21:17:23.5488318Z         include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element
2025-08-14T21:17:23.5489040Z                                       is equivalent to the size of `indices`. This matches the CSR format.
2025-08-14T21:17:23.5489704Z         padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the
2025-08-14T21:17:23.5490430Z                                      gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated
2025-08-14T21:17:23.5491076Z                                      during training, i.e. it remains as a fixed "pad". For a newly constructed
2025-08-14T21:17:23.5491710Z                                      EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all
2025-08-14T21:17:23.5492333Z                                      zeros, but can be updated to another value to be used as the padding vector.
2025-08-14T21:17:23.5492942Z                                      Note that the embedding vector at :attr:`padding_idx` is excluded from the
2025-08-14T21:17:23.5493416Z                                      reduction.
2025-08-14T21:17:23.5493635Z 
2025-08-14T21:17:23.5493738Z     Attributes:
2025-08-14T21:17:23.5494187Z         weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)`
2025-08-14T21:17:23.5494767Z                          initialized from :math:`\mathcal{N}(0, 1)`.
2025-08-14T21:17:23.5495023Z 
2025-08-14T21:17:23.5495137Z     Examples::
2025-08-14T21:17:23.5495271Z 
2025-08-14T21:17:23.5495501Z         >>> # an EmbeddingBag module containing 10 tensors of size 3
2025-08-14T21:17:23.5495947Z         >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum')
2025-08-14T21:17:23.5496347Z         >>> # a batch of 2 samples of 4 indices each
2025-08-14T21:17:23.5496773Z         >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long)
2025-08-14T21:17:23.5497217Z         >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-08-14T21:17:23.5497624Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:23.5497993Z         >>> embedding_sum(input, offsets)
2025-08-14T21:17:23.5498321Z         tensor([[-0.8861, -5.4350, -0.0523],
2025-08-14T21:17:23.5498643Z                 [ 1.1306, -2.5798, -1.0044]])
2025-08-14T21:17:23.5498853Z 
2025-08-14T21:17:23.5498975Z         >>> # Example with padding_idx
2025-08-14T21:17:23.5499387Z         >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2)
2025-08-14T21:17:23.5499902Z         >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long)
2025-08-14T21:17:23.5500364Z         >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-08-14T21:17:23.5500740Z         >>> embedding_sum(input, offsets)
2025-08-14T21:17:23.5501055Z         tensor([[ 0.0000,  0.0000,  0.0000],
2025-08-14T21:17:23.5501366Z                 [-0.7082,  3.2145, -2.6251]])
2025-08-14T21:17:23.5501574Z 
2025-08-14T21:17:23.5501764Z         >>> # An EmbeddingBag can be loaded from an Embedding like so
2025-08-14T21:17:23.5502233Z         >>> embedding = nn.Embedding(10, 3, padding_idx=2)
2025-08-14T21:17:23.5502686Z         >>> embedding_sum = nn.EmbeddingBag.from_pretrained(
2025-08-14T21:17:23.5503066Z                 embedding.weight,
2025-08-14T21:17:23.5503393Z                 padding_idx=embedding.padding_idx,
2025-08-14T21:17:23.5503721Z                 mode='sum')
2025-08-14T21:17:23.5503978Z     
2025-08-14T21:17:23.5504345Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.5504712Z 
2025-08-14T21:17:23.5541950Z msg = Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186.
2025-08-14T21:17:23.5542962Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.5543483Z Take in and process masked source/target sequences.
2025-08-14T21:17:23.5543755Z 
2025-08-14T21:17:23.5543853Z         .. note::
2025-08-14T21:17:23.5543995Z 
2025-08-14T21:17:23.5544399Z             If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are
2025-08-14T21:17:23.5545038Z             not allowed to participate in the attention,
2025-08-14T21:17:23.5545490Z             which is the opposite of the definition for :attr:`attn_mask`
2025-08-14T21:17:23.5545993Z             in :func:`torch.nn.functional.scaled_dot_product_attention`.
2025-08-14T21:17:23.5546297Z 
2025-08-14T21:17:23.5546395Z         Args:
2025-08-14T21:17:23.5546659Z             src: the sequence to the encoder (required).
2025-08-14T21:17:23.5547047Z             tgt: the sequence to the decoder (required).
2025-08-14T21:17:23.5547479Z             src_mask: the additive mask for the src sequence (optional).
2025-08-14T21:17:23.5547953Z             tgt_mask: the additive mask for the tgt sequence (optional).
2025-08-14T21:17:23.5548461Z             memory_mask: the additive mask for the encoder output (optional).
2025-08-14T21:17:23.5549019Z             src_key_padding_mask: the Tensor mask for src keys per batch (optional).
2025-08-14T21:17:23.5549600Z             tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional).
2025-08-14T21:17:23.5550189Z             memory_key_padding_mask: the Tensor mask for memory keys per batch (optional).
2025-08-14T21:17:23.5550774Z             src_is_causal: If specified, applies a causal mask as ``src_mask``.
2025-08-14T21:17:23.5551248Z                 Default: ``None``; try to detect a causal mask.
2025-08-14T21:17:23.5551662Z                 Warning:
2025-08-14T21:17:23.5552137Z                 ``src_is_causal`` provides a hint that ``src_mask`` is
2025-08-14T21:17:23.5552601Z                 the causal mask. Providing incorrect hints can result in
2025-08-14T21:17:23.5553067Z                 incorrect execution, including forward and backward
2025-08-14T21:17:23.5553440Z                 compatibility.
2025-08-14T21:17:23.5553836Z             tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``.
2025-08-14T21:17:23.5554316Z                 Default: ``None``; try to detect a causal mask.
2025-08-14T21:17:23.5554654Z                 Warning:
2025-08-14T21:17:23.5554981Z                 ``tgt_is_causal`` provides a hint that ``tgt_mask`` is
2025-08-14T21:17:23.5555433Z                 the causal mask. Providing incorrect hints can result in
2025-08-14T21:17:23.5555892Z                 incorrect execution, including forward and backward
2025-08-14T21:17:23.5556261Z                 compatibility.
2025-08-14T21:17:23.5556628Z             memory_is_causal: If specified, applies a causal mask as
2025-08-14T21:17:23.5557021Z                 ``memory_mask``.
2025-08-14T21:17:23.5557300Z                 Default: ``False``.
2025-08-14T21:17:23.5557592Z                 Warning:
2025-08-14T21:17:23.5557890Z                 ``memory_is_causal`` provides a hint that
2025-08-14T21:17:23.5558296Z                 ``memory_mask`` is the causal mask. Providing incorrect
2025-08-14T21:17:23.5558807Z                 hints can result in incorrect execution, including
2025-08-14T21:17:23.5559258Z                 forward and backward compatibility.
2025-08-14T21:17:23.5559494Z 
2025-08-14T21:17:23.5559596Z         Shape:
2025-08-14T21:17:23.5559973Z             - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or
2025-08-14T21:17:23.5560454Z               `(N, S, E)` if `batch_first=True`.
2025-08-14T21:17:23.5560922Z             - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-08-14T21:17:23.5561407Z               `(N, T, E)` if `batch_first=True`.
2025-08-14T21:17:23.5561827Z             - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`.
2025-08-14T21:17:23.5562329Z             - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`.
2025-08-14T21:17:23.5562744Z             - memory_mask: :math:`(T, S)`.
2025-08-14T21:17:23.5563219Z             - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-08-14T21:17:23.5563829Z             - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`.
2025-08-14T21:17:23.5564455Z             - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-08-14T21:17:23.5564829Z 
2025-08-14T21:17:23.5565141Z             Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked
2025-08-14T21:17:23.5565791Z             positions. If a BoolTensor is provided, positions with ``True``
2025-08-14T21:17:23.5566394Z             are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor
2025-08-14T21:17:23.5566948Z             is provided, it will be added to the attention weight.
2025-08-14T21:17:23.5567527Z             [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by
2025-08-14T21:17:23.5568171Z             the attention. If a BoolTensor is provided, the positions with the
2025-08-14T21:17:23.5568819Z             value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged.
2025-08-14T21:17:23.5569244Z 
2025-08-14T21:17:23.5569515Z             - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-08-14T21:17:23.5570001Z               `(N, T, E)` if `batch_first=True`.
2025-08-14T21:17:23.5570236Z 
2025-08-14T21:17:23.5570479Z             Note: Due to the multi-head attention architecture in the transformer model,
2025-08-14T21:17:23.5571149Z             the output sequence length of a transformer is same as the input sequence
2025-08-14T21:17:23.5571633Z             (i.e. target) length of the decoder.
2025-08-14T21:17:23.5571863Z 
2025-08-14T21:17:23.5572185Z             where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the
2025-08-14T21:17:23.5572770Z             batch size, :math:`E` is the feature number
2025-08-14T21:17:23.5573011Z 
2025-08-14T21:17:23.5573113Z         Examples:
2025-08-14T21:17:23.5573355Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:23.5573670Z             >>> output = transformer_model(
2025-08-14T21:17:23.5574041Z             ...     src, tgt, src_mask=src_mask, tgt_mask=tgt_mask
2025-08-14T21:17:23.5574393Z             ... )
2025-08-14T21:17:23.5574605Z         
2025-08-14T21:17:23.5574979Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.5575346Z 
2025-08-14T21:17:23.5854791Z msg = Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766.
2025-08-14T21:17:23.5855949Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.5856327Z 
2025-08-14T21:17:23.5856562Z Context manager for training with uneven inputs across processes in DDP.
2025-08-14T21:17:23.5856928Z 
2025-08-14T21:17:23.5857151Z This context manager will keep track of already-joined DDP processes,
2025-08-14T21:17:23.5857892Z and "shadow" the forward and backward passes by inserting collective
2025-08-14T21:17:23.5858510Z communication operations to match with the ones created by non-joined
2025-08-14T21:17:23.5859080Z DDP processes. This will ensure each collective call has a corresponding
2025-08-14T21:17:23.5859653Z call by already-joined DDP processes, preventing hangs or errors that
2025-08-14T21:17:23.5860191Z would otherwise happen when training with uneven inputs across
2025-08-14T21:17:23.5860755Z processes. Alternatively, if the flag ``throw_on_early_termination`` is
2025-08-14T21:17:23.5861308Z specified to be ``True``, all trainers will throw an error once one rank
2025-08-14T21:17:23.5861832Z runs out of inputs, allowing these errors to be caught and handled
2025-08-14T21:17:23.5862262Z according to application logic.
2025-08-14T21:17:23.5862457Z 
2025-08-14T21:17:23.5862673Z Once all DDP processes have joined, the context manager will broadcast
2025-08-14T21:17:23.5863238Z the model corresponding to the last joined process to all processes to
2025-08-14T21:17:23.5863731Z ensure the model is the same across all processes
2025-08-14T21:17:23.5864101Z (which is guaranteed by DDP).
2025-08-14T21:17:23.5864289Z 
2025-08-14T21:17:23.5864489Z To use this to enable training with uneven inputs across processes,
2025-08-14T21:17:23.5865032Z simply wrap this context manager around your training loop. No further
2025-08-14T21:17:23.5865546Z modifications to the model or data loading is required.
2025-08-14T21:17:23.5865828Z 
2025-08-14T21:17:23.5865943Z .. warning::
2025-08-14T21:17:23.5866289Z     If the model or training loop this context manager is wrapped around
2025-08-14T21:17:23.5866801Z     has additional distributed collective operations, such as
2025-08-14T21:17:23.5867286Z     ``SyncBatchNorm`` in the model's forward pass, then the flag
2025-08-14T21:17:23.5867786Z     ``throw_on_early_termination`` must be enabled. This is because this
2025-08-14T21:17:23.5868322Z     context manager is not aware of non-DDP collective communication.
2025-08-14T21:17:23.5868824Z     This flag will cause all ranks to throw when any one rank
2025-08-14T21:17:23.5869309Z     exhausts inputs, allowing these errors to be caught and recovered
2025-08-14T21:17:23.5869741Z     from across all ranks.
2025-08-14T21:17:23.5869912Z 
2025-08-14T21:17:23.5870004Z Args:
2025-08-14T21:17:23.5870293Z     divide_by_initial_world_size (bool): If ``True``, will divide
2025-08-14T21:17:23.5870795Z         gradients by the initial ``world_size`` DDP training was launched
2025-08-14T21:17:23.5871380Z         with. If ``False``, will compute the effective world size
2025-08-14T21:17:23.5871929Z         (number of ranks that have not depleted their inputs yet) and
2025-08-14T21:17:23.5872371Z         divide gradients by that during allreduce. Set
2025-08-14T21:17:23.5872815Z         ``divide_by_initial_world_size=True`` to ensure every input
2025-08-14T21:17:23.5873321Z         sample including the uneven inputs have equal weight in terms of
2025-08-14T21:17:23.5873813Z         how much they contribute to the global gradient. This is
2025-08-14T21:17:23.5874272Z         achieved by always dividing the gradient by the initial
2025-08-14T21:17:23.5874748Z         ``world_size`` even when we encounter uneven inputs. If you set
2025-08-14T21:17:23.5875225Z         this to ``False``, we divide the gradient by the remaining
2025-08-14T21:17:23.5875693Z         number of nodes. This ensures parity with training on a smaller
2025-08-14T21:17:23.5876196Z         ``world_size`` although it also means the uneven inputs would
2025-08-14T21:17:23.5876690Z         contribute more towards the global gradient. Typically, you
2025-08-14T21:17:23.5877175Z         would want to set this to ``True`` for cases where the last few
2025-08-14T21:17:23.5877679Z         inputs of your training job are uneven. In extreme cases, where
2025-08-14T21:17:23.5878177Z         there is a large discrepancy in the number of inputs, setting
2025-08-14T21:17:23.5878683Z         this to ``False`` might provide better results.
2025-08-14T21:17:23.5879164Z     enable (bool): Whether to enable uneven input detection or not. Pass
2025-08-14T21:17:23.5879667Z         in ``enable=False`` to disable in cases where you know that
2025-08-14T21:17:23.5880144Z         inputs are even across participating processes. Default is
2025-08-14T21:17:23.5880527Z         ``True``.
2025-08-14T21:17:23.5880962Z     throw_on_early_termination (bool): Whether to throw an error
2025-08-14T21:17:23.5881539Z         or continue training when at least one rank has exhausted
2025-08-14T21:17:23.5882024Z         inputs. If ``True``, will throw upon the first rank reaching end
2025-08-14T21:17:23.5882489Z         of data. If ``False``, will continue training with a smaller
2025-08-14T21:17:23.5883103Z         effective world size until all ranks are joined. Note that if
2025-08-14T21:17:23.5883625Z         this flag is specified, then the flag
2025-08-14T21:17:23.5884024Z         ``divide_by_initial_world_size`` would be ignored. Default
2025-08-14T21:17:23.5884410Z         is ``False``.
2025-08-14T21:17:23.5884560Z 
2025-08-14T21:17:23.5884564Z 
2025-08-14T21:17:23.5884672Z Example::
2025-08-14T21:17:23.5884792Z 
2025-08-14T21:17:23.5884915Z     >>> # xdoctest: +SKIP("Distributed")
2025-08-14T21:17:23.5885219Z     >>> import torch
2025-08-14T21:17:23.5885491Z     >>> import torch.distributed as dist
2025-08-14T21:17:23.5885806Z     >>> import os
2025-08-14T21:17:23.5886066Z     >>> import torch.multiprocessing as mp
2025-08-14T21:17:23.5886408Z     >>> import torch.nn as nn
2025-08-14T21:17:23.5886718Z     >>> # On each spawned worker
2025-08-14T21:17:23.5887003Z     >>> def worker(rank):
2025-08-14T21:17:23.5887353Z     >>>     dist.init_process_group("nccl", rank=rank, world_size=2)
2025-08-14T21:17:23.5887760Z     >>>     torch.cuda.set_device(rank)
2025-08-14T21:17:23.5888103Z     >>>     model = nn.Linear(1, 1, bias=False).to(rank)
2025-08-14T21:17:23.5888533Z     >>>     model = torch.nn.parallel.DistributedDataParallel(
2025-08-14T21:17:23.5888974Z     >>>         model, device_ids=[rank], output_device=rank
2025-08-14T21:17:23.5889321Z     >>>     )
2025-08-14T21:17:23.5889574Z     >>>     # Rank 1 gets one more input than rank 0.
2025-08-14T21:17:23.5890007Z     >>>     inputs = [torch.tensor([1]).float() for _ in range(10 + rank)]
2025-08-14T21:17:23.5890422Z     >>>     with model.join():
2025-08-14T21:17:23.5890701Z     >>>         for _ in range(5):
2025-08-14T21:17:23.5891009Z     >>>             for inp in inputs:
2025-08-14T21:17:23.5891436Z     >>>                 loss = model(inp).sum()
2025-08-14T21:17:23.5891759Z     >>>                 loss.backward()
2025-08-14T21:17:23.5892161Z     >>>     # Without the join() API, the below synchronization will hang
2025-08-14T21:17:23.5892616Z     >>>     # blocking for rank 1's allreduce to complete.
2025-08-14T21:17:23.5893000Z     >>>     torch.cuda.synchronize(device=rank)
2025-08-14T21:17:23.5893236Z 
2025-08-14T21:17:23.5893490Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.5893877Z 
2025-08-14T21:17:23.5894627Z msg = Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057.
2025-08-14T21:17:23.5895717Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.5896093Z 
2025-08-14T21:17:23.5896408Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction.
2025-08-14T21:17:23.5896837Z 
2025-08-14T21:17:23.5897055Z Registers an optimizer with DDP such that the optimization for a
2025-08-14T21:17:23.5897572Z parameter will run immediately when that parameter's gradient is
2025-08-14T21:17:23.5898099Z finished with reduction, instead of waiting for all parameters'
2025-08-14T21:17:23.5898636Z gradients to finish reduction. This can result in a training speedup
2025-08-14T21:17:23.5899214Z depending on your workload since the optimizer can run while gradient
2025-08-14T21:17:23.5899811Z reduction for other parameters are still ongoing. In addition, this has
2025-08-14T21:17:23.5900387Z the potential to reduce peak memory consumption during training, as it
2025-08-14T21:17:23.5900934Z only needs to load the per-parameter optimizer states of a single
2025-08-14T21:17:23.5901452Z parameter at a time, instead of loading all per-parameter optimizer
2025-08-14T21:17:23.5901875Z states at once.
2025-08-14T21:17:23.5902016Z 
2025-08-14T21:17:23.5902108Z Args:
2025-08-14T21:17:23.5902413Z     optim (Type): a ``torch.optim.Optimizer`` class to be registered
2025-08-14T21:17:23.5902829Z     as a fused optimizer.
2025-08-14T21:17:23.5903175Z     *args (Sequence[Any]): Arguments to forward to `optim`.
2025-08-14T21:17:23.5903659Z     optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters
2025-08-14T21:17:23.5904221Z     to optimize, similar to `params` argument of traditional `torch.optim`
2025-08-14T21:17:23.5904776Z     Optimizers. If this is omitted, all DDP model parameters will be
2025-08-14T21:17:23.5905190Z     optimized.
2025-08-14T21:17:23.5905513Z     **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`.
2025-08-14T21:17:23.5905835Z 
2025-08-14T21:17:23.5905925Z .. warning ::
2025-08-14T21:17:23.5906277Z     _register_fused_optim should only be called once on a DDP instance,
2025-08-14T21:17:23.5906810Z     and registering multiple fused optimizers for the same DDP model
2025-08-14T21:17:23.5907264Z     is not currently supported. Please ping
2025-08-14T21:17:23.5907749Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:23.5908195Z     for your use case.
2025-08-14T21:17:23.5908353Z 
2025-08-14T21:17:23.5908440Z .. warning ::
2025-08-14T21:17:23.5908767Z     _register_fused_optim and register_comm_hook currently do not
2025-08-14T21:17:23.5909521Z     compose together, meaning that custom DDP communication hooks are
2025-08-14T21:17:23.5910018Z     not supported with overlapped optimizers. Please ping
2025-08-14T21:17:23.5910538Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:23.5910986Z     for your use case.
2025-08-14T21:17:23.5911142Z 
2025-08-14T21:17:23.5911230Z .. warning ::
2025-08-14T21:17:23.5911663Z     Gradient accumulation and DDP `no_sync` are currently not supported
2025-08-14T21:17:23.5912137Z     with overlapped optimizer. Please ping
2025-08-14T21:17:23.5912606Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:23.5913166Z     for your use case.
2025-08-14T21:17:23.5913340Z 
2025-08-14T21:17:23.5913430Z Example::
2025-08-14T21:17:23.5913550Z 
2025-08-14T21:17:23.5913692Z     >>> # xdoctest: +SKIP("No rendezvous handler")
2025-08-14T21:17:23.5914224Z     >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...')
2025-08-14T21:17:23.5914850Z     >>> net = torch.nn.parallel.DistributedDataParallel(model, pg)
2025-08-14T21:17:23.5915256Z     >>> lr = 1e-2
2025-08-14T21:17:23.5915495Z     >>> betas = (0.9, 0.99)
2025-08-14T21:17:23.5915748Z     >>> eps = 1e-6
2025-08-14T21:17:23.5916116Z     >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps)
2025-08-14T21:17:23.5916582Z     >>> # Example with subset of parameters
2025-08-14T21:17:23.5916933Z     >>> params_to_opt = [list(net.parameters())[0]]
2025-08-14T21:17:23.5917290Z     >>> net._register_fused_optim(
2025-08-14T21:17:23.5917716Z     ...   torch.optim.Adam, lr, optim_params=params_to_opt,  betas=betas, eps=eps
2025-08-14T21:17:23.5918140Z     ... )
2025-08-14T21:17:23.5918269Z 
2025-08-14T21:17:23.5918519Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.5918899Z 
2025-08-14T21:17:23.6410994Z msg = Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14.
2025-08-14T21:17:23.6412046Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6412909Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``.
2025-08-14T21:17:23.6413249Z 
2025-08-14T21:17:23.6413525Z     The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-08-14T21:17:23.6414199Z     Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-08-14T21:17:23.6414990Z     This function is used to facilitate the computation to adopt NHWC kernels, which
2025-08-14T21:17:23.6415774Z     provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-08-14T21:17:23.6416412Z 
2025-08-14T21:17:23.6416573Z     .. note::
2025-08-14T21:17:23.6417262Z         Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive
2025-08-14T21:17:23.6418020Z         than the utility function ``convert_conv2d_weight_memory_format``. Any
2025-08-14T21:17:23.6418586Z         layer with 4d weight will be affected by ``model.to``, which does not
2025-08-14T21:17:23.6419160Z         necessarily benefit from conversion to specified ``memory_format``.
2025-08-14T21:17:23.6419737Z         One place we are confident in is that NHWC(channels_last) conversion for
2025-08-14T21:17:23.6420307Z         convolution in cuDNN, as it is beneficial to run convolution in NHWC,
2025-08-14T21:17:23.6420844Z         even in cases where we have to apply permutation to input tensors.
2025-08-14T21:17:23.6421172Z 
2025-08-14T21:17:23.6421405Z         Hence our strategy here is to convert only the weight of convolution to
2025-08-14T21:17:23.6421868Z         channels_last. This ensures that;
2025-08-14T21:17:23.6422310Z         1. Fast convolution kernels will be used, the benefit of which could
2025-08-14T21:17:23.6422880Z         outweigh overhead of permutation (if input is not in the same format).
2025-08-14T21:17:23.6423469Z         2. No unnecessary permutations are applied on layers that do not benefit
2025-08-14T21:17:23.6423943Z         from memory_format conversion.
2025-08-14T21:17:23.6424158Z 
2025-08-14T21:17:23.6424384Z         The optimal case is that, layers between convolution layers are channels
2025-08-14T21:17:23.6424972Z         last compatible. Input tensor would be permuted to channels last when it
2025-08-14T21:17:23.6425563Z         encounters the first convolution layer and stay in that memory format.
2025-08-14T21:17:23.6426165Z         Hence following convolutions will not need to permute its input tensor.
2025-08-14T21:17:23.6426525Z 
2025-08-14T21:17:23.6426911Z         In case where a channels last incompatible layer is between convolution
2025-08-14T21:17:23.6427475Z         layers, we need to permute the input tensor back to contiguous format
2025-08-14T21:17:23.6428042Z         for that layer. The input tensor will go through the remaining layers in
2025-08-14T21:17:23.6428623Z         contiguous format and be permuted to channels last when it encounters
2025-08-14T21:17:23.6429181Z         another convolution layer. There's no point in propagating that
2025-08-14T21:17:23.6429740Z         permutation to an earlier layer, as most layers are quite agnostic to
2025-08-14T21:17:23.6430186Z         ``memory_format``.
2025-08-14T21:17:23.6430359Z 
2025-08-14T21:17:23.6430593Z         This claim might change when PyTorch supports fusion of permutation, as
2025-08-14T21:17:23.6431174Z         there might have been a better spot to fuse the permutation other than
2025-08-14T21:17:23.6431749Z         immediately before a convolution.
2025-08-14T21:17:23.6431974Z 
2025-08-14T21:17:23.6432079Z     Args:
2025-08-14T21:17:23.6432409Z         module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container
2025-08-14T21:17:23.6432851Z                             ``nn.Module``
2025-08-14T21:17:23.6433220Z         memory_format: user specified ``memory_format``,
2025-08-14T21:17:23.6433658Z             e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-08-14T21:17:23.6433965Z 
2025-08-14T21:17:23.6434091Z     Returns:
2025-08-14T21:17:23.6434367Z         The original module with updated ``nn.Conv2d``
2025-08-14T21:17:23.6434652Z 
2025-08-14T21:17:23.6434756Z     Example:
2025-08-14T21:17:23.6435014Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:23.6435423Z         >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-08-14T21:17:23.6435796Z         >>> input = torch.randint(
2025-08-14T21:17:23.6436138Z         ...     1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda"
2025-08-14T21:17:23.6436492Z         ... )
2025-08-14T21:17:23.6436728Z         >>> model = nn.Sequential(
2025-08-14T21:17:23.6437038Z         >>>     nn.Conv2d(8, 4, 3)).cuda().half()
2025-08-14T21:17:23.6437369Z         >>> # This is identical to:
2025-08-14T21:17:23.6437823Z         >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last)
2025-08-14T21:17:23.6438356Z         >>> model = nn.utils.convert_conv2d_weight_memory_format(
2025-08-14T21:17:23.6438739Z         ...     model, torch.channels_last
2025-08-14T21:17:23.6439056Z         ... )
2025-08-14T21:17:23.6439291Z         >>> out = model(input)
2025-08-14T21:17:23.6439547Z     
2025-08-14T21:17:23.6439920Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6440290Z 
2025-08-14T21:17:23.6440976Z msg = Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93.
2025-08-14T21:17:23.6441994Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6442576Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format``
2025-08-14T21:17:23.6443186Z     The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-08-14T21:17:23.6443860Z     Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-08-14T21:17:23.6444516Z     This function is used to facilitate the computation to adopt NHWC kernels, which
2025-08-14T21:17:23.6445192Z     provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-08-14T21:17:23.6445626Z 
2025-08-14T21:17:23.6445718Z     .. note::
2025-08-14T21:17:23.6446108Z         Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive
2025-08-14T21:17:23.6446710Z         than the utility function ``convert_conv3d_weight_memory_format``. Any
2025-08-14T21:17:23.6447254Z         layer with 4d weight will be affected by ``model.to``, which does not
2025-08-14T21:17:23.6447955Z         necessarily benefit from conversion to specified ``memory_format``.
2025-08-14T21:17:23.6448546Z         One place we are confident in is that NDHWC(channels_last_3d) conversion for
2025-08-14T21:17:23.6449125Z         convolution in cuDNN, as it is beneficial to run convolution in NDHWC,
2025-08-14T21:17:23.6449678Z         even in cases where we have to apply permutation to input tensors.
2025-08-14T21:17:23.6450014Z 
2025-08-14T21:17:23.6450243Z         Hence our strategy here is to convert only the weight of convolution to
2025-08-14T21:17:23.6450732Z         channels_last_3d. This ensures that;
2025-08-14T21:17:23.6451174Z         1. Fast convolution kernels will be used, the benefit of which could
2025-08-14T21:17:23.6451743Z         outweigh overhead of permutation (if input is not in the same format).
2025-08-14T21:17:23.6452333Z         2. No unnecessary permutations are applied on layers that do not benefit
2025-08-14T21:17:23.6452792Z         from memory_format conversion.
2025-08-14T21:17:23.6453025Z 
2025-08-14T21:17:23.6453247Z         The optimal case is that, layers between convolution layers are channels
2025-08-14T21:17:23.6453829Z         last compatible. Input tensor would be permuted to channels last when it
2025-08-14T21:17:23.6454418Z         encounters the first convolution layer and stay in that memory format.
2025-08-14T21:17:23.6455001Z         Hence following convolutions will not need to permute its input tensor.
2025-08-14T21:17:23.6455419Z 
2025-08-14T21:17:23.6455688Z         In case where a channels last incompatible layer is between convolution
2025-08-14T21:17:23.6456252Z         layers, we need to permute the input tensor back to contiguous format
2025-08-14T21:17:23.6456822Z         for that layer. The input tensor will go through the remaining layers in
2025-08-14T21:17:23.6457393Z         contiguous format and be permuted to channels last when it encounters
2025-08-14T21:17:23.6457960Z         another convolution layer. There's no point in propagating that
2025-08-14T21:17:23.6458514Z         permutation to an earlier layer, as most layers are quite agnostic to
2025-08-14T21:17:23.6458946Z         ``memory_format``.
2025-08-14T21:17:23.6459128Z 
2025-08-14T21:17:23.6459357Z         This claim might change when PyTorch supports fusion of permutation, as
2025-08-14T21:17:23.6459934Z         there might have been a better spot to fuse the permutation other than
2025-08-14T21:17:23.6460398Z         immediately before a convolution.
2025-08-14T21:17:23.6460623Z 
2025-08-14T21:17:23.6460707Z     Args:
2025-08-14T21:17:23.6461045Z         module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container
2025-08-14T21:17:23.6461483Z                             ``nn.Module``
2025-08-14T21:17:23.6461838Z         memory_format: user specified ``memory_format``,
2025-08-14T21:17:23.6462281Z             e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-08-14T21:17:23.6462587Z 
2025-08-14T21:17:23.6462672Z     Returns:
2025-08-14T21:17:23.6462954Z         The original module with updated ``nn.Conv3d``
2025-08-14T21:17:23.6463208Z 
2025-08-14T21:17:23.6463294Z     Example:
2025-08-14T21:17:23.6463565Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:23.6463970Z         >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-08-14T21:17:23.6464335Z         >>> input = torch.randint(
2025-08-14T21:17:23.6464689Z         ...     1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda"
2025-08-14T21:17:23.6465043Z         ... )
2025-08-14T21:17:23.6465280Z         >>> model = nn.Sequential(
2025-08-14T21:17:23.6465584Z         >>>     nn.Conv3d(8, 4, 3)).cuda().half()
2025-08-14T21:17:23.6465918Z         >>> # This is identical to:
2025-08-14T21:17:23.6466376Z         >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d)
2025-08-14T21:17:23.6466905Z         >>> model = nn.utils.convert_conv3d_weight_memory_format(
2025-08-14T21:17:23.6467305Z         ...     model, torch.channels_last_3d
2025-08-14T21:17:23.6467686Z         ... )
2025-08-14T21:17:23.6467910Z         >>> out = model(input)
2025-08-14T21:17:23.6468185Z     
2025-08-14T21:17:23.6468559Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6468926Z 
2025-08-14T21:17:23.6540869Z msg = Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424.
2025-08-14T21:17:23.6541866Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6542414Z Register a parametrization to a tensor in a module.
2025-08-14T21:17:23.6542694Z 
2025-08-14T21:17:23.6542967Z     Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``,
2025-08-14T21:17:23.6543652Z     the module will return the parametrized version ``parametrization(module.weight)``.
2025-08-14T21:17:23.6544310Z     If the original tensor requires a gradient, the backward pass will differentiate
2025-08-14T21:17:23.6544997Z     through :attr:`parametrization`, and the optimizer will update the tensor accordingly.
2025-08-14T21:17:23.6545421Z 
2025-08-14T21:17:23.6545735Z     The first time that a module registers a parametrization, this function will add an attribute
2025-08-14T21:17:23.6546418Z     ``parametrizations`` to the module of type :class:`~ParametrizationList`.
2025-08-14T21:17:23.6546779Z 
2025-08-14T21:17:23.6547182Z     The list of parametrizations on the tensor ``weight`` will be accessible under
2025-08-14T21:17:23.6547743Z     ``module.parametrizations.weight``.
2025-08-14T21:17:23.6547973Z 
2025-08-14T21:17:23.6548119Z     The original tensor will be accessible under
2025-08-14T21:17:23.6548521Z     ``module.parametrizations.weight.original``.
2025-08-14T21:17:23.6548778Z 
2025-08-14T21:17:23.6549041Z     Parametrizations may be concatenated by registering several parametrizations
2025-08-14T21:17:23.6561753Z     on the same attribute.
2025-08-14T21:17:23.6561975Z 
2025-08-14T21:17:23.6562246Z     The training mode of a registered parametrization is updated on registration
2025-08-14T21:17:23.6562762Z     to match the training mode of the host module
2025-08-14T21:17:23.6563009Z 
2025-08-14T21:17:23.6563315Z     Parametrized parameters and buffers have an inbuilt caching system that can be activated
2025-08-14T21:17:23.6563875Z     using the context manager :func:`cached`.
2025-08-14T21:17:23.6564120Z 
2025-08-14T21:17:23.6564366Z     A :attr:`parametrization` may optionally implement a method with signature
2025-08-14T21:17:23.6564731Z 
2025-08-14T21:17:23.6564865Z     .. code-block:: python
2025-08-14T21:17:23.6565038Z 
2025-08-14T21:17:23.6565258Z         def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]]
2025-08-14T21:17:23.6565603Z 
2025-08-14T21:17:23.6565868Z     This method is called on the unparametrized tensor when the first parametrization
2025-08-14T21:17:23.6566468Z     is registered to compute the initial value of the original tensor.
2025-08-14T21:17:23.6567112Z     If this method is not implemented, the original tensor will be just the unparametrized tensor.
2025-08-14T21:17:23.6567537Z 
2025-08-14T21:17:23.6567851Z     If all the parametrizations registered on a tensor implement `right_inverse` it is possible
2025-08-14T21:17:23.6568575Z     to initialize a parametrized tensor by assigning to it, as shown in the example below.
2025-08-14T21:17:23.6568995Z 
2025-08-14T21:17:23.6569225Z     It is possible for the first parametrization to depend on several inputs.
2025-08-14T21:17:23.6569821Z     This may be implemented returning a tuple of tensors from ``right_inverse``
2025-08-14T21:17:23.6570406Z     (see the example implementation of a ``RankOne`` parametrization below).
2025-08-14T21:17:23.6570768Z 
2025-08-14T21:17:23.6571101Z     In this case, the unconstrained tensors are also located under ``module.parametrizations.weight``
2025-08-14T21:17:23.6571690Z     with names ``original0``, ``original1``,...
2025-08-14T21:17:23.6571927Z 
2025-08-14T21:17:23.6572059Z     .. note::
2025-08-14T21:17:23.6572348Z 
2025-08-14T21:17:23.6572632Z         If unsafe=False (default) both the forward and right_inverse methods will be called
2025-08-14T21:17:23.6573161Z         once to perform a number of consistency checks.
2025-08-14T21:17:23.6573694Z         If unsafe=True, then right_inverse will be called if the tensor is not parametrized,
2025-08-14T21:17:23.6574205Z         and nothing will be called otherwise.
2025-08-14T21:17:23.6574433Z 
2025-08-14T21:17:23.6574523Z     .. note::
2025-08-14T21:17:23.6574665Z 
2025-08-14T21:17:23.6574867Z         In most situations, ``right_inverse`` will be a function such that
2025-08-14T21:17:23.6575312Z         ``forward(right_inverse(X)) == X`` (see
2025-08-14T21:17:23.6575839Z         `right inverse <https://en.wikipedia.org/wiki/Inverse_function#Right_inverses>`_).
2025-08-14T21:17:23.6576483Z         Sometimes, when the parametrization is not surjective, it may be reasonable
2025-08-14T21:17:23.6576952Z         to relax this.
2025-08-14T21:17:23.6577109Z 
2025-08-14T21:17:23.6577213Z     .. warning::
2025-08-14T21:17:23.6577352Z 
2025-08-14T21:17:23.6577642Z         If a parametrization depends on several inputs, :func:`~register_parametrization`
2025-08-14T21:17:23.6578287Z         will register a number of new parameters. If such parametrization is registered
2025-08-14T21:17:23.6578938Z         after the optimizer is created, these new parameters will need to be added manually
2025-08-14T21:17:23.6579599Z         to the optimizer. See :meth:`torch.Optimizer.add_param_group`.
2025-08-14T21:17:23.6579947Z 
2025-08-14T21:17:23.6580032Z     Args:
2025-08-14T21:17:23.6580371Z         module (nn.Module): module on which to register the parametrization
2025-08-14T21:17:23.6580924Z         tensor_name (str): name of the parameter or buffer on which to register
2025-08-14T21:17:23.6581369Z             the parametrization
2025-08-14T21:17:23.6581758Z         parametrization (nn.Module): the parametrization to register
2025-08-14T21:17:23.6582174Z     Keyword args:
2025-08-14T21:17:23.6582544Z         unsafe (bool): a boolean flag that denotes whether the parametrization
2025-08-14T21:17:23.6583063Z             may change the dtype and shape of the tensor. Default: `False`
2025-08-14T21:17:23.6583650Z             Warning: the parametrization is not checked for consistency upon registration.
2025-08-14T21:17:23.6584163Z             Enable this flag at your own risk.
2025-08-14T21:17:23.6584391Z 
2025-08-14T21:17:23.6584486Z     Raises:
2025-08-14T21:17:23.6584891Z         ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name`
2025-08-14T21:17:23.6585303Z 
2025-08-14T21:17:23.6585391Z     Examples:
2025-08-14T21:17:23.6585679Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-08-14T21:17:23.6586026Z         >>> import torch
2025-08-14T21:17:23.6586299Z         >>> import torch.nn as nn
2025-08-14T21:17:23.6586637Z         >>> import torch.nn.utils.parametrize as P
2025-08-14T21:17:23.6586959Z         >>>
2025-08-14T21:17:23.6587200Z         >>> class Symmetric(nn.Module):
2025-08-14T21:17:23.6587524Z         >>>     def forward(self, X):
2025-08-14T21:17:23.6587896Z         >>>         return X.triu() + X.triu(1).T  # Return a symmetric matrix
2025-08-14T21:17:23.6588284Z         >>>
2025-08-14T21:17:23.6588524Z         >>>     def right_inverse(self, A):
2025-08-14T21:17:23.6588849Z         >>>         return A.triu()
2025-08-14T21:17:23.6589122Z         >>>
2025-08-14T21:17:23.6589347Z         >>> m = nn.Linear(5, 5)
2025-08-14T21:17:23.6589709Z         >>> P.register_parametrization(m, "weight", Symmetric())
2025-08-14T21:17:23.6590223Z         >>> print(torch.allclose(m.weight, m.weight.T))  # m.weight is now symmetric
2025-08-14T21:17:23.6590672Z         True
2025-08-14T21:17:23.6590906Z         >>> A = torch.rand(5, 5)
2025-08-14T21:17:23.6591204Z         >>> A = A + A.T  # A is now symmetric
2025-08-14T21:17:23.6591731Z         >>> m.weight = A  # Initialize the weight to be the symmetric matrix A
2025-08-14T21:17:23.6592253Z         >>> print(torch.allclose(m.weight, A))
2025-08-14T21:17:23.6592577Z         True
2025-08-14T21:17:23.6592703Z 
2025-08-14T21:17:23.6592811Z         >>> class RankOne(nn.Module):
2025-08-14T21:17:23.6593134Z         >>>     def forward(self, x, y):
2025-08-14T21:17:23.6593497Z         >>> # Form a rank 1 matrix multiplying two vectors
2025-08-14T21:17:23.6593873Z         >>>         return x.unsqueeze(-1) @ y.unsqueeze(-2)
2025-08-14T21:17:23.6594209Z         >>>
2025-08-14T21:17:23.6594446Z         >>>     def right_inverse(self, Z):
2025-08-14T21:17:23.6594773Z         >>> # Project Z onto the rank 1 matrices
2025-08-14T21:17:23.6595160Z         >>>         U, S, Vh = torch.linalg.svd(Z, full_matrices=False)
2025-08-14T21:17:23.6595551Z         >>> # Return rescaled singular vectors
2025-08-14T21:17:23.6595890Z         >>>         s0_sqrt = S[0].sqrt().unsqueeze(-1)
2025-08-14T21:17:23.6596275Z         >>>         return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt
2025-08-14T21:17:23.6596632Z         >>>
2025-08-14T21:17:23.6596899Z         >>> linear_rank_one = P.register_parametrization(
2025-08-14T21:17:23.6597277Z         ...     nn.Linear(4, 4), "weight", RankOne()
2025-08-14T21:17:23.6597606Z         ... )
2025-08-14T21:17:23.6597943Z         >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item())
2025-08-14T21:17:23.6598340Z         1
2025-08-14T21:17:23.6598474Z 
2025-08-14T21:17:23.6598587Z     
2025-08-14T21:17:23.6598958Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6599358Z 
2025-08-14T21:17:23.6656111Z msg = Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979.
2025-08-14T21:17:23.6657121Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6657805Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension.
2025-08-14T21:17:23.6658244Z 
2025-08-14T21:17:23.6658493Z     Prunes tensor corresponding to parameter called ``name`` in ``module``
2025-08-14T21:17:23.6659065Z     by removing the specified ``amount`` of (currently unpruned) channels
2025-08-14T21:17:23.6659567Z     along the specified ``dim`` with the lowest L\ ``n``-norm.
2025-08-14T21:17:23.6660197Z     Modifies module in place (and also return the modified module)
2025-08-14T21:17:23.6660759Z     by:
2025-08-14T21:17:23.6660898Z 
2025-08-14T21:17:23.6661260Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:23.6661876Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:23.6662429Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:23.6662973Z        original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:23.6663388Z        ``name+'_orig'``.
2025-08-14T21:17:23.6663563Z 
2025-08-14T21:17:23.6663646Z     Args:
2025-08-14T21:17:23.6663958Z         module (nn.Module): module containing the tensor to prune
2025-08-14T21:17:23.6664456Z         name (str): parameter name within ``module`` on which pruning
2025-08-14T21:17:23.6665025Z                 will act.
2025-08-14T21:17:23.6665487Z         amount (int or float): quantity of parameters to prune.
2025-08-14T21:17:23.6666091Z             If ``float``, should be between 0.0 and 1.0 and represent the
2025-08-14T21:17:23.6666583Z             fraction of parameters to prune. If ``int``, it represents the
2025-08-14T21:17:23.6667039Z             absolute number of parameters to prune.
2025-08-14T21:17:23.6667484Z         n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid
2025-08-14T21:17:23.6667945Z             entries for argument ``p`` in :func:`torch.norm`.
2025-08-14T21:17:23.6668418Z         dim (int): index of the dim along which we define channels to prune.
2025-08-14T21:17:23.6668979Z         importance_scores (torch.Tensor): tensor of importance scores (of same
2025-08-14T21:17:23.6669689Z             shape as module parameter) used to compute mask for pruning.
2025-08-14T21:17:23.6670212Z             The values in this tensor indicate the importance of the corresponding
2025-08-14T21:17:23.6670693Z             elements in the parameter being pruned.
2025-08-14T21:17:23.6671165Z             If unspecified or None, the module parameter will be used in its place.
2025-08-14T21:17:23.6671576Z 
2025-08-14T21:17:23.6671683Z     Returns:
2025-08-14T21:17:23.6672024Z         module (nn.Module): modified (i.e. pruned) version of the input module
2025-08-14T21:17:23.6672374Z 
2025-08-14T21:17:23.6672462Z     Examples:
2025-08-14T21:17:23.6672716Z         >>> from torch.nn.utils import prune
2025-08-14T21:17:23.6673038Z         >>> m = prune.ln_structured(
2025-08-14T21:17:23.6673426Z         ...     nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf")
2025-08-14T21:17:23.6673810Z         ... )
2025-08-14T21:17:23.6674012Z     
2025-08-14T21:17:23.6674383Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6674753Z 
2025-08-14T21:17:23.6675335Z msg = Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026.
2025-08-14T21:17:23.6676255Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6676630Z 
2025-08-14T21:17:23.6677072Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``.
2025-08-14T21:17:23.6677713Z 
2025-08-14T21:17:23.6677825Z Modifies modules in place by:
2025-08-14T21:17:23.6678032Z 
2025-08-14T21:17:23.6678239Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:23.6678786Z    binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:23.6679337Z 2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:23.6679863Z    original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:23.6680286Z    ``name+'_orig'``.
2025-08-14T21:17:23.6680437Z 
2025-08-14T21:17:23.6680531Z Args:
2025-08-14T21:17:23.6680846Z     parameters (Iterable of (module, name) tuples): parameters of
2025-08-14T21:17:23.6681362Z         the model to prune in a global fashion, i.e. by aggregating all
2025-08-14T21:17:23.6681886Z         weights prior to deciding which ones to prune. module must be of
2025-08-14T21:17:23.6682366Z         type :class:`nn.Module`, and name must be a string.
2025-08-14T21:17:23.6682844Z     pruning_method (function): a valid pruning function from this module,
2025-08-14T21:17:23.6683360Z         or a custom one implemented by the user that satisfies the
2025-08-14T21:17:23.6683886Z         implementation guidelines and has ``PRUNING_TYPE='unstructured'``.
2025-08-14T21:17:23.6684454Z     importance_scores (dict): a dictionary mapping (module, name) tuples to
2025-08-14T21:17:23.6685034Z         the corresponding parameter's importance scores tensor. The tensor
2025-08-14T21:17:23.6685592Z         should be the same shape as the parameter, and is used for computing
2025-08-14T21:17:23.6686022Z         mask for pruning.
2025-08-14T21:17:23.6686392Z         If unspecified or None, the parameter will be used in place of its
2025-08-14T21:17:23.6686821Z         importance scores.
2025-08-14T21:17:23.6687124Z     kwargs: other keyword arguments such as:
2025-08-14T21:17:23.6687550Z         amount (int or float): quantity of parameters to prune across the
2025-08-14T21:17:23.6687976Z         specified parameters.
2025-08-14T21:17:23.6688341Z         If ``float``, should be between 0.0 and 1.0 and represent the
2025-08-14T21:17:23.6688820Z         fraction of parameters to prune. If ``int``, it represents the
2025-08-14T21:17:23.6689273Z         absolute number of parameters to prune.
2025-08-14T21:17:23.6689522Z 
2025-08-14T21:17:23.6689607Z Raises:
2025-08-14T21:17:23.6689882Z     TypeError: if ``PRUNING_TYPE != 'unstructured'``
2025-08-14T21:17:23.6690138Z 
2025-08-14T21:17:23.6690284Z Note:
2025-08-14T21:17:23.6690622Z     Since global structured pruning doesn't make much sense unless the
2025-08-14T21:17:23.6691160Z     norm is normalized by the size of the parameter, we now limit the
2025-08-14T21:17:23.6691620Z     scope of global pruning to unstructured methods.
2025-08-14T21:17:23.6691894Z 
2025-08-14T21:17:23.6691980Z Examples:
2025-08-14T21:17:23.6692231Z     >>> from torch.nn.utils import prune
2025-08-14T21:17:23.6692578Z     >>> from collections import OrderedDict
2025-08-14T21:17:23.6692897Z     >>> net = nn.Sequential(
2025-08-14T21:17:23.6693177Z     ...     OrderedDict(
2025-08-14T21:17:23.6693428Z     ...         [
2025-08-14T21:17:23.6693673Z     ...             ("first", nn.Linear(10, 4)),
2025-08-14T21:17:23.6694016Z     ...             ("second", nn.Linear(4, 1)),
2025-08-14T21:17:23.6694326Z     ...         ]
2025-08-14T21:17:23.6694535Z     ...     )
2025-08-14T21:17:23.6694751Z     ... )
2025-08-14T21:17:23.6694980Z     >>> parameters_to_prune = (
2025-08-14T21:17:23.6695272Z     ...     (net.first, "weight"),
2025-08-14T21:17:23.6695581Z     ...     (net.second, "weight"),
2025-08-14T21:17:23.6695870Z     ... )
2025-08-14T21:17:23.6696092Z     >>> prune.global_unstructured(
2025-08-14T21:17:23.6696401Z     ...     parameters_to_prune,
2025-08-14T21:17:23.6696732Z     ...     pruning_method=prune.L1Unstructured,
2025-08-14T21:17:23.6697065Z     ...     amount=10,
2025-08-14T21:17:23.6697326Z     ... )
2025-08-14T21:17:23.6697699Z     >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0))
2025-08-14T21:17:23.6698130Z     tensor(10)
2025-08-14T21:17:23.6698264Z 
2025-08-14T21:17:23.6698268Z 
2025-08-14T21:17:23.6698535Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6698900Z 
2025-08-14T21:17:23.6699416Z msg = Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149.
2025-08-14T21:17:23.6700312Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6701085Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``.
2025-08-14T21:17:23.6701590Z 
2025-08-14T21:17:23.6701814Z     Modifies module in place (and also return the modified module) by:
2025-08-14T21:17:23.6702140Z 
2025-08-14T21:17:23.6702351Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:23.6702900Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:23.6703449Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:23.6703992Z        original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:23.6704401Z        ``name+'_orig'``.
2025-08-14T21:17:23.6704574Z 
2025-08-14T21:17:23.6704657Z     Args:
2025-08-14T21:17:23.6704956Z         module (nn.Module): module containing the tensor to prune
2025-08-14T21:17:23.6705426Z         name (str): parameter name within ``module`` on which pruning
2025-08-14T21:17:23.6705817Z             will act.
2025-08-14T21:17:23.6706145Z         mask (Tensor): binary mask to be applied to the parameter.
2025-08-14T21:17:23.6706431Z 
2025-08-14T21:17:23.6706529Z     Returns:
2025-08-14T21:17:23.6706869Z         module (nn.Module): modified (i.e. pruned) version of the input module
2025-08-14T21:17:23.6707217Z 
2025-08-14T21:17:23.6707301Z     Examples:
2025-08-14T21:17:23.6707557Z         >>> from torch.nn.utils import prune
2025-08-14T21:17:23.6707883Z         >>> m = prune.custom_from_mask(
2025-08-14T21:17:23.6708268Z         ...     nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0])
2025-08-14T21:17:23.6708644Z         ... )
2025-08-14T21:17:23.6708860Z         >>> print(m.bias_mask)
2025-08-14T21:17:23.6709387Z         tensor([0., 1., 0.])
2025-08-14T21:17:23.6709559Z 
2025-08-14T21:17:23.6709653Z     
2025-08-14T21:17:23.6710157Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6710526Z 
2025-08-14T21:17:23.6728612Z msg = Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=350.
2025-08-14T21:17:23.6729513Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.6730041Z Pad a packed batch of variable length sequences.
2025-08-14T21:17:23.6730298Z 
2025-08-14T21:17:23.6730488Z     It is an inverse operation to :func:`pack_padded_sequence`.
2025-08-14T21:17:23.6730773Z 
2025-08-14T21:17:23.6731050Z     The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``)
2025-08-14T21:17:23.6731685Z     or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest
2025-08-14T21:17:23.6732163Z     sequence and ``B`` is the batch size.
2025-08-14T21:17:23.6732383Z 
2025-08-14T21:17:23.6732485Z     Example:
2025-08-14T21:17:23.6732849Z         >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
2025-08-14T21:17:23.6733361Z         >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]])
2025-08-14T21:17:23.6733722Z         >>> lens = [2, 1, 3]
2025-08-14T21:17:23.6734005Z         >>> packed = pack_padded_sequence(
2025-08-14T21:17:23.6734381Z         ...     seq, lens, batch_first=True, enforce_sorted=False
2025-08-14T21:17:23.6735186Z         ... )
2025-08-14T21:17:23.6735390Z         >>> packed
2025-08-14T21:17:23.6735825Z         PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]),
2025-08-14T21:17:23.6736402Z                        sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0]))
2025-08-14T21:17:23.6736988Z         >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True)
2025-08-14T21:17:23.6737443Z         >>> seq_unpacked
2025-08-14T21:17:23.6737707Z         tensor([[1, 2, 0],
2025-08-14T21:17:23.6737965Z                 [3, 0, 0],
2025-08-14T21:17:23.6738213Z                 [4, 5, 6]])
2025-08-14T21:17:23.6738480Z         >>> lens_unpacked
2025-08-14T21:17:23.6738742Z         tensor([2, 1, 3])
2025-08-14T21:17:23.6738903Z 
2025-08-14T21:17:23.6739002Z     .. note::
2025-08-14T21:17:23.6739291Z         :attr:`total_length` is useful to implement the
2025-08-14T21:17:23.6739774Z         ``pack sequence -> recurrent network -> unpack sequence`` pattern in a
2025-08-14T21:17:23.6740340Z         :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`.
2025-08-14T21:17:23.6740900Z         See :ref:`this FAQ section <pack-rnn-unpack-with-data-parallelism>` for
2025-08-14T21:17:23.6741335Z         details.
2025-08-14T21:17:23.6741469Z 
2025-08-14T21:17:23.6741563Z     Args:
2025-08-14T21:17:23.6741800Z         sequence (PackedSequence): batch to pad
2025-08-14T21:17:23.6742282Z         batch_first (bool, optional): if ``True``, the output will be in ``B x T x *``
2025-08-14T21:17:23.6742752Z             format, ``T x B x *`` otherwise.
2025-08-14T21:17:23.6743171Z         padding_value (float, optional): values for padded elements.
2025-08-14T21:17:23.6743699Z         total_length (int, optional): if not ``None``, the output will be padded to
2025-08-14T21:17:23.6744290Z             have length :attr:`total_length`. This method will throw :class:`ValueError`
2025-08-14T21:17:23.6744839Z             if :attr:`total_length` is less than the max sequence length in
2025-08-14T21:17:23.6745239Z             :attr:`sequence`.
2025-08-14T21:17:23.6745433Z 
2025-08-14T21:17:23.6745518Z     Returns:
2025-08-14T21:17:23.6745839Z         Tuple of Tensor containing the padded sequence, and a Tensor
2025-08-14T21:17:23.6746347Z         containing the list of lengths of each sequence in the batch.
2025-08-14T21:17:23.6746872Z         Batch elements will be re-ordered as they were ordered originally when
2025-08-14T21:17:23.6747433Z         the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``.
2025-08-14T21:17:23.6747859Z     
2025-08-14T21:17:23.6748274Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.6748650Z 
2025-08-14T21:17:23.7560132Z msg = Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808.
2025-08-14T21:17:23.7561055Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7561773Z Contains a list of schedulers expected to be called sequentially during the optimization process.
2025-08-14T21:17:23.7562222Z 
2025-08-14T21:17:23.7562601Z     Specifically, the schedulers will be called according to the milestone points, which should provide exact
2025-08-14T21:17:23.7563295Z     intervals by which each scheduler should be called at a given epoch.
2025-08-14T21:17:23.7563637Z 
2025-08-14T21:17:23.7563720Z     Args:
2025-08-14T21:17:23.7563979Z         optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:23.7564365Z         schedulers (list): List of chained schedulers.
2025-08-14T21:17:23.7564843Z         milestones (list): List of integers that reflects milestone points.
2025-08-14T21:17:23.7565355Z         last_epoch (int): The index of last epoch. Default: -1.
2025-08-14T21:17:23.7565632Z 
2025-08-14T21:17:23.7565736Z     Example:
2025-08-14T21:17:23.7565959Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7566300Z         >>> # Assuming optimizer uses lr = 0.05 for all groups
2025-08-14T21:17:23.7566884Z         >>> # lr = 0.005     if epoch == 0
2025-08-14T21:17:23.7567266Z         >>> # lr = 0.005     if epoch == 1
2025-08-14T21:17:23.7567583Z         >>> # lr = 0.005     if epoch == 2
2025-08-14T21:17:23.7567879Z         >>> # ...
2025-08-14T21:17:23.7568111Z         >>> # lr = 0.05      if epoch == 20
2025-08-14T21:17:23.7568433Z         >>> # lr = 0.045     if epoch == 21
2025-08-14T21:17:23.7568750Z         >>> # lr = 0.0405    if epoch == 22
2025-08-14T21:17:23.7569155Z         >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20)
2025-08-14T21:17:23.7569638Z         >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9)
2025-08-14T21:17:23.7570022Z         >>> scheduler = SequentialLR(
2025-08-14T21:17:23.7570357Z         ...     optimizer,
2025-08-14T21:17:23.7570650Z         ...     schedulers=[scheduler1, scheduler2],
2025-08-14T21:17:23.7570994Z         ...     milestones=[20],
2025-08-14T21:17:23.7571277Z         ... )
2025-08-14T21:17:23.7571506Z         >>> for epoch in range(100):
2025-08-14T21:17:23.7571808Z         >>>     train(...)
2025-08-14T21:17:23.7572074Z         >>>     validate(...)
2025-08-14T21:17:23.7572343Z         >>>     scheduler.step()
2025-08-14T21:17:23.7572544Z 
2025-08-14T21:17:23.7572735Z     .. image:: ../scripts/lr_scheduler_images/SequentialLR.png
2025-08-14T21:17:23.7573103Z     
2025-08-14T21:17:23.7573469Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.7573836Z 
2025-08-14T21:17:23.7596223Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233.
2025-08-14T21:17:23.7597165Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:23.7597716Z Reduce learning rate when a metric has stopped improving.
2025-08-14T21:17:23.7598005Z 
2025-08-14T21:17:23.7598221Z     Models often benefit from reducing the learning rate by a factor
2025-08-14T21:17:23.7598722Z     of 2-10 once learning stagnates. This scheduler reads a metrics
2025-08-14T21:17:23.7599227Z     quantity and if no improvement is seen for a 'patience' number
2025-08-14T21:17:23.7599661Z     of epochs, the learning rate is reduced.
2025-08-14T21:17:23.7599889Z 
2025-08-14T21:17:23.7599985Z     Args:
2025-08-14T21:17:23.7600228Z         optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:23.7600628Z         mode (str): One of `min`, `max`. In `min` mode, lr will
2025-08-14T21:17:23.7601053Z             be reduced when the quantity monitored has stopped
2025-08-14T21:17:23.7601659Z             decreasing; in `max` mode it will be reduced when the
2025-08-14T21:17:23.7602140Z             quantity monitored has stopped increasing. Default: 'min'.
2025-08-14T21:17:23.7602626Z         factor (float): Factor by which the learning rate will be
2025-08-14T21:17:23.7603041Z             reduced. new_lr = lr * factor. Default: 0.1.
2025-08-14T21:17:23.7603511Z         patience (int): The number of allowed epochs with no improvement after
2025-08-14T21:17:23.7603987Z             which the learning rate will be reduced.
2025-08-14T21:17:23.7604649Z             For example, consider the case of having no patience (`patience = 0`).
2025-08-14T21:17:23.7605603Z             In the first epoch, a baseline is established and is always considered good as there's no previous baseline.
2025-08-14T21:17:23.7606444Z             In the second epoch, if the performance is worse than the baseline,
2025-08-14T21:17:23.7606968Z             we have what is considered an intolerable epoch.
2025-08-14T21:17:23.7607533Z             Since the count of intolerable epochs (1) is greater than the patience level (0),
2025-08-14T21:17:23.7608156Z             the learning rate is reduced at the end of this epoch.
2025-08-14T21:17:23.7608832Z             From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch
2025-08-14T21:17:23.7609835Z             if the performance is worse than the baseline. If the performance improves or remains the same,
2025-08-14T21:17:23.7610642Z             the learning rate is not adjusted.
2025-08-14T21:17:23.7611028Z             Default: 10.
2025-08-14T21:17:23.7611373Z         threshold (float): Threshold for measuring the new optimum,
2025-08-14T21:17:23.7611900Z             to only focus on significant changes. Default: 1e-4.
2025-08-14T21:17:23.7612378Z         threshold_mode (str): One of `rel`, `abs`. In `rel` mode,
2025-08-14T21:17:23.7612917Z             dynamic_threshold = best * ( 1 + threshold ) in 'max'
2025-08-14T21:17:23.7613485Z             mode or best * ( 1 - threshold ) in `min` mode.
2025-08-14T21:17:23.7614094Z             In `abs` mode, dynamic_threshold = best + threshold in
2025-08-14T21:17:23.7614549Z             `max` mode or best - threshold in `min` mode. Default: 'rel'.
2025-08-14T21:17:23.7615068Z         cooldown (int): Number of epochs to wait before resuming
2025-08-14T21:17:23.7615591Z             normal operation after lr has been reduced. Default: 0.
2025-08-14T21:17:23.7616054Z         min_lr (float or list): A scalar or a list of scalars. A
2025-08-14T21:17:23.7616544Z             lower bound on the learning rate of all param groups
2025-08-14T21:17:23.7616980Z             or each group respectively. Default: 0.
2025-08-14T21:17:23.7617435Z         eps (float): Minimal decay applied to lr. If the difference
2025-08-14T21:17:23.7617965Z             between new and old lr is smaller than eps, the update is
2025-08-14T21:17:23.7618357Z             ignored. Default: 1e-8.
2025-08-14T21:17:23.7618621Z 
2025-08-14T21:17:23.7618713Z     Example:
2025-08-14T21:17:23.7618946Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7619404Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-08-14T21:17:23.7619910Z         >>> scheduler = ReduceLROnPlateau(optimizer, "min")
2025-08-14T21:17:23.7620352Z         >>> for epoch in range(10):
2025-08-14T21:17:23.7620650Z         >>>     train(...)
2025-08-14T21:17:23.7620968Z         >>>     val_loss = validate(...)
2025-08-14T21:17:23.7621335Z         >>> # Note that step should be called after validate()
2025-08-14T21:17:23.7621766Z         >>>     scheduler.step(val_loss)
2025-08-14T21:17:23.7621978Z 
2025-08-14T21:17:23.7622186Z     .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png
2025-08-14T21:17:23.7622632Z     
2025-08-14T21:17:23.7623216Z Original Error: IndentationError('unexpected indent', ('<source_block>', 8, 4, '    scheduler.step(val_loss)\n', 8, -1))
2025-08-14T21:17:23.7623742Z 
2025-08-14T21:17:23.7623900Z     scheduler.step(val_loss)
2025-08-14T21:17:23.7624328Z    ^
2025-08-14T21:17:23.7625027Z msg = Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430.
2025-08-14T21:17:23.7625969Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7626737Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR).
2025-08-14T21:17:23.7627343Z 
2025-08-14T21:17:23.7627829Z     The policy cycles the learning rate between two boundaries with a constant frequency,
2025-08-14T21:17:23.7628726Z     as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_.
2025-08-14T21:17:23.7629331Z     The distance between the two boundaries can be scaled on a per-iteration
2025-08-14T21:17:23.7629792Z     or per-cycle basis.
2025-08-14T21:17:23.7629970Z 
2025-08-14T21:17:23.7630215Z     Cyclical learning rate policy changes the learning rate after every batch.
2025-08-14T21:17:23.7630786Z     `step` should be called after a batch has been used for training.
2025-08-14T21:17:23.7631097Z 
2025-08-14T21:17:23.7631306Z     This class has three built-in policies, as put forth in the paper:
2025-08-14T21:17:23.7631742Z 
2025-08-14T21:17:23.7631951Z     * "triangular": A basic triangular cycle without amplitude scaling.
2025-08-14T21:17:23.7632578Z     * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle.
2025-08-14T21:17:23.7633417Z     * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}`
2025-08-14T21:17:23.7634032Z       at each cycle iteration.
2025-08-14T21:17:23.7634330Z 
2025-08-14T21:17:23.7634631Z     This implementation was adapted from the github repo: `bckenstler/CLR`_
2025-08-14T21:17:23.7635146Z 
2025-08-14T21:17:23.7635293Z     Args:
2025-08-14T21:17:23.7635627Z         optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:23.7636067Z         base_lr (float or list): Initial learning rate which is the
2025-08-14T21:17:23.7636537Z             lower boundary in the cycle for each parameter group.
2025-08-14T21:17:23.7637084Z         max_lr (float or list): Upper learning rate boundaries in the cycle
2025-08-14T21:17:23.7637528Z             for each parameter group. Functionally,
2025-08-14T21:17:23.7637934Z             it defines the cycle amplitude (max_lr - base_lr).
2025-08-14T21:17:23.7638333Z             The lr at any cycle is the sum of base_lr
2025-08-14T21:17:23.7638707Z             and some scaling of the amplitude; therefore
2025-08-14T21:17:23.7639102Z             max_lr may not actually be reached depending on
2025-08-14T21:17:23.7639465Z             scaling function.
2025-08-14T21:17:23.7639818Z         step_size_up (int): Number of training iterations in the
2025-08-14T21:17:23.7640223Z             increasing half of a cycle. Default: 2000
2025-08-14T21:17:23.7640699Z         step_size_down (int): Number of training iterations in the
2025-08-14T21:17:23.7641172Z             decreasing half of a cycle. If step_size_down is None,
2025-08-14T21:17:23.7641573Z             it is set to step_size_up. Default: None
2025-08-14T21:17:23.7641984Z         mode (str): One of {triangular, triangular2, exp_range}.
2025-08-14T21:17:23.7642415Z             Values correspond to policies detailed above.
2025-08-14T21:17:23.7642814Z             If scale_fn is not None, this argument is ignored.
2025-08-14T21:17:23.7643192Z             Default: 'triangular'
2025-08-14T21:17:23.7643560Z         gamma (float): Constant in 'exp_range' scaling function:
2025-08-14T21:17:23.7643951Z             gamma**(cycle iterations)
2025-08-14T21:17:23.7644242Z             Default: 1.0
2025-08-14T21:17:23.7644596Z         scale_fn (function): Custom scaling policy defined by a single
2025-08-14T21:17:23.7645020Z             argument lambda function, where
2025-08-14T21:17:23.7645347Z             0 <= scale_fn(x) <= 1 for all x >= 0.
2025-08-14T21:17:23.7645692Z             If specified, then 'mode' is ignored.
2025-08-14T21:17:23.7646168Z             Default: None
2025-08-14T21:17:23.7646457Z         scale_mode (str): {'cycle', 'iterations'}.
2025-08-14T21:17:23.7646839Z             Defines whether scale_fn is evaluated on
2025-08-14T21:17:23.7647228Z             cycle number or cycle iterations (training
2025-08-14T21:17:23.7647642Z             iterations since start of cycle).
2025-08-14T21:17:23.7647973Z             Default: 'cycle'
2025-08-14T21:17:23.7648354Z         cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-08-14T21:17:23.7648860Z             to learning rate between 'base_momentum' and 'max_momentum'.
2025-08-14T21:17:23.7649246Z             Default: True
2025-08-14T21:17:23.7649635Z         base_momentum (float or list): Lower momentum boundaries in the cycle
2025-08-14T21:17:23.7650180Z             for each parameter group. Note that momentum is cycled inversely
2025-08-14T21:17:23.7650657Z             to learning rate; at the peak of a cycle, momentum is
2025-08-14T21:17:23.7651084Z             'base_momentum' and learning rate is 'max_lr'.
2025-08-14T21:17:23.7651433Z             Default: 0.8
2025-08-14T21:17:23.7651812Z         max_momentum (float or list): Upper momentum boundaries in the cycle
2025-08-14T21:17:23.7652263Z             for each parameter group. Functionally,
2025-08-14T21:17:23.7652701Z             it defines the cycle amplitude (max_momentum - base_momentum).
2025-08-14T21:17:23.7653237Z             The momentum at any cycle is the difference of max_momentum
2025-08-14T21:17:23.7653701Z             and some scaling of the amplitude; therefore
2025-08-14T21:17:23.7654129Z             base_momentum may not actually be reached depending on
2025-08-14T21:17:23.7654598Z             scaling function. Note that momentum is cycled inversely
2025-08-14T21:17:23.7655106Z             to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-08-14T21:17:23.7655538Z             and learning rate is 'base_lr'
2025-08-14T21:17:23.7655858Z             Default: 0.9
2025-08-14T21:17:23.7656250Z         last_epoch (int): The index of the last batch. This parameter is used when
2025-08-14T21:17:23.7656796Z             resuming a training job. Since `step()` should be invoked after each
2025-08-14T21:17:23.7657344Z             batch instead of after each epoch, this number represents the total
2025-08-14T21:17:23.7657905Z             number of *batches* computed, not the total number of epochs computed.
2025-08-14T21:17:23.7658440Z             When last_epoch=-1, the schedule is started from the beginning.
2025-08-14T21:17:23.7658834Z             Default: -1
2025-08-14T21:17:23.7659002Z 
2025-08-14T21:17:23.7659087Z     Example:
2025-08-14T21:17:23.7659319Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7659718Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-08-14T21:17:23.7660218Z         >>> scheduler = torch.optim.lr_scheduler.CyclicLR(
2025-08-14T21:17:23.7660584Z         ...     optimizer,
2025-08-14T21:17:23.7660845Z         ...     base_lr=0.01,
2025-08-14T21:17:23.7661184Z         ...     max_lr=0.1,
2025-08-14T21:17:23.7661460Z         ...     step_size_up=10,
2025-08-14T21:17:23.7661732Z         ... )
2025-08-14T21:17:23.7662019Z         >>> data_loader = torch.utils.data.DataLoader(...)
2025-08-14T21:17:23.7662393Z         >>> for epoch in range(10):
2025-08-14T21:17:23.7662708Z         >>>     for batch in data_loader:
2025-08-14T21:17:23.7663019Z         >>>         train_batch(...)
2025-08-14T21:17:23.7663327Z         >>>         scheduler.step()
2025-08-14T21:17:23.7663523Z 
2025-08-14T21:17:23.7663700Z     .. image:: ../scripts/lr_scheduler_images/CyclicLR.png
2025-08-14T21:17:23.7663963Z 
2025-08-14T21:17:23.7664277Z     .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186
2025-08-14T21:17:23.7664866Z     .. _bckenstler/CLR: https://github.com/bckenstler/CLR
2025-08-14T21:17:23.7665221Z     
2025-08-14T21:17:23.7665586Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.7666042Z 
2025-08-14T21:17:23.7666734Z msg = Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1722.
2025-08-14T21:17:23.7667736Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7668361Z Set the learning rate of each parameter group using a cosine annealing schedule.
2025-08-14T21:17:23.7668744Z 
2025-08-14T21:17:23.7668927Z     The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}`
2025-08-14T21:17:23.7669466Z     is the number of epochs since the last restart and :math:`T_{i}` is the number
2025-08-14T21:17:23.7669961Z     of epochs between two warm restarts in SGDR:
2025-08-14T21:17:23.7670204Z 
2025-08-14T21:17:23.7670292Z     .. math::
2025-08-14T21:17:23.7670607Z         \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 +
2025-08-14T21:17:23.7671056Z         \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right)
2025-08-14T21:17:23.7671307Z 
2025-08-14T21:17:23.7671550Z     When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`.
2025-08-14T21:17:23.7672028Z     When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`.
2025-08-14T21:17:23.7672344Z 
2025-08-14T21:17:23.7672449Z     It has been proposed in
2025-08-14T21:17:23.7672808Z     `SGDR: Stochastic Gradient Descent with Warm Restarts`_.
2025-08-14T21:17:23.7673148Z 
2025-08-14T21:17:23.7673233Z     Args:
2025-08-14T21:17:23.7673528Z         optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:23.7673942Z         T_0 (int): Number of iterations until the first restart.
2025-08-14T21:17:23.7674492Z         T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1.
2025-08-14T21:17:23.7675090Z         eta_min (float, optional): Minimum learning rate. Default: 0.
2025-08-14T21:17:23.7675617Z         last_epoch (int, optional): The index of the last epoch. Default: -1.
2025-08-14T21:17:23.7675945Z 
2025-08-14T21:17:23.7676132Z     .. _SGDR\: Stochastic Gradient Descent with Warm Restarts:
2025-08-14T21:17:23.7676527Z         https://arxiv.org/abs/1608.03983
2025-08-14T21:17:23.7676760Z 
2025-08-14T21:17:23.7676846Z     Example:
2025-08-14T21:17:23.7677077Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7677436Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05)
2025-08-14T21:17:23.7677966Z         >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts(
2025-08-14T21:17:23.7678422Z         ...     optimizer, T_0=20
2025-08-14T21:17:23.7678701Z         ... )
2025-08-14T21:17:23.7678924Z         >>> for epoch in range(100):
2025-08-14T21:17:23.7679221Z         >>>     train(...)
2025-08-14T21:17:23.7679487Z         >>>     validate(...)
2025-08-14T21:17:23.7679765Z         >>>     scheduler.step()
2025-08-14T21:17:23.7679962Z 
2025-08-14T21:17:23.7680195Z     .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png
2025-08-14T21:17:23.7680632Z     
2025-08-14T21:17:23.7680988Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.7681364Z 
2025-08-14T21:17:23.7681888Z msg = Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1872.
2025-08-14T21:17:23.7682789Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7683472Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy.
2025-08-14T21:17:23.7683891Z 
2025-08-14T21:17:23.7684185Z     The 1cycle policy anneals the learning rate from an initial learning rate to some maximum
2025-08-14T21:17:23.7684891Z     learning rate and then from that maximum learning rate to some minimum learning rate much
2025-08-14T21:17:23.7685417Z     lower than the initial learning rate.
2025-08-14T21:17:23.7685867Z     This policy was initially described in the paper `Super-Convergence:
2025-08-14T21:17:23.7686486Z     Very Fast Training of Neural Networks Using Large Learning Rates`_.
2025-08-14T21:17:23.7686828Z 
2025-08-14T21:17:23.7687070Z     The 1cycle learning rate policy changes the learning rate after every batch.
2025-08-14T21:17:23.7687708Z     `step` should be called after a batch has been used for training.
2025-08-14T21:17:23.7688017Z 
2025-08-14T21:17:23.7688140Z     This scheduler is not chainable.
2025-08-14T21:17:23.7688346Z 
2025-08-14T21:17:23.7688589Z     Note also that the total number of steps in the cycle can be determined in one
2025-08-14T21:17:23.7689090Z     of two ways (listed in order of precedence):
2025-08-14T21:17:23.7689332Z 
2025-08-14T21:17:23.7689495Z     #. A value for total_steps is explicitly provided.
2025-08-14T21:17:23.7689933Z     #. A number of epochs (epochs) and a number of steps per epoch
2025-08-14T21:17:23.7690352Z        (steps_per_epoch) are provided.
2025-08-14T21:17:23.7690734Z        In this case, the number of total steps is inferred by
2025-08-14T21:17:23.7691139Z        total_steps = epochs * steps_per_epoch
2025-08-14T21:17:23.7691365Z 
2025-08-14T21:17:23.7691601Z     You must either provide a value for total_steps or provide a value for both
2025-08-14T21:17:23.7692066Z     epochs and steps_per_epoch.
2025-08-14T21:17:23.7692254Z 
2025-08-14T21:17:23.7692567Z     The default behaviour of this scheduler follows the fastai implementation of 1cycle, which
2025-08-14T21:17:23.7693271Z     claims that "unpublished work has shown even better results by using only two phases". To
2025-08-14T21:17:23.7694000Z     mimic the behaviour of the original paper instead, set ``three_phase=True``.
2025-08-14T21:17:23.7694369Z 
2025-08-14T21:17:23.7694454Z     Args:
2025-08-14T21:17:23.7694718Z         optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:23.7695155Z         max_lr (float or list): Upper learning rate boundaries in the cycle
2025-08-14T21:17:23.7695590Z             for each parameter group.
2025-08-14T21:17:23.7696015Z         total_steps (int): The total number of steps in the cycle. Note that
2025-08-14T21:17:23.7696540Z             if a value is not provided here, then it must be inferred by providing
2025-08-14T21:17:23.7697003Z             a value for epochs and steps_per_epoch.
2025-08-14T21:17:23.7697346Z             Default: None
2025-08-14T21:17:23.7697720Z         epochs (int): The number of epochs to train for. This is used along
2025-08-14T21:17:23.7698270Z             with steps_per_epoch in order to infer the total number of steps in the cycle
2025-08-14T21:17:23.7698774Z             if a value for total_steps is not provided.
2025-08-14T21:17:23.7699121Z             Default: None
2025-08-14T21:17:23.7699504Z         steps_per_epoch (int): The number of steps per epoch to train for. This is
2025-08-14T21:17:23.7700078Z             used along with epochs in order to infer the total number of steps in the
2025-08-14T21:17:23.7700578Z             cycle if a value for total_steps is not provided.
2025-08-14T21:17:23.7700937Z             Default: None
2025-08-14T21:17:23.7701330Z         pct_start (float): The percentage of the cycle (in number of steps) spent
2025-08-14T21:17:23.7701801Z             increasing the learning rate.
2025-08-14T21:17:23.7702116Z             Default: 0.3
2025-08-14T21:17:23.7702391Z         anneal_strategy (str): {'cos', 'linear'}
2025-08-14T21:17:23.7702648Z             Specifies the annealing strategy: "cos" for cosine annealing, "linear" for
2025-08-14T21:17:23.7702749Z             linear annealing.
2025-08-14T21:17:23.7702845Z             Default: 'cos'
2025-08-14T21:17:23.7703054Z         cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-08-14T21:17:23.7703235Z             to learning rate between 'base_momentum' and 'max_momentum'.
2025-08-14T21:17:23.7703338Z             Default: True
2025-08-14T21:17:23.7703554Z         base_momentum (float or list): Lower momentum boundaries in the cycle
2025-08-14T21:17:23.7703755Z             for each parameter group. Note that momentum is cycled inversely
2025-08-14T21:17:23.7703993Z             to learning rate; at the peak of a cycle, momentum is
2025-08-14T21:17:23.7704135Z             'base_momentum' and learning rate is 'max_lr'.
2025-08-14T21:17:23.7704229Z             Default: 0.85
2025-08-14T21:17:23.7704451Z         max_momentum (float or list): Upper momentum boundaries in the cycle
2025-08-14T21:17:23.7704578Z             for each parameter group. Functionally,
2025-08-14T21:17:23.7704776Z             it defines the cycle amplitude (max_momentum - base_momentum).
2025-08-14T21:17:23.7704918Z             Note that momentum is cycled inversely
2025-08-14T21:17:23.7705124Z             to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-08-14T21:17:23.7705248Z             and learning rate is 'base_lr'
2025-08-14T21:17:23.7705344Z             Default: 0.95
2025-08-14T21:17:23.7705529Z         div_factor (float): Determines the initial learning rate via
2025-08-14T21:17:23.7705652Z             initial_lr = max_lr/div_factor
2025-08-14T21:17:23.7705743Z             Default: 25
2025-08-14T21:17:23.7705950Z         final_div_factor (float): Determines the minimum learning rate via
2025-08-14T21:17:23.7706078Z             min_lr = initial_lr/final_div_factor
2025-08-14T21:17:23.7706167Z             Default: 1e4
2025-08-14T21:17:23.7706421Z         three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the
2025-08-14T21:17:23.7706673Z             learning rate according to 'final_div_factor' instead of modifying the second
2025-08-14T21:17:23.7707056Z             phase (the first two phases will be symmetrical about the step indicated by
2025-08-14T21:17:23.7707161Z             'pct_start').
2025-08-14T21:17:23.7707377Z         last_epoch (int): The index of the last batch. This parameter is used when
2025-08-14T21:17:23.7707592Z             resuming a training job. Since `step()` should be invoked after each
2025-08-14T21:17:23.7707816Z             batch instead of after each epoch, this number represents the total
2025-08-14T21:17:23.7708039Z             number of *batches* computed, not the total number of epochs computed.
2025-08-14T21:17:23.7708248Z             When last_epoch=-1, the schedule is started from the beginning.
2025-08-14T21:17:23.7708341Z             Default: -1
2025-08-14T21:17:23.7708345Z 
2025-08-14T21:17:23.7708432Z     Example:
2025-08-14T21:17:23.7708557Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7708708Z         >>> data_loader = torch.utils.data.DataLoader(...)
2025-08-14T21:17:23.7708942Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
2025-08-14T21:17:23.7709326Z         >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(
2025-08-14T21:17:23.7709541Z         ...     optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10
2025-08-14T21:17:23.7709640Z         ... )
2025-08-14T21:17:23.7709745Z         >>> for epoch in range(10):
2025-08-14T21:17:23.7709853Z         >>>     for batch in data_loader:
2025-08-14T21:17:23.7709966Z         >>>         train_batch(...)
2025-08-14T21:17:23.7710073Z         >>>         optimizer.step()
2025-08-14T21:17:23.7710173Z         >>>         scheduler.step()
2025-08-14T21:17:23.7710178Z 
2025-08-14T21:17:23.7710357Z     .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png
2025-08-14T21:17:23.7710362Z 
2025-08-14T21:17:23.7710651Z     .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates:
2025-08-14T21:17:23.7710786Z         https://arxiv.org/abs/1708.07120
2025-08-14T21:17:23.7710871Z     
2025-08-14T21:17:23.7711122Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.7711126Z 
2025-08-14T21:17:23.7788173Z msg = Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867.
2025-08-14T21:17:23.7788439Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7788557Z Load the optimizer state.
2025-08-14T21:17:23.7788562Z 
2025-08-14T21:17:23.7788829Z         Args:
2025-08-14T21:17:23.7789029Z             state_dict (dict): optimizer state. Should be an object returned
2025-08-14T21:17:23.7789164Z                 from a call to :meth:`state_dict`.
2025-08-14T21:17:23.7789168Z 
2025-08-14T21:17:23.7789263Z         .. warning::
2025-08-14T21:17:23.7789600Z             Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`,
2025-08-14T21:17:23.7789827Z             as calling it beforehand will overwrite the loaded learning rates.
2025-08-14T21:17:23.7789834Z 
2025-08-14T21:17:23.7789922Z         .. note::
2025-08-14T21:17:23.7790226Z             The names of the parameters (if they exist under the "param_names" key of each param group
2025-08-14T21:17:23.7790402Z             in :meth:`state_dict`) will not affect the loading process.
2025-08-14T21:17:23.7790726Z             To use the parameters' names for custom cases (such as when the parameters in the loaded state dict
2025-08-14T21:17:23.7790918Z             differ from those initialized in the optimizer),
2025-08-14T21:17:23.7791224Z             a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict
2025-08-14T21:17:23.7791332Z             accordingly.
2025-08-14T21:17:23.7791695Z             If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override
2025-08-14T21:17:23.7792013Z             the current names, if present, in the optimizer state. If they do not exist in loaded state dict,
2025-08-14T21:17:23.7792283Z             the optimizer ``param_names`` will remain unchanged.
2025-08-14T21:17:23.7792288Z 
2025-08-14T21:17:23.7792377Z         Example:
2025-08-14T21:17:23.7792491Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:23.7792613Z             >>> model = torch.nn.Linear(10, 10)
2025-08-14T21:17:23.7792776Z             >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4)
2025-08-14T21:17:23.7792948Z             >>> scheduler1 = torch.optim.lr_scheduler.LinearLR(
2025-08-14T21:17:23.7793041Z             ...     optim,
2025-08-14T21:17:23.7793144Z             ...     start_factor=0.1,
2025-08-14T21:17:23.7793252Z             ...     end_factor=1,
2025-08-14T21:17:23.7793346Z             ...     total_iters=20,
2025-08-14T21:17:23.7793441Z             ... )
2025-08-14T21:17:23.7793629Z             >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR(
2025-08-14T21:17:23.7793720Z             ...     optim,
2025-08-14T21:17:23.7793824Z             ...     T_max=80,
2025-08-14T21:17:23.7793917Z             ...     eta_min=3e-5,
2025-08-14T21:17:23.7793997Z             ... )
2025-08-14T21:17:23.7794149Z             >>> lr = torch.optim.lr_scheduler.SequentialLR(
2025-08-14T21:17:23.7794238Z             ...     optim,
2025-08-14T21:17:23.7794368Z             ...     schedulers=[scheduler1, scheduler2],
2025-08-14T21:17:23.7794476Z             ...     milestones=[20],
2025-08-14T21:17:23.7794558Z             ... )
2025-08-14T21:17:23.7794707Z             >>> lr.load_state_dict(torch.load("./save_seq.pt"))
2025-08-14T21:17:23.7794923Z             >>> # now load the optimizer checkpoint after loading the LRScheduler
2025-08-14T21:17:23.7795089Z             >>> optim.load_state_dict(torch.load("./save_optim.pt"))
2025-08-14T21:17:23.7795094Z 
2025-08-14T21:17:23.7795188Z         
2025-08-14T21:17:23.7795437Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.7795443Z 
2025-08-14T21:17:23.7999358Z msg = Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120.
2025-08-14T21:17:23.7999632Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.7999996Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA).
2025-08-14T21:17:23.8000002Z 
2025-08-14T21:17:23.8000257Z     Stochastic Weight Averaging was proposed in `Averaging Weights Leads to
2025-08-14T21:17:23.8000636Z     Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii
2025-08-14T21:17:23.8000870Z     Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson
2025-08-14T21:17:23.8000957Z     (UAI 2018).
2025-08-14T21:17:23.8000961Z 
2025-08-14T21:17:23.8001174Z     Exponential Moving Average is a variation of `Polyak averaging`_,
2025-08-14T21:17:23.8001424Z     but using exponential weights instead of equal weights across iterations.
2025-08-14T21:17:23.8001434Z 
2025-08-14T21:17:23.8001670Z     AveragedModel class creates a copy of the provided module :attr:`model`
2025-08-14T21:17:23.8001906Z     on the device :attr:`device` and allows to compute running averages of the
2025-08-14T21:17:23.8002015Z     parameters of the :attr:`model`.
2025-08-14T21:17:23.8002020Z 
2025-08-14T21:17:23.8002102Z     Args:
2025-08-14T21:17:23.8002269Z         model (torch.nn.Module): model to use with SWA/EMA
2025-08-14T21:17:23.8002505Z         device (torch.device, optional): if provided, the averaged model will be
2025-08-14T21:17:23.8002615Z             stored on the :attr:`device`
2025-08-14T21:17:23.8002827Z         avg_fn (function, optional): the averaging function used to update
2025-08-14T21:17:23.8003025Z             parameters; the function must take in the current value of the
2025-08-14T21:17:23.8003255Z             :class:`AveragedModel` parameter, the current value of :attr:`model`
2025-08-14T21:17:23.8003493Z             parameter, and the number of models already averaged; if None,
2025-08-14T21:17:23.8003693Z             an equally weighted average is used (default: None)
2025-08-14T21:17:23.8003929Z         multi_avg_fn (function, optional): the averaging function used to update
2025-08-14T21:17:23.8004162Z             parameters inplace; the function must take in the current values of the
2025-08-14T21:17:23.8004426Z             :class:`AveragedModel` parameters as a list, the current values of :attr:`model`
2025-08-14T21:17:23.8004668Z             parameters as a list, and the number of models already averaged; if None,
2025-08-14T21:17:23.8004825Z             an equally weighted average is used (default: None)
2025-08-14T21:17:23.8005041Z         use_buffers (bool): if ``True``, it will compute running averages for
2025-08-14T21:17:23.8005263Z             both the parameters and the buffers of the model. (default: ``False``)
2025-08-14T21:17:23.8005267Z 
2025-08-14T21:17:23.8005353Z     Example:
2025-08-14T21:17:23.8005499Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:23.8005628Z         >>> loader, optimizer, model, loss_fn = ...
2025-08-14T21:17:23.8005796Z         >>> swa_model = torch.optim.swa_utils.AveragedModel(model)
2025-08-14T21:17:23.8006030Z         >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer,
2025-08-14T21:17:23.8006162Z         >>>                                     T_max=300)
2025-08-14T21:17:23.8006274Z         >>> swa_start = 160
2025-08-14T21:17:23.8006414Z         >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05)
2025-08-14T21:17:23.8006519Z         >>> for i in range(300):
2025-08-14T21:17:23.8006645Z         >>>      for input, target in loader:
2025-08-14T21:17:23.8006754Z         >>>          optimizer.zero_grad()
2025-08-14T21:17:23.8006897Z         >>>          loss_fn(model(input), target).backward()
2025-08-14T21:17:23.8007000Z         >>>          optimizer.step()
2025-08-14T21:17:23.8007098Z         >>>      if i > swa_start:
2025-08-14T21:17:23.8007240Z         >>>          swa_model.update_parameters(model)
2025-08-14T21:17:23.8007346Z         >>>          swa_scheduler.step()
2025-08-14T21:17:23.8007430Z         >>>      else:
2025-08-14T21:17:23.8007542Z         >>>          scheduler.step()
2025-08-14T21:17:23.8007623Z         >>>
2025-08-14T21:17:23.8007773Z         >>> # Update bn statistics for the swa_model at the end
2025-08-14T21:17:23.8007945Z         >>> torch.optim.swa_utils.update_bn(loader, swa_model)
2025-08-14T21:17:23.8007949Z 
2025-08-14T21:17:23.8008318Z     You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters.
2025-08-14T21:17:23.8008585Z     If no averaging function is provided, the default is to compute
2025-08-14T21:17:23.8008731Z     equally-weighted average of the weights (SWA).
2025-08-14T21:17:23.8008736Z 
2025-08-14T21:17:23.8008822Z     Example:
2025-08-14T21:17:23.8008963Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:23.8009370Z         >>> # Compute exponential moving averages of the weights and buffers
2025-08-14T21:17:23.8009612Z         >>> ema_model = torch.optim.swa_utils.AveragedModel(model,
2025-08-14T21:17:23.8009982Z         >>>             torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True)
2025-08-14T21:17:23.8009990Z 
2025-08-14T21:17:23.8010130Z     .. note::
2025-08-14T21:17:23.8010365Z         When using SWA/EMA with models containing Batch Normalization you may
2025-08-14T21:17:23.8010568Z         need to update the activation statistics for Batch Normalization.
2025-08-14T21:17:23.8010805Z         This can be done either by using the :meth:`torch.optim.swa_utils.update_bn`
2025-08-14T21:17:23.8011040Z         or by setting :attr:`use_buffers` to `True`. The first approach updates the
2025-08-14T21:17:23.8011279Z         statistics in a post-training step by passing data through the model. The
2025-08-14T21:17:23.8011526Z         second does it during the parameter update phase by averaging all buffers.
2025-08-14T21:17:23.8011849Z         Empirical evidence has shown that updating the statistics in normalization
2025-08-14T21:17:23.8012123Z         layers increases accuracy, but you may wish to empirically test which
2025-08-14T21:17:23.8012293Z         approach yields the best results in your problem.
2025-08-14T21:17:23.8012297Z 
2025-08-14T21:17:23.8012386Z     .. note::
2025-08-14T21:17:23.8012638Z         :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model.
2025-08-14T21:17:23.8012659Z 
2025-08-14T21:17:23.8012742Z     .. note::
2025-08-14T21:17:23.8012943Z         When :meth:`update_parameters` is called for the first time (i.e.
2025-08-14T21:17:23.8013140Z         :attr:`n_averaged` is `0`) the parameters of `model` are copied
2025-08-14T21:17:23.8013339Z         to the parameters of :class:`AveragedModel`. For every subsequent
2025-08-14T21:17:23.8013525Z         call of :meth:`update_parameters` the function `avg_fn` is used
2025-08-14T21:17:23.8013643Z         to update the parameters.
2025-08-14T21:17:23.8013650Z 
2025-08-14T21:17:23.8013873Z     .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-08-14T21:17:23.8014015Z         https://arxiv.org/abs/1803.05407
2025-08-14T21:17:23.8014249Z     .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should
2025-08-14T21:17:23.8014335Z         Average:
2025-08-14T21:17:23.8014459Z         https://arxiv.org/abs/1806.05594
2025-08-14T21:17:23.8014656Z     .. _SWALP: Stochastic Weight Averaging in Low-Precision Training:
2025-08-14T21:17:23.8014771Z         https://arxiv.org/abs/1904.11943
2025-08-14T21:17:23.8015003Z     .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That
2025-08-14T21:17:23.8015102Z         Generalizes Well:
2025-08-14T21:17:23.8015212Z         https://arxiv.org/abs/2001.02312
2025-08-14T21:17:23.8015320Z     .. _Polyak averaging:
2025-08-14T21:17:23.8015486Z         https://paperswithcode.com/method/polyak-averaging
2025-08-14T21:17:23.8015579Z     
2025-08-14T21:17:23.8015830Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.8015836Z 
2025-08-14T21:17:23.8016333Z msg = Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375.
2025-08-14T21:17:23.8016602Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:23.8016813Z Anneals the learning rate in each parameter group to a fixed value.
2025-08-14T21:17:23.8016818Z 
2025-08-14T21:17:23.8017144Z     This learning rate scheduler is meant to be used with Stochastic Weight
2025-08-14T21:17:23.8017356Z     Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`).
2025-08-14T21:17:23.8017361Z 
2025-08-14T21:17:23.8017444Z     Args:
2025-08-14T21:17:23.8017627Z         optimizer (torch.optim.Optimizer): wrapped optimizer
2025-08-14T21:17:23.8017830Z         swa_lrs (float or list): the learning rate value for all param groups
2025-08-14T21:17:23.8017974Z             together or separately for each group.
2025-08-14T21:17:23.8018177Z         annealing_epochs (int): number of epochs in the annealing phase
2025-08-14T21:17:23.8018273Z             (default: 10)
2025-08-14T21:17:23.8018501Z         annealing_strategy (str): "cos" or "linear"; specifies the annealing
2025-08-14T21:17:23.8018705Z             strategy: "cos" for cosine annealing, "linear" for linear annealing
2025-08-14T21:17:23.8018803Z             (default: "cos")
2025-08-14T21:17:23.8018996Z         last_epoch (int): the index of the last epoch (default: -1)
2025-08-14T21:17:23.8019005Z 
2025-08-14T21:17:23.8019181Z     The :class:`SWALR` scheduler can be used together with other
2025-08-14T21:17:23.8019408Z     schedulers to switch to a constant learning rate late in the training
2025-08-14T21:17:23.8019508Z     as in the example below.
2025-08-14T21:17:23.8019513Z 
2025-08-14T21:17:23.8019595Z     Example:
2025-08-14T21:17:23.8019736Z         >>> # xdoctest: +SKIP("Undefined variables")
2025-08-14T21:17:23.8019897Z         >>> loader, optimizer, model = ...
2025-08-14T21:17:23.8020039Z         >>> lr_lambda = lambda epoch: 0.9
2025-08-14T21:17:23.8020267Z         >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer,
2025-08-14T21:17:23.8020367Z         >>>        lr_lambda=lr_lambda)
2025-08-14T21:17:23.8020549Z         >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer,
2025-08-14T21:17:23.8020724Z         >>>        anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05)
2025-08-14T21:17:23.8020818Z         >>> swa_start = 160
2025-08-14T21:17:23.8020936Z         >>> for i in range(300):
2025-08-14T21:17:23.8021047Z         >>>      for input, target in loader:
2025-08-14T21:17:23.8021156Z         >>>          optimizer.zero_grad()
2025-08-14T21:17:23.8021300Z         >>>          loss_fn(model(input), target).backward()
2025-08-14T21:17:23.8021406Z         >>>          optimizer.step()
2025-08-14T21:17:23.8021503Z         >>>      if i > swa_start:
2025-08-14T21:17:23.8021624Z         >>>          swa_scheduler.step()
2025-08-14T21:17:23.8021714Z         >>>      else:
2025-08-14T21:17:23.8021830Z         >>>          scheduler.step()
2025-08-14T21:17:23.8021835Z 
2025-08-14T21:17:23.8022058Z     .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-08-14T21:17:23.8022173Z         https://arxiv.org/abs/1803.05407
2025-08-14T21:17:23.8022267Z     
2025-08-14T21:17:23.8022518Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:23.8022522Z 
2025-08-14T21:17:24.2986511Z msg = Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331.
2025-08-14T21:17:24.2987517Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:24.2988054Z Asserts that ``actual`` and ``expected`` are close.
2025-08-14T21:17:24.2988333Z 
2025-08-14T21:17:24.2988696Z     If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if
2025-08-14T21:17:24.2989191Z 
2025-08-14T21:17:24.2989309Z     .. math::
2025-08-14T21:17:24.2989438Z 
2025-08-14T21:17:24.2989807Z         \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert
2025-08-14T21:17:24.2990304Z 
2025-08-14T21:17:24.2990644Z     Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are
2025-08-14T21:17:24.2991309Z     only considered equal to each other if ``equal_nan`` is ``True``.
2025-08-14T21:17:24.2991943Z 
2025-08-14T21:17:24.2992158Z     In addition, they are only considered close if they have the same
2025-08-14T21:17:24.2992476Z 
2025-08-14T21:17:24.2992666Z     - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``),
2025-08-14T21:17:24.2993105Z     - ``dtype`` (if ``check_dtype`` is ``True``),
2025-08-14T21:17:24.2993488Z     - ``layout`` (if ``check_layout`` is ``True``), and
2025-08-14T21:17:24.2993873Z     - stride (if ``check_stride`` is ``True``).
2025-08-14T21:17:24.2994108Z 
2025-08-14T21:17:24.2994404Z     If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed.
2025-08-14T21:17:24.2994828Z 
2025-08-14T21:17:24.2995185Z     If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are
2025-08-14T21:17:24.2996037Z     checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR,
2025-08-14T21:17:24.2996758Z     or ``ccol_indices``  and ``row_indices`` for CSC and BSC layouts, respectively,
2025-08-14T21:17:24.2997480Z     are always checked for equality whereas the values are checked for closeness according to the definition above.
2025-08-14T21:17:24.2997992Z 
2025-08-14T21:17:24.2998273Z     If ``actual`` and ``expected`` are quantized, they are considered close if they have the same
2025-08-14T21:17:24.2999028Z     :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the
2025-08-14T21:17:24.2999760Z     definition above.
2025-08-14T21:17:24.2999920Z 
2025-08-14T21:17:24.3000240Z     ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which
2025-08-14T21:17:24.3001047Z     :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types
2025-08-14T21:17:24.3001897Z     have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s
2025-08-14T21:17:24.3002764Z     or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all
2025-08-14T21:17:24.3003492Z     their elements are considered close according to the above definition.
2025-08-14T21:17:24.3003837Z 
2025-08-14T21:17:24.3003938Z     .. note::
2025-08-14T21:17:24.3004065Z 
2025-08-14T21:17:24.3004395Z         Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e.
2025-08-14T21:17:24.3005170Z         :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus,
2025-08-14T21:17:24.3005887Z         Python scalars of different types can be checked, but require ``check_dtype=False``.
2025-08-14T21:17:24.3006279Z 
2025-08-14T21:17:24.3006376Z     Args:
2025-08-14T21:17:24.3006595Z         actual (Any): Actual input.
2025-08-14T21:17:24.3006915Z         expected (Any): Expected input.
2025-08-14T21:17:24.3007499Z         allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types
2025-08-14T21:17:24.3008122Z             are allowed. Otherwise type equality is required.
2025-08-14T21:17:24.3008761Z         rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default
2025-08-14T21:17:24.3009692Z             values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-08-14T21:17:24.3010439Z         atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default
2025-08-14T21:17:24.3011172Z             values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-08-14T21:17:24.3011799Z         equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal.
2025-08-14T21:17:24.3012452Z         check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same
2025-08-14T21:17:24.3013197Z             :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different
2025-08-14T21:17:24.3013801Z             :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared.
2025-08-14T21:17:24.3014506Z         check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this
2025-08-14T21:17:24.3015318Z             check is disabled, tensors with different ``dtype``'s are promoted  to a common ``dtype`` (according to
2025-08-14T21:17:24.3015932Z             :func:`torch.promote_types`) before being compared.
2025-08-14T21:17:24.3016571Z         check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this
2025-08-14T21:17:24.3017381Z             check is disabled, tensors with different ``layout``'s are converted to strided tensors before being
2025-08-14T21:17:24.3017925Z             compared.
2025-08-14T21:17:24.3018440Z         check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride.
2025-08-14T21:17:24.3019274Z         msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during
2025-08-14T21:17:24.3020104Z             the comparison. Can also passed as callable in which case it will be called with the generated message and
2025-08-14T21:17:24.3020700Z             should return the new message.
2025-08-14T21:17:24.3020965Z 
2025-08-14T21:17:24.3021050Z     Raises:
2025-08-14T21:17:24.3021455Z         ValueError: If no :class:`torch.Tensor` can be constructed from an input.
2025-08-14T21:17:24.3021971Z         ValueError: If only ``rtol`` or ``atol`` is specified.
2025-08-14T21:17:24.3022566Z         AssertionError: If corresponding inputs are not Python scalars and are not directly related.
2025-08-14T21:17:24.3023380Z         AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have
2025-08-14T21:17:24.3023959Z             different types.
2025-08-14T21:17:24.3024510Z         AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match.
2025-08-14T21:17:24.3025346Z         AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match.
2025-08-14T21:17:24.3026149Z         AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`.
2025-08-14T21:17:24.3026887Z         AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same
2025-08-14T21:17:24.3027421Z             :attr:`~torch.Tensor.layout`.
2025-08-14T21:17:24.3027855Z         AssertionError: If only one of corresponding tensors is quantized.
2025-08-14T21:17:24.3028581Z         AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s.
2025-08-14T21:17:24.3029381Z         AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same
2025-08-14T21:17:24.3029904Z             :attr:`~torch.Tensor.device`.
2025-08-14T21:17:24.3030464Z         AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``.
2025-08-14T21:17:24.3031282Z         AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride.
2025-08-14T21:17:24.3032212Z         AssertionError: If the values of corresponding tensors are not close according to the definition above.
2025-08-14T21:17:24.3032699Z 
2025-08-14T21:17:24.3033064Z     The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching
2025-08-14T21:17:24.3033703Z     ``dtype``'s, the maximum of both tolerances is used.
2025-08-14T21:17:24.3033974Z 
2025-08-14T21:17:24.3034103Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3034478Z     | ``dtype``                 | ``rtol``   | ``atol`` |
2025-08-14T21:17:24.3034830Z     +===========================+============+==========+
2025-08-14T21:17:24.3035263Z     | :attr:`~torch.float16`    | ``1e-3``   | ``1e-5`` |
2025-08-14T21:17:24.3035627Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3036007Z     | :attr:`~torch.bfloat16`   | ``1.6e-2`` | ``1e-5`` |
2025-08-14T21:17:24.3036387Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3036749Z     | :attr:`~torch.float32`    | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3037126Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3037505Z     | :attr:`~torch.float64`    | ``1e-7``   | ``1e-7`` |
2025-08-14T21:17:24.3037877Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3038243Z     | :attr:`~torch.complex32`  | ``1e-3``   | ``1e-5`` |
2025-08-14T21:17:24.3038623Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3039001Z     | :attr:`~torch.complex64`  | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3039368Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3039749Z     | :attr:`~torch.complex128` | ``1e-7``   | ``1e-7`` |
2025-08-14T21:17:24.3040127Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3040507Z     | :attr:`~torch.quint8`     | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3040868Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3041242Z     | :attr:`~torch.quint2x4`   | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3041642Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3042035Z     | :attr:`~torch.quint4x2`   | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3042405Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3042776Z     | :attr:`~torch.qint8`      | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3043129Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3043494Z     | :attr:`~torch.qint32`     | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:24.3043864Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3044217Z     | other                     | ``0.0``    | ``0.0``  |
2025-08-14T21:17:24.3044559Z     +---------------------------+------------+----------+
2025-08-14T21:17:24.3044802Z 
2025-08-14T21:17:24.3044896Z     .. note::
2025-08-14T21:17:24.3045021Z 
2025-08-14T21:17:24.3045413Z         :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged
2025-08-14T21:17:24.3046270Z         to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might
2025-08-14T21:17:24.3046985Z         define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default:
2025-08-14T21:17:24.3047370Z 
2025-08-14T21:17:24.3047469Z         >>> import functools
2025-08-14T21:17:24.3047906Z         >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0)
2025-08-14T21:17:24.3048383Z         >>> assert_equal(1e-9, 1e-10)
2025-08-14T21:17:24.3048716Z         Traceback (most recent call last):
2025-08-14T21:17:24.3049031Z         ...
2025-08-14T21:17:24.3049269Z         AssertionError: Scalars are not equal!
2025-08-14T21:17:24.3049596Z         <BLANKLINE>
2025-08-14T21:17:24.3049852Z         Expected 1e-10 but got 1e-09.
2025-08-14T21:17:24.3050187Z         Absolute difference: 9.000000000000001e-10
2025-08-14T21:17:24.3050520Z         Relative difference: 9.0
2025-08-14T21:17:24.3050725Z 
2025-08-14T21:17:24.3050812Z     Examples:
2025-08-14T21:17:24.3051056Z         >>> # tensor to tensor comparison
2025-08-14T21:17:24.3051400Z         >>> expected = torch.tensor([1e0, 1e-1, 1e-2])
2025-08-14T21:17:24.3051781Z         >>> actual = torch.acos(torch.cos(expected))
2025-08-14T21:17:24.3052167Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3052419Z 
2025-08-14T21:17:24.3052539Z         >>> # scalar to scalar comparison
2025-08-14T21:17:24.3052839Z         >>> import math
2025-08-14T21:17:24.3053173Z         >>> expected = math.sqrt(2.0)
2025-08-14T21:17:24.3053493Z         >>> actual = 2.0 / math.sqrt(2.0)
2025-08-14T21:17:24.3053842Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3054108Z 
2025-08-14T21:17:24.3054232Z         >>> # numpy array to numpy array comparison
2025-08-14T21:17:24.3054582Z         >>> import numpy as np
2025-08-14T21:17:24.3054878Z         >>> expected = np.array([1e0, 1e-1, 1e-2])
2025-08-14T21:17:24.3055243Z         >>> actual = np.arccos(np.cos(expected))
2025-08-14T21:17:24.3055627Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3055878Z 
2025-08-14T21:17:24.3056008Z         >>> # sequence to sequence comparison
2025-08-14T21:17:24.3056328Z         >>> import numpy as np
2025-08-14T21:17:24.3056763Z         >>> # The types of the sequences do not have to match. They only have to have the same
2025-08-14T21:17:24.3057266Z         >>> # length and their elements have to match.
2025-08-14T21:17:24.3057653Z         >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)]
2025-08-14T21:17:24.3058027Z         >>> actual = tuple(expected)
2025-08-14T21:17:24.3058377Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3058632Z 
2025-08-14T21:17:24.3058749Z         >>> # mapping to mapping comparison
2025-08-14T21:17:24.3059098Z         >>> from collections import OrderedDict
2025-08-14T21:17:24.3059436Z         >>> import numpy as np
2025-08-14T21:17:24.3059784Z         >>> foo = torch.tensor(1.0)
2025-08-14T21:17:24.3060093Z         >>> bar = 2.0
2025-08-14T21:17:24.3060350Z         >>> baz = np.array(3.0)
2025-08-14T21:17:24.3060791Z         >>> # The types and a possible ordering of mappings do not have to match. They only
2025-08-14T21:17:24.3061354Z         >>> # have to have the same set of keys and their elements have to match.
2025-08-14T21:17:24.3061880Z         >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)])
2025-08-14T21:17:24.3062338Z         >>> actual = {"baz": baz, "bar": bar, "foo": foo}
2025-08-14T21:17:24.3062735Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3062986Z 
2025-08-14T21:17:24.3063111Z         >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-08-14T21:17:24.3063458Z         >>> actual = expected.clone()
2025-08-14T21:17:24.3063836Z         >>> # By default, directly related instances can be compared
2025-08-14T21:17:24.3064326Z         >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected)
2025-08-14T21:17:24.3064857Z         >>> # This check can be made more strict with allow_subclasses=False
2025-08-14T21:17:24.3065282Z         >>> torch.testing.assert_close(
2025-08-14T21:17:24.3065695Z         ...     torch.nn.Parameter(actual), expected, allow_subclasses=False
2025-08-14T21:17:24.3066098Z         ... )
2025-08-14T21:17:24.3066348Z         Traceback (most recent call last):
2025-08-14T21:17:24.3066663Z         ...
2025-08-14T21:17:24.3066986Z         TypeError: No comparison pair was able to handle inputs of type
2025-08-14T21:17:24.3067533Z         <class 'torch.nn.parameter.Parameter'> and <class 'torch.Tensor'>.
2025-08-14T21:17:24.3068095Z         >>> # If the inputs are not directly related, they are never considered close
2025-08-14T21:17:24.3068602Z         >>> torch.testing.assert_close(actual.numpy(), expected)
2025-08-14T21:17:24.3069002Z         Traceback (most recent call last):
2025-08-14T21:17:24.3069310Z         ...
2025-08-14T21:17:24.3069712Z         TypeError: No comparison pair was able to handle inputs of type <class 'numpy.ndarray'>
2025-08-14T21:17:24.3070230Z         and <class 'torch.Tensor'>.
2025-08-14T21:17:24.3070701Z         >>> # Exceptions to these rules are Python scalars. They can be checked regardless of
2025-08-14T21:17:24.3071204Z         >>> # their type if check_dtype=False.
2025-08-14T21:17:24.3071678Z         >>> torch.testing.assert_close(1.0, 1, check_dtype=False)
2025-08-14T21:17:24.3071974Z 
2025-08-14T21:17:24.3072076Z         >>> # NaN != NaN by default.
2025-08-14T21:17:24.3072481Z         >>> expected = torch.tensor(float("Nan"))
2025-08-14T21:17:24.3072823Z         >>> actual = expected.clone()
2025-08-14T21:17:24.3073188Z         >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:24.3073569Z         Traceback (most recent call last):
2025-08-14T21:17:24.3073885Z         ...
2025-08-14T21:17:24.3074125Z         AssertionError: Scalars are not close!
2025-08-14T21:17:24.3074465Z         <BLANKLINE>
2025-08-14T21:17:24.3074724Z         Expected nan but got nan.
2025-08-14T21:17:24.3075059Z         Absolute difference: nan (up to 1e-05 allowed)
2025-08-14T21:17:24.3075468Z         Relative difference: nan (up to 1.3e-06 allowed)
2025-08-14T21:17:24.3075935Z         >>> torch.testing.assert_close(actual, expected, equal_nan=True)
2025-08-14T21:17:24.3076252Z 
2025-08-14T21:17:24.3076376Z         >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-08-14T21:17:24.3076739Z         >>> actual = torch.tensor([1.0, 4.0, 5.0])
2025-08-14T21:17:24.3077125Z         >>> # The default error message can be overwritten.
2025-08-14T21:17:24.3077501Z         >>> torch.testing.assert_close(
2025-08-14T21:17:24.3077896Z         ...     actual, expected, msg="Argh, the tensors are not close!"
2025-08-14T21:17:24.3078281Z         ... )
2025-08-14T21:17:24.3078531Z         Traceback (most recent call last):
2025-08-14T21:17:24.3078826Z         ...
2025-08-14T21:17:24.3079107Z         AssertionError: Argh, the tensors are not close!
2025-08-14T21:17:24.3079623Z         >>> # If msg is a callable, it can be used to augment the generated message with
2025-08-14T21:17:24.3092359Z         >>> # extra information
2025-08-14T21:17:24.3092704Z         >>> torch.testing.assert_close(
2025-08-14T21:17:24.3093137Z         ...     actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter"
2025-08-14T21:17:24.3093540Z         ... )
2025-08-14T21:17:24.3093794Z         Traceback (most recent call last):
2025-08-14T21:17:24.3094113Z         ...
2025-08-14T21:17:24.3094333Z         AssertionError: Header
2025-08-14T21:17:24.3094631Z         <BLANKLINE>
2025-08-14T21:17:24.3094890Z         Tensor-likes are not close!
2025-08-14T21:17:24.3095175Z         <BLANKLINE>
2025-08-14T21:17:24.3095434Z         Mismatched elements: 2 / 3 (66.7%)
2025-08-14T21:17:24.3095886Z         Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed)
2025-08-14T21:17:24.3096452Z         Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed)
2025-08-14T21:17:24.3096899Z         <BLANKLINE>
2025-08-14T21:17:24.3097139Z         Footer
2025-08-14T21:17:24.3097356Z     
2025-08-14T21:17:24.3097709Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:24.3098091Z 
2025-08-14T21:17:25.5206362Z msg = Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134.
2025-08-14T21:17:25.5207320Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.5207890Z Register a container-like type as pytree node.
2025-08-14T21:17:25.5208143Z 
2025-08-14T21:17:25.5208242Z     Args:
2025-08-14T21:17:25.5208545Z         cls (type): A Python type to treat as an internal pytree node.
2025-08-14T21:17:25.5209299Z         flatten_fn (callable): A function to be used during flattening, taking an instance of
2025-08-14T21:17:25.5209950Z             ``cls`` and returning a pair, with (1) an iterable for the children to be flattened
2025-08-14T21:17:25.5210636Z             recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be
2025-08-14T21:17:25.5211157Z             passed to the ``unflatten_fn``.
2025-08-14T21:17:25.5211668Z         unflatten_fn (callable): A function taking two arguments: the auxiliary data that was
2025-08-14T21:17:25.5212329Z             returned by ``flatten_fn`` and stored in the treespec, and the unflattened children.
2025-08-14T21:17:25.5212874Z             The function should return an instance of ``cls``.
2025-08-14T21:17:25.5213658Z         serialized_type_name (str, optional): A keyword argument used to specify the fully
2025-08-14T21:17:25.5214222Z             qualified name used when serializing the tree spec.
2025-08-14T21:17:25.5214820Z         to_dumpable_context (callable, optional): An optional keyword argument to custom specify how
2025-08-14T21:17:25.5215521Z             to convert the context of the pytree to a custom json dumpable representation. This is
2025-08-14T21:17:25.5216201Z             used for json serialization, which is being used in :mod:`torch.export` right now.
2025-08-14T21:17:25.5216895Z         from_dumpable_context (callable, optional): An optional keyword argument to custom specify
2025-08-14T21:17:25.5217585Z             how to convert the custom json dumpable representation of the context back to the
2025-08-14T21:17:25.5218217Z             original context. This is used for json deserialization, which is being used in
2025-08-14T21:17:25.5218716Z             :mod:`torch.export` right now.
2025-08-14T21:17:25.5218941Z 
2025-08-14T21:17:25.5219061Z     Example::
2025-08-14T21:17:25.5219193Z 
2025-08-14T21:17:25.5219305Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:25.5219623Z         >>> # Registry a Python type with lambda functions
2025-08-14T21:17:25.5219991Z         >>> register_pytree_node(
2025-08-14T21:17:25.5220300Z         ...     set,
2025-08-14T21:17:25.5220563Z         ...     lambda s: (sorted(s), None, None),
2025-08-14T21:17:25.5220981Z         ...     lambda children, _: set(children),
2025-08-14T21:17:25.5221362Z         ... )
2025-08-14T21:17:25.5221565Z     
2025-08-14T21:17:25.5221937Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.5222307Z 
2025-08-14T21:17:25.5902519Z msg = Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218.
2025-08-14T21:17:25.5903532Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.5903936Z 
2025-08-14T21:17:25.5904153Z Context passed to policy function during selective checkpointing.
2025-08-14T21:17:25.5904498Z 
2025-08-14T21:17:25.5904723Z This class is used to pass relevant metadata to the policy function during
2025-08-14T21:17:25.5905350Z selective checkpointing. The metadata includes whether the current invocation
2025-08-14T21:17:25.5905908Z of the policy function is during recomputation or not.
2025-08-14T21:17:25.5906188Z 
2025-08-14T21:17:25.5906305Z Example:
2025-08-14T21:17:25.5906613Z     >>> # xdoctest: +SKIP(stub)
2025-08-14T21:17:25.5906941Z     >>>
2025-08-14T21:17:25.5907179Z     >>> def policy_fn(ctx, op, *args, **kwargs):
2025-08-14T21:17:25.5907577Z     >>>    print(ctx.is_recompute)
2025-08-14T21:17:25.5908053Z     >>>
2025-08-14T21:17:25.5908793Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-08-14T21:17:25.5909492Z     >>>
2025-08-14T21:17:25.5909770Z     >>> out = torch.utils.checkpoint.checkpoint(
2025-08-14T21:17:25.5910118Z     >>>     fn, x, y,
2025-08-14T21:17:25.5910368Z     >>>     use_reentrant=False,
2025-08-14T21:17:25.5910670Z     >>>     context_fn=context_fn,
2025-08-14T21:17:25.5910957Z     >>> )
2025-08-14T21:17:25.5911078Z 
2025-08-14T21:17:25.5911330Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.5911779Z 
2025-08-14T21:17:25.5912437Z msg = Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358.
2025-08-14T21:17:25.5913450Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.5913844Z 
2025-08-14T21:17:25.5914083Z Helper to avoid recomputing certain ops during activation checkpointing.
2025-08-14T21:17:25.5914432Z 
2025-08-14T21:17:25.5914662Z Use this with `torch.utils.checkpoint.checkpoint` to control which
2025-08-14T21:17:25.5915367Z operations are recomputed during the backward pass.
2025-08-14T21:17:25.5915654Z 
2025-08-14T21:17:25.5915738Z Args:
2025-08-14T21:17:25.5915979Z     policy_fn_or_list (Callable or List):
2025-08-14T21:17:25.5916369Z       - If a policy function is provided, it should accept a
2025-08-14T21:17:25.5916898Z         :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and
2025-08-14T21:17:25.5917474Z         kwargs to the op, and return a :class:`CheckpointPolicy` enum value
2025-08-14T21:17:25.5918048Z         indicating whether the execution of the op should be recomputed or not.
2025-08-14T21:17:25.5918603Z       - If a list of operations is provided, it is equivalent to a policy
2025-08-14T21:17:25.5919112Z         returning `CheckpointPolicy.MUST_SAVE` for the specified
2025-08-14T21:17:25.5919634Z         operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other
2025-08-14T21:17:25.5920055Z         operations.
2025-08-14T21:17:25.5920425Z     allow_cache_entry_mutation (bool, optional): By default, an error is
2025-08-14T21:17:25.5920980Z         raised if any tensors cached by selective activation checkpoint are
2025-08-14T21:17:25.5921529Z         mutated in order to ensure correctness. If set to `True`, this check
2025-08-14T21:17:25.5921943Z         is disabled.
2025-08-14T21:17:25.5922189Z Returns:
2025-08-14T21:17:25.5922426Z     A tuple of two context managers.
2025-08-14T21:17:25.5922638Z 
2025-08-14T21:17:25.5922722Z Example:
2025-08-14T21:17:25.5923007Z     >>> # xdoctest: +REQUIRES(LINUX)
2025-08-14T21:17:25.5923369Z     >>> import functools
2025-08-14T21:17:25.5923612Z     >>>
2025-08-14T21:17:25.5923859Z     >>> x = torch.rand(10, 10, requires_grad=True)
2025-08-14T21:17:25.5924225Z     >>> y = torch.rand(10, 10, requires_grad=True)
2025-08-14T21:17:25.5924537Z     >>>
2025-08-14T21:17:25.5924753Z     >>> ops_to_save = [
2025-08-14T21:17:25.5925035Z     >>>    torch.ops.aten.mm.default,
2025-08-14T21:17:25.5925328Z     >>> ]
2025-08-14T21:17:25.5925540Z     >>>
2025-08-14T21:17:25.5925789Z     >>> def policy_fn(ctx, op, *args, **kwargs):
2025-08-14T21:17:25.5926134Z     >>>    if op in ops_to_save:
2025-08-14T21:17:25.5926443Z     >>>        return CheckpointPolicy.MUST_SAVE
2025-08-14T21:17:25.5926775Z     >>>    else:
2025-08-14T21:17:25.5927065Z     >>>        return CheckpointPolicy.PREFER_RECOMPUTE
2025-08-14T21:17:25.5927393Z     >>>
2025-08-14T21:17:25.5927782Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-08-14T21:17:25.5928259Z     >>>
2025-08-14T21:17:25.5928465Z     >>> # or equivalently
2025-08-14T21:17:25.5928908Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save)
2025-08-14T21:17:25.5929389Z     >>>
2025-08-14T21:17:25.5929585Z     >>> def fn(x, y):
2025-08-14T21:17:25.5929942Z     >>>     return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y
2025-08-14T21:17:25.5930346Z     >>>
2025-08-14T21:17:25.5930591Z     >>> out = torch.utils.checkpoint.checkpoint(
2025-08-14T21:17:25.5930932Z     >>>     fn, x, y,
2025-08-14T21:17:25.5931199Z     >>>     use_reentrant=False,
2025-08-14T21:17:25.5931503Z     >>>     context_fn=context_fn,
2025-08-14T21:17:25.5931776Z     >>> )
2025-08-14T21:17:25.5931905Z 
2025-08-14T21:17:25.5932157Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.5932523Z 
2025-08-14T21:17:25.6183484Z msg = Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1147.
2025-08-14T21:17:25.6184552Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6184933Z 
2025-08-14T21:17:25.6185080Z Create a :class:`setuptools.Extension` for C++.
2025-08-14T21:17:25.6185346Z 
2025-08-14T21:17:25.6185586Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:25.6186175Z bare minimum (but often sufficient) arguments to build a C++ extension.
2025-08-14T21:17:25.6186511Z 
2025-08-14T21:17:25.6186971Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:25.6187455Z constructor. Full list arguments can be found at
2025-08-14T21:17:25.6188060Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-08-14T21:17:25.6188520Z 
2025-08-14T21:17:25.6188626Z .. warning::
2025-08-14T21:17:25.6189150Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:25.6190012Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:25.6190880Z     the user's responsibility in their library to not use APIs from
2025-08-14T21:17:25.6191922Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:25.6192607Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:25.6193166Z     example, to give access to custom ops from python, the library should
2025-08-14T21:17:25.6193634Z     register the ops through the dispatcher.
2025-08-14T21:17:25.6193877Z 
2025-08-14T21:17:25.6194114Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:25.6194655Z     as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:25.6195193Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:25.6195743Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:25.6196647Z     safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:25.6197282Z     different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:25.6197730Z     CPython version of choice.
2025-08-14T21:17:25.6197919Z 
2025-08-14T21:17:25.6198021Z Example:
2025-08-14T21:17:25.6198231Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.6198559Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:25.6198939Z     >>> from setuptools import setup
2025-08-14T21:17:25.6199368Z     >>> from torch.utils.cpp_extension import BuildExtension, CppExtension
2025-08-14T21:17:25.6199800Z     >>> setup(
2025-08-14T21:17:25.6200042Z     ...     name='extension',
2025-08-14T21:17:25.6200311Z     ...     ext_modules=[
2025-08-14T21:17:25.6200579Z     ...         CppExtension(
2025-08-14T21:17:25.6200863Z     ...             name='extension',
2025-08-14T21:17:25.6201178Z     ...             sources=['extension.cpp'],
2025-08-14T21:17:25.6201531Z     ...             extra_compile_args=['-g'],
2025-08-14T21:17:25.6201915Z     ...             extra_link_args=['-Wl,--no-as-needed', '-lm'])
2025-08-14T21:17:25.6202274Z     ...     ],
2025-08-14T21:17:25.6202486Z     ...     cmdclass={
2025-08-14T21:17:25.6202754Z     ...         'build_ext': BuildExtension
2025-08-14T21:17:25.6203053Z     ...     })
2025-08-14T21:17:25.6203179Z 
2025-08-14T21:17:25.6203440Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6203806Z 
2025-08-14T21:17:25.6204417Z msg = Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1217.
2025-08-14T21:17:25.6205340Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6205813Z 
2025-08-14T21:17:25.6206062Z Create a :class:`setuptools.Extension` for CUDA/C++.
2025-08-14T21:17:25.6206421Z 
2025-08-14T21:17:25.6206662Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:25.6207314Z bare minimum (but often sufficient) arguments to build a CUDA/C++
2025-08-14T21:17:25.6208278Z extension. This includes the CUDA include path, library path and runtime
2025-08-14T21:17:25.6208812Z library.
2025-08-14T21:17:25.6208939Z 
2025-08-14T21:17:25.6209321Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:25.6209794Z constructor. Full list arguments can be found at
2025-08-14T21:17:25.6210372Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-08-14T21:17:25.6210975Z 
2025-08-14T21:17:25.6211076Z .. warning::
2025-08-14T21:17:25.6211445Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:25.6212007Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:25.6212526Z     the user's responsibility in their library to not use APIs from
2025-08-14T21:17:25.6213072Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:25.6213647Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:25.6214183Z     example, to give access to custom ops from python, the library should
2025-08-14T21:17:25.6214645Z     register the ops through the dispatcher.
2025-08-14T21:17:25.6214889Z 
2025-08-14T21:17:25.6215112Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:25.6215656Z     as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:25.6216266Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:25.6217032Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:25.6217788Z     safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:25.6218405Z     different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:25.6218849Z     CPython version of choice.
2025-08-14T21:17:25.6219140Z 
2025-08-14T21:17:25.6219227Z Example:
2025-08-14T21:17:25.6219505Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.6219810Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:25.6220185Z     >>> from setuptools import setup
2025-08-14T21:17:25.6220625Z     >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension
2025-08-14T21:17:25.6221045Z     >>> setup(
2025-08-14T21:17:25.6221290Z     ...     name='cuda_extension',
2025-08-14T21:17:25.6221584Z     ...     ext_modules=[
2025-08-14T21:17:25.6221836Z     ...         CUDAExtension(
2025-08-14T21:17:25.6222138Z     ...                 name='cuda_extension',
2025-08-14T21:17:25.6222526Z     ...                 sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:25.6222937Z     ...                 extra_compile_args={'cxx': ['-g'],
2025-08-14T21:17:25.6223287Z     ...                                     'nvcc': ['-O2']},
2025-08-14T21:17:25.6223676Z     ...                 extra_link_args=['-Wl,--no-as-needed', '-lcuda'])
2025-08-14T21:17:25.6224039Z     ...     ],
2025-08-14T21:17:25.6224250Z     ...     cmdclass={
2025-08-14T21:17:25.6224521Z     ...         'build_ext': BuildExtension
2025-08-14T21:17:25.6224825Z     ...     })
2025-08-14T21:17:25.6224952Z 
2025-08-14T21:17:25.6225049Z Compute capabilities:
2025-08-14T21:17:25.6225220Z 
2025-08-14T21:17:25.6225515Z By default the extension will be compiled to run on all archs of the cards visible during the
2025-08-14T21:17:25.6226223Z building process of the extension, plus PTX. If down the road a new card is installed the
2025-08-14T21:17:25.6226929Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's
2025-08-14T21:17:25.6227633Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch
2025-08-14T21:17:25.6228339Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does
2025-08-14T21:17:25.6228865Z support (see below for details on PTX).
2025-08-14T21:17:25.6229088Z 
2025-08-14T21:17:25.6229408Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which
2025-08-14T21:17:25.6229942Z CCs you want the extension to support:
2025-08-14T21:17:25.6230171Z 
2025-08-14T21:17:25.6230358Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py``
2025-08-14T21:17:25.6230894Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py``
2025-08-14T21:17:25.6231246Z 
2025-08-14T21:17:25.6231723Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified
2025-08-14T21:17:25.6232486Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >=
2025-08-14T21:17:25.6233228Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with
2025-08-14T21:17:25.6233947Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to
2025-08-14T21:17:25.6234672Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on
2025-08-14T21:17:25.6235399Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better
2025-08-14T21:17:25.6236114Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6,
2025-08-14T21:17:25.6236873Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but
2025-08-14T21:17:25.6237395Z "8.0 8.6" would be better.
2025-08-14T21:17:25.6237579Z 
2025-08-14T21:17:25.6237879Z Note that while it's possible to include all supported archs, the more archs get included the
2025-08-14T21:17:25.6238590Z slower the building process will be, as it will build a separate kernel image for each arch.
2025-08-14T21:17:25.6238994Z 
2025-08-14T21:17:25.6239337Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows.
2025-08-14T21:17:25.6239993Z To workaround the issue, move python binding logic to pure C++ file.
2025-08-14T21:17:25.6240409Z 
2025-08-14T21:17:25.6240498Z Example use:
2025-08-14T21:17:25.6240738Z     #include <ATen/ATen.h>
2025-08-14T21:17:25.6241060Z     at::Tensor SigmoidAlphaBlendForwardCuda(....)
2025-08-14T21:17:25.6241331Z 
2025-08-14T21:17:25.6241419Z Instead of:
2025-08-14T21:17:25.6241659Z     #include <torch/extension.h>
2025-08-14T21:17:25.6242017Z     torch::Tensor SigmoidAlphaBlendForwardCuda(...)
2025-08-14T21:17:25.6242283Z 
2025-08-14T21:17:25.6242556Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460
2025-08-14T21:17:25.6243462Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48
2025-08-14T21:17:25.6244082Z 
2025-08-14T21:17:25.6244207Z Relocatable device code linking:
2025-08-14T21:17:25.6244405Z 
2025-08-14T21:17:25.6244696Z If you want to reference device symbols across compilation units (across object files),
2025-08-14T21:17:25.6245350Z the object files need to be built with `relocatable device code` (-rdc=true or -dc).
2025-08-14T21:17:25.6246092Z An exception to this rule is "dynamic parallelism" (nested kernel launches)  which is not used a lot anymore.
2025-08-14T21:17:25.6246905Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it.
2025-08-14T21:17:25.6247658Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step
2025-08-14T21:17:25.6248281Z helps reduce the protentional perf degradation of `-rdc`.
2025-08-14T21:17:25.6248746Z Note that it needs to be used at both steps to be useful.
2025-08-14T21:17:25.6249019Z 
2025-08-14T21:17:25.6249394Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step.
2025-08-14T21:17:25.6250038Z There is also a case where `-dlink` is used without `-rdc`:
2025-08-14T21:17:25.6250584Z when an extension is linked against a static lib containing rdc-compiled objects
2025-08-14T21:17:25.6251174Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem).
2025-08-14T21:17:25.6251496Z 
2025-08-14T21:17:25.6251708Z Note: Ninja is required to build a CUDA Extension with RDC linking.
2025-08-14T21:17:25.6252023Z 
2025-08-14T21:17:25.6252106Z Example:
2025-08-14T21:17:25.6252325Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.6252642Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:25.6252982Z     >>> CUDAExtension(
2025-08-14T21:17:25.6253246Z     ...        name='cuda_extension',
2025-08-14T21:17:25.6253692Z     ...        sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:25.6254056Z     ...        dlink=True,
2025-08-14T21:17:25.6254346Z     ...        dlink_libraries=["dlink_lib"],
2025-08-14T21:17:25.6254697Z     ...        extra_compile_args={'cxx': ['-g'],
2025-08-14T21:17:25.6255055Z     ...                            'nvcc': ['-O2', '-rdc=true']})
2025-08-14T21:17:25.6255291Z 
2025-08-14T21:17:25.6255541Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6255926Z 
2025-08-14T21:17:25.6256473Z msg = Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1408.
2025-08-14T21:17:25.6257394Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6257770Z 
2025-08-14T21:17:25.6257947Z Creates a :class:`setuptools.Extension` for SYCL/C++.
2025-08-14T21:17:25.6258215Z 
2025-08-14T21:17:25.6258458Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:25.6259020Z bare minimum (but often sufficient) arguments to build a SYCL/C++
2025-08-14T21:17:25.6259427Z extension.
2025-08-14T21:17:25.6259548Z 
2025-08-14T21:17:25.6259751Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:25.6260161Z constructor.
2025-08-14T21:17:25.6260302Z 
2025-08-14T21:17:25.6260390Z .. warning::
2025-08-14T21:17:25.6260777Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:25.6261349Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:25.6261877Z     the user's responsibility in their library to not use APIs from
2025-08-14T21:17:25.6262423Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:25.6262980Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:25.6263532Z     example, to give access to custom ops from python, the library should
2025-08-14T21:17:25.6263998Z     register the ops through the dispatcher.
2025-08-14T21:17:25.6264231Z 
2025-08-14T21:17:25.6264467Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:25.6265003Z     as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:25.6265536Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:25.6266080Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:25.6266622Z     safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:25.6267170Z     different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:25.6267609Z     CPython version of choice.
2025-08-14T21:17:25.6267796Z 
2025-08-14T21:17:25.6267892Z Example:
2025-08-14T21:17:25.6268099Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.6268417Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:25.6268902Z     >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension
2025-08-14T21:17:25.6269319Z     >>> setup(
2025-08-14T21:17:25.6269559Z     ...     name='xpu_extension',
2025-08-14T21:17:25.6269851Z     ...     ext_modules=[
2025-08-14T21:17:25.6270102Z     ...     SyclExtension(
2025-08-14T21:17:25.6270386Z     ...                 name='xpu_extension',
2025-08-14T21:17:25.6270775Z     ...                 sources=['extension.cpp', 'extension_kernel.cpp'],
2025-08-14T21:17:25.6271243Z     ...                 extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']})
2025-08-14T21:17:25.6271698Z     ...     ],
2025-08-14T21:17:25.6271924Z     ...     cmdclass={
2025-08-14T21:17:25.6272195Z     ...         'build_ext': BuildExtension
2025-08-14T21:17:25.6272489Z     ...     })
2025-08-14T21:17:25.6272632Z 
2025-08-14T21:17:25.6272928Z By default the extension will be compiled to run on all archs of the cards visible during the
2025-08-14T21:17:25.6273673Z building process of the extension. If down the road a new card is installed the
2025-08-14T21:17:25.6274288Z extension may need to be recompiled. You can override the default behavior using
2025-08-14T21:17:25.6274966Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension
2025-08-14T21:17:25.6275485Z to support:
2025-08-14T21:17:25.6275609Z 
2025-08-14T21:17:25.6275824Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py``
2025-08-14T21:17:25.6276136Z 
2025-08-14T21:17:25.6276434Z Note that while it's possible to include all supported archs, the more archs get included the
2025-08-14T21:17:25.6277146Z slower the building process will be, as it will build a separate kernel image for each arch.
2025-08-14T21:17:25.6277563Z 
2025-08-14T21:17:25.6277699Z Note: Ninja is required to build SyclExtension.
2025-08-14T21:17:25.6277945Z 
2025-08-14T21:17:25.6278205Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6278571Z 
2025-08-14T21:17:25.6279131Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1585.
2025-08-14T21:17:25.6280003Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6280378Z 
2025-08-14T21:17:25.6280520Z Load a PyTorch C++ extension just-in-time (JIT).
2025-08-14T21:17:25.6280785Z 
2025-08-14T21:17:25.6280990Z To load an extension, a Ninja build file is emitted, which is used to
2025-08-14T21:17:25.6281559Z compile the given sources into a dynamic library. This library is
2025-08-14T21:17:25.6282130Z subsequently loaded into the current Python process as a module and
2025-08-14T21:17:25.6282584Z returned from this function, ready for use.
2025-08-14T21:17:25.6282830Z 
2025-08-14T21:17:25.6283035Z By default, the directory to which the build file is emitted and the
2025-08-14T21:17:25.6283595Z resulting library compiled to is ``<tmp>/torch_extensions/<name>``, where
2025-08-14T21:17:25.6284144Z ``<tmp>`` is the temporary folder on the current platform and ``<name>``
2025-08-14T21:17:25.6284684Z the name of the extension. This location can be overridden in two ways.
2025-08-14T21:17:25.6285226Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it
2025-08-14T21:17:25.6285768Z replaces ``<tmp>/torch_extensions`` and all extensions will be compiled
2025-08-14T21:17:25.6286308Z into subfolders of this directory. Second, if the ``build_directory``
2025-08-14T21:17:25.6286894Z argument to this function is supplied, it overrides the entire path, i.e.
2025-08-14T21:17:25.6287400Z the library will be compiled into that folder directly.
2025-08-14T21:17:25.6287685Z 
2025-08-14T21:17:25.6287895Z To compile the sources, the default system compiler (``c++``) is used,
2025-08-14T21:17:25.6288465Z which can be overridden by setting the ``CXX`` environment variable. To pass
2025-08-14T21:17:25.6289058Z additional arguments to the compilation process, ``extra_cflags`` or
2025-08-14T21:17:25.6289619Z ``extra_ldflags`` can be provided. For example, to compile your extension
2025-08-14T21:17:25.6290176Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use
2025-08-14T21:17:25.6290667Z ``extra_cflags`` to pass further include directories.
2025-08-14T21:17:25.6290929Z 
2025-08-14T21:17:25.6291165Z CUDA support with mixed compilation is provided. Simply pass CUDA source
2025-08-14T21:17:25.6291710Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be
2025-08-14T21:17:25.6292259Z detected and compiled with nvcc rather than the C++ compiler. This includes
2025-08-14T21:17:25.6292837Z passing the CUDA lib64 directory as a library directory, and linking
2025-08-14T21:17:25.6293310Z ``cudart``. You can pass additional flags to nvcc via
2025-08-14T21:17:25.6293782Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various
2025-08-14T21:17:25.6294347Z heuristics for finding the CUDA install directory are used, which usually
2025-08-14T21:17:25.6294956Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the
2025-08-14T21:17:25.6295384Z safest option.
2025-08-14T21:17:25.6295533Z 
2025-08-14T21:17:25.6295769Z SYCL support with mixed compilation is provided. Simply pass SYCL source
2025-08-14T21:17:25.6296322Z files (``.sycl``) along with other sources. Such files will be detected
2025-08-14T21:17:25.6296842Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather
2025-08-14T21:17:25.6297387Z than the C++ compiler. You can pass additional flags to SYCL compiler
2025-08-14T21:17:25.6297910Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++.
2025-08-14T21:17:25.6298412Z SYCL compiler is expected to be found via system PATH environment
2025-08-14T21:17:25.6298818Z variable.
2025-08-14T21:17:25.6298951Z 
2025-08-14T21:17:25.6299032Z Args:
2025-08-14T21:17:25.6299359Z     name: The name of the extension to build. This MUST be the same as the
2025-08-14T21:17:25.6299783Z         name of the pybind11 module!
2025-08-14T21:17:25.6300198Z     sources: A list of relative or absolute paths to C++ source files.
2025-08-14T21:17:25.6300741Z     extra_cflags: optional list of compiler flags to forward to the build.
2025-08-14T21:17:25.6301294Z     extra_cuda_cflags: optional list of compiler flags to forward to nvcc
2025-08-14T21:17:25.6301739Z         when building CUDA sources.
2025-08-14T21:17:25.6302163Z     extra_sycl_cflags: optional list of compiler flags to forward to SYCL
2025-08-14T21:17:25.6302653Z         compiler when building SYCL sources.
2025-08-14T21:17:25.6303124Z     extra_ldflags: optional list of linker flags to forward to the build.
2025-08-14T21:17:25.6303686Z     extra_include_paths: optional list of include directories to forward
2025-08-14T21:17:25.6304120Z         to the build.
2025-08-14T21:17:25.6304445Z     build_directory: optional path to use as build workspace.
2025-08-14T21:17:25.6304927Z     verbose: If ``True``, turns on verbose logging of load steps.
2025-08-14T21:17:25.6305447Z     with_cuda: Determines whether CUDA headers and libraries are added to
2025-08-14T21:17:25.6305939Z         the build. If set to ``None`` (default), this value is
2025-08-14T21:17:25.6306418Z         automatically determined based on the existence of ``.cu`` or
2025-08-14T21:17:25.6306910Z         ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers
2025-08-14T21:17:25.6307305Z         and libraries to be included.
2025-08-14T21:17:25.6307724Z     with_sycl: Determines whether SYCL headers and libraries are added to
2025-08-14T21:17:25.6308228Z         the build. If set to ``None`` (default), this value is
2025-08-14T21:17:25.6308714Z         automatically determined based on the existence of ``.sycl`` in
2025-08-14T21:17:25.6309356Z         ``sources``. Set it to `True`` to force SYCL headers and
2025-08-14T21:17:25.6309746Z         libraries to be included.
2025-08-14T21:17:25.6310160Z     is_python_module: If ``True`` (default), imports the produced shared
2025-08-14T21:17:25.6310677Z         library as a Python module. If ``False``, behavior depends on
2025-08-14T21:17:25.6311078Z         ``is_standalone``.
2025-08-14T21:17:25.6311540Z     is_standalone: If ``False`` (default) loads the constructed extension
2025-08-14T21:17:25.6312070Z         into the process as a plain dynamic library. If ``True``, build a
2025-08-14T21:17:25.6312486Z         standalone executable.
2025-08-14T21:17:25.6312686Z 
2025-08-14T21:17:25.6312770Z Returns:
2025-08-14T21:17:25.6313004Z     If ``is_python_module`` is ``True``:
2025-08-14T21:17:25.6313394Z         Returns the loaded PyTorch extension as a Python module.
2025-08-14T21:17:25.6313698Z 
2025-08-14T21:17:25.6313899Z     If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``:
2025-08-14T21:17:25.6314433Z         Returns nothing. (The shared library is loaded into the process as
2025-08-14T21:17:25.6314853Z         a side effect.)
2025-08-14T21:17:25.6315008Z 
2025-08-14T21:17:25.6315115Z     If ``is_standalone`` is ``True``.
2025-08-14T21:17:25.6316014Z         Return the path to the executable. (On Windows, TORCH_LIB_PATH is
2025-08-14T21:17:25.6316519Z         added to the PATH environment variable as a side effect.)
2025-08-14T21:17:25.6316805Z 
2025-08-14T21:17:25.6316904Z Example:
2025-08-14T21:17:25.6317113Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.6317421Z     >>> from torch.utils.cpp_extension import load
2025-08-14T21:17:25.6317767Z     >>> module = load(
2025-08-14T21:17:25.6318012Z     ...     name='extension',
2025-08-14T21:17:25.6318355Z     ...     sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:25.6318733Z     ...     extra_cflags=['-O2'],
2025-08-14T21:17:25.6319009Z     ...     verbose=True)
2025-08-14T21:17:25.6319180Z 
2025-08-14T21:17:25.6319429Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6319796Z 
2025-08-14T21:17:25.6320335Z msg = Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1890.
2025-08-14T21:17:25.6321235Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6321610Z 
2025-08-14T21:17:25.6321820Z Load a PyTorch C++ extension just-in-time (JIT) from string sources.
2025-08-14T21:17:25.6322151Z 
2025-08-14T21:17:25.6322380Z This function behaves exactly like :func:`load`, but takes its sources as
2025-08-14T21:17:25.6322958Z strings rather than filenames. These strings are stored to files in the
2025-08-14T21:17:25.6323564Z build directory, after which the behavior of :func:`load_inline` is
2025-08-14T21:17:25.6324035Z identical to :func:`load`.
2025-08-14T21:17:25.6324222Z 
2025-08-14T21:17:25.6324305Z See `the
2025-08-14T21:17:25.6324751Z tests <https://github.com/pytorch/pytorch/blob/master/test/test_cpp_extensions_jit.py>`_
2025-08-14T21:17:25.6325306Z for good examples of using this function.
2025-08-14T21:17:25.6325548Z 
2025-08-14T21:17:25.6325780Z Sources may omit two required parts of a typical non-inline C++ extension:
2025-08-14T21:17:25.6326386Z the necessary header includes, as well as the (pybind11) binding code. More
2025-08-14T21:17:25.6326989Z precisely, strings passed to ``cpp_sources`` are first concatenated into a
2025-08-14T21:17:25.6327525Z single ``.cpp`` file. This file is then prepended with ``#include
2025-08-14T21:17:25.6327927Z <torch/extension.h>``
2025-08-14T21:17:25.6328083Z 
2025-08-14T21:17:25.6328316Z Furthermore, if the ``functions`` argument is supplied, bindings will be
2025-08-14T21:17:25.6328890Z automatically generated for each function specified. ``functions`` can
2025-08-14T21:17:25.6329469Z either be a list of function names, or a dictionary mapping from function
2025-08-14T21:17:25.6330035Z names to docstrings. If a list is given, the name of each function is used
2025-08-14T21:17:25.6330474Z as its docstring.
2025-08-14T21:17:25.6330617Z 
2025-08-14T21:17:25.6330830Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu``
2025-08-14T21:17:25.6331337Z file and  prepended with ``torch/types.h``, ``cuda.h`` and
2025-08-14T21:17:25.6331840Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled
2025-08-14T21:17:25.6332382Z separately, but ultimately linked into a single library. Note that no
2025-08-14T21:17:25.6332960Z bindings are generated for functions in ``cuda_sources`` per se. To bind
2025-08-14T21:17:25.6333528Z to a CUDA kernel, you must create a C++ function that calls it, and either
2025-08-14T21:17:25.6334081Z declare or define this C++ function in one of the ``cpp_sources`` (and
2025-08-14T21:17:25.6334520Z include its name in ``functions``).
2025-08-14T21:17:25.6334739Z 
2025-08-14T21:17:25.6334957Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl``
2025-08-14T21:17:25.6335519Z file and  prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes.
2025-08-14T21:17:25.6336043Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately
2025-08-14T21:17:25.6336581Z linked into a single library. Note that no bindings are generated for
2025-08-14T21:17:25.6337187Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must
2025-08-14T21:17:25.6337736Z create a C++ function that calls it, and either declare or define this
2025-08-14T21:17:25.6338242Z C++ function in one of the ``cpp_sources`` (and include its name
2025-08-14T21:17:25.6338645Z in ``functions``).
2025-08-14T21:17:25.6338788Z 
2025-08-14T21:17:25.6338792Z 
2025-08-14T21:17:25.6338796Z 
2025-08-14T21:17:25.6338995Z See :func:`load` for a description of arguments omitted below.
2025-08-14T21:17:25.6339287Z 
2025-08-14T21:17:25.6339383Z Args:
2025-08-14T21:17:25.6339708Z     cpp_sources: A string, or list of strings, containing C++ source code.
2025-08-14T21:17:25.6340270Z     cuda_sources: A string, or list of strings, containing CUDA source code.
2025-08-14T21:17:25.6340842Z     sycl_sources: A string, or list of strings, containing SYCL source code.
2025-08-14T21:17:25.6341374Z     functions: A list of function names for which to generate function
2025-08-14T21:17:25.6341913Z         bindings. If a dictionary is given, it should map function names to
2025-08-14T21:17:25.6342429Z         docstrings (which are otherwise just the function names).
2025-08-14T21:17:25.6342955Z     with_cuda: Determines whether CUDA headers and libraries are added to
2025-08-14T21:17:25.6343442Z         the build. If set to ``None`` (default), this value is
2025-08-14T21:17:25.6343921Z         automatically determined based on whether ``cuda_sources`` is
2025-08-14T21:17:25.6344424Z         provided. Set it to ``True`` to force CUDA headers
2025-08-14T21:17:25.6344814Z         and libraries to be included.
2025-08-14T21:17:25.6345245Z     with_sycl: Determines whether SYCL headers and libraries are added to
2025-08-14T21:17:25.6345744Z         the build. If set to ``None`` (default), this value is
2025-08-14T21:17:25.6346223Z         automatically determined based on whether ``sycl_sources`` is
2025-08-14T21:17:25.6346686Z         provided. Set it to ``True`` to force SYCL headers
2025-08-14T21:17:25.6347066Z         and libraries to be included.
2025-08-14T21:17:25.6347486Z     with_pytorch_error_handling: Determines whether pytorch error and
2025-08-14T21:17:25.6348003Z         warning macros are handled by pytorch instead of pybind. To do
2025-08-14T21:17:25.6348541Z         this, each function ``foo`` is called via an intermediary ``_safe_foo``
2025-08-14T21:17:25.6349080Z         function. This redirection might cause issues in obscure cases
2025-08-14T21:17:25.6349575Z         of cpp. This flag should be set to ``False`` when this redirect
2025-08-14T21:17:25.6349975Z         causes issues.
2025-08-14T21:17:25.6350383Z     no_implicit_headers: If ``True``, skips automatically adding headers, most notably
2025-08-14T21:17:25.6350981Z         ``#include <torch/extension.h>`` and ``#include <torch/types.h>`` lines.
2025-08-14T21:17:25.6351555Z         Use this option to improve cold start times when you
2025-08-14T21:17:25.6352089Z         already include the necessary headers in your source code. Default: ``False``.
2025-08-14T21:17:25.6352468Z 
2025-08-14T21:17:25.6352567Z Example:
2025-08-14T21:17:25.6352829Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:25.6353247Z     >>> from torch.utils.cpp_extension import load_inline
2025-08-14T21:17:25.6353613Z     >>> source = """
2025-08-14T21:17:25.6353911Z     at::Tensor sin_add(at::Tensor x, at::Tensor y) {
2025-08-14T21:17:25.6354253Z       return x.sin() + y.sin();
2025-08-14T21:17:25.6354530Z     }
2025-08-14T21:17:25.6354741Z     """
2025-08-14T21:17:25.6354988Z     >>> module = load_inline(name='inline_extension',
2025-08-14T21:17:25.6355362Z     ...                      cpp_sources=[source],
2025-08-14T21:17:25.6355712Z     ...                      functions=['sin_add'])
2025-08-14T21:17:25.6355938Z 
2025-08-14T21:17:25.6356022Z .. note::
2025-08-14T21:17:25.6356381Z     Since load_inline will just-in-time compile the source code, please ensure
2025-08-14T21:17:25.6356966Z     that you have the right toolchains installed in the runtime. For example,
2025-08-14T21:17:25.6357593Z     when loading C++, make sure a C++ compiler is available. If you're loading
2025-08-14T21:17:25.6358170Z     a CUDA extension, you will need to additionally install the corresponding CUDA
2025-08-14T21:17:25.6358788Z     toolkit (nvcc and any other dependencies your code has). Compiling toolchains
2025-08-14T21:17:25.6359396Z     are not included when you install torch and must be additionally installed.
2025-08-14T21:17:25.6359750Z 
2025-08-14T21:17:25.6360005Z     During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build
2025-08-14T21:17:25.6360600Z     the extension. This may use up too many resources on some systems. One
2025-08-14T21:17:25.6361162Z     can control the number of workers by setting the `MAX_JOBS` environment
2025-08-14T21:17:25.6361617Z     variable to a non-negative number.
2025-08-14T21:17:25.6361830Z 
2025-08-14T21:17:25.6362076Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6362453Z 
2025-08-14T21:17:25.6469508Z msg = Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61.
2025-08-14T21:17:25.6470502Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.6470878Z 
2025-08-14T21:17:25.6471189Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark.
2025-08-14T21:17:25.6471758Z 
2025-08-14T21:17:25.6472118Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible
2025-08-14T21:17:25.6472770Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference
2025-08-14T21:17:25.6473372Z server like load. It can emulate multiple calling threads to a single module
2025-08-14T21:17:25.6473964Z provided. In the future we plan to enhance this component to support inter and
2025-08-14T21:17:25.6474555Z intra-op parallelism as well as multiple models running in a single process.
2025-08-14T21:17:25.6474934Z 
2025-08-14T21:17:25.6475184Z Please note that even though nn.Module is supported, it might incur an overhead
2025-08-14T21:17:25.6475779Z from the need to hold GIL every time we execute Python code or pass around
2025-08-14T21:17:25.6476359Z inputs as Python objects. As soon as you have a ScriptModule version of your
2025-08-14T21:17:25.6476941Z model for inference deployment it is better to switch to using it in this
2025-08-14T21:17:25.6477386Z benchmark.
2025-08-14T21:17:25.6477512Z 
2025-08-14T21:17:25.6477609Z Example::
2025-08-14T21:17:25.6477726Z 
2025-08-14T21:17:25.6477842Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:25.6478210Z     >>> from torch.utils import ThroughputBenchmark
2025-08-14T21:17:25.6478594Z     >>> bench = ThroughputBenchmark(my_module)
2025-08-14T21:17:25.6478999Z     >>> # Pre-populate benchmark's data set with the inputs
2025-08-14T21:17:25.6479362Z     >>> for input in inputs:
2025-08-14T21:17:25.6479765Z     ...     # Both args and kwargs work, same as any PyTorch Module / ScriptModule
2025-08-14T21:17:25.6480233Z     ...     bench.add_input(input[0], x2=input[1])
2025-08-14T21:17:25.6480657Z     >>> # Inputs supplied above are randomly used during the execution
2025-08-14T21:17:25.6481076Z     >>> stats = bench.benchmark(
2025-08-14T21:17:25.6481386Z     ...     num_calling_threads=4,
2025-08-14T21:17:25.6481692Z     ...     num_warmup_iters = 100,
2025-08-14T21:17:25.6481982Z     ...     num_iters = 1000,
2025-08-14T21:17:25.6482251Z     ... )
2025-08-14T21:17:25.6482553Z     >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms))
2025-08-14T21:17:25.6483024Z     >>> print("Number of iterations: {}".format(stats.num_iters))
2025-08-14T21:17:25.6483323Z 
2025-08-14T21:17:25.6483573Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.6483940Z 
2025-08-14T21:17:25.7682886Z msg = Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18.
2025-08-14T21:17:25.7683917Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.7684496Z Sampler that restricts data loading to a subset of the dataset.
2025-08-14T21:17:25.7684826Z 
2025-08-14T21:17:25.7684964Z     It is especially useful in conjunction with
2025-08-14T21:17:25.7685467Z     :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each
2025-08-14T21:17:25.7686110Z     process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a
2025-08-14T21:17:25.7686719Z     :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the
2025-08-14T21:17:25.7687205Z     original dataset that is exclusive to it.
2025-08-14T21:17:25.7687443Z 
2025-08-14T21:17:25.7687561Z     .. note::
2025-08-14T21:17:25.7687920Z         Dataset is assumed to be of constant size and that any instance of it always
2025-08-14T21:17:25.7688424Z         returns the same elements in the same order.
2025-08-14T21:17:25.7688689Z 
2025-08-14T21:17:25.7688782Z     Args:
2025-08-14T21:17:25.7689027Z         dataset: Dataset used for sampling.
2025-08-14T21:17:25.7689465Z         num_replicas (int, optional): Number of processes participating in
2025-08-14T21:17:25.7690055Z             distributed training. By default, :attr:`world_size` is retrieved from the
2025-08-14T21:17:25.7690562Z             current distributed group.
2025-08-14T21:17:25.7691087Z         rank (int, optional): Rank of the current process within :attr:`num_replicas`.
2025-08-14T21:17:25.7691700Z             By default, :attr:`rank` is retrieved from the current distributed
2025-08-14T21:17:25.7692114Z             group.
2025-08-14T21:17:25.7692479Z         shuffle (bool, optional): If ``True`` (default), sampler will shuffle the
2025-08-14T21:17:25.7692901Z             indices.
2025-08-14T21:17:25.7693244Z         seed (int, optional): random seed used to shuffle the sampler if
2025-08-14T21:17:25.7693757Z             :attr:`shuffle=True`. This number should be identical across all
2025-08-14T21:17:25.7694239Z             processes in the distributed group. Default: ``0``.
2025-08-14T21:17:25.7694721Z         drop_last (bool, optional): if ``True``, then the sampler will drop the
2025-08-14T21:17:25.7695252Z             tail of the data to make it evenly divisible across the number of
2025-08-14T21:17:25.7695764Z             replicas. If ``False``, the sampler will add extra indices to make
2025-08-14T21:17:25.7696277Z             the data evenly divisible across the replicas. Default: ``False``.
2025-08-14T21:17:25.7696614Z 
2025-08-14T21:17:25.7696706Z     .. warning::
2025-08-14T21:17:25.7697038Z         In distributed mode, calling the :meth:`set_epoch` method at
2025-08-14T21:17:25.7697599Z         the beginning of each epoch **before** creating the :class:`DataLoader` iterator
2025-08-14T21:17:25.7698221Z         is necessary to make shuffling work properly across multiple epochs. Otherwise,
2025-08-14T21:17:25.7698738Z         the same ordering will be always used.
2025-08-14T21:17:25.7698967Z 
2025-08-14T21:17:25.7699068Z     Example::
2025-08-14T21:17:25.7699197Z 
2025-08-14T21:17:25.7699312Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:25.7699705Z         >>> sampler = DistributedSampler(dataset) if is_distributed else None
2025-08-14T21:17:25.7700223Z         >>> loader = DataLoader(dataset, shuffle=(sampler is None),
2025-08-14T21:17:25.7700628Z         ...                     sampler=sampler)
2025-08-14T21:17:25.7700979Z         >>> for epoch in range(start_epoch, n_epochs):
2025-08-14T21:17:25.7701333Z         ...     if is_distributed:
2025-08-14T21:17:25.7701648Z         ...         sampler.set_epoch(epoch)
2025-08-14T21:17:25.7701959Z         ...     train(loader)
2025-08-14T21:17:25.7702225Z     
2025-08-14T21:17:25.7702593Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.7702958Z 
2025-08-14T21:17:25.7763710Z msg = Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=227.
2025-08-14T21:17:25.7764770Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.7765595Z Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights).
2025-08-14T21:17:25.7765993Z 
2025-08-14T21:17:25.7766123Z     Args:
2025-08-14T21:17:25.7766529Z         weights (sequence)   : a sequence of weights, not necessary summing up to one
2025-08-14T21:17:25.7767036Z         num_samples (int): number of samples to draw
2025-08-14T21:17:25.7767508Z         replacement (bool): if ``True``, samples are drawn with replacement.
2025-08-14T21:17:25.7768045Z             If not, they are drawn without replacement, which means that when a
2025-08-14T21:17:25.7768575Z             sample index is drawn for a row, it cannot be drawn again for that row.
2025-08-14T21:17:25.7769076Z         generator (Generator): Generator used in sampling.
2025-08-14T21:17:25.7769355Z 
2025-08-14T21:17:25.7769446Z     Example:
2025-08-14T21:17:25.7769723Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:25.7770053Z         >>> list(
2025-08-14T21:17:25.7770307Z         ...     WeightedRandomSampler(
2025-08-14T21:17:25.7770666Z         ...         [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True
2025-08-14T21:17:25.7770998Z         ...     )
2025-08-14T21:17:25.7771221Z         ... )
2025-08-14T21:17:25.7771525Z         [4, 4, 1, 4, 5]
2025-08-14T21:17:25.7771804Z         >>> list(
2025-08-14T21:17:25.7772058Z         ...     WeightedRandomSampler(
2025-08-14T21:17:25.7772419Z         ...         [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False
2025-08-14T21:17:25.7772763Z         ...     )
2025-08-14T21:17:25.7772972Z         ... )
2025-08-14T21:17:25.7773189Z         [0, 1, 4, 3, 2]
2025-08-14T21:17:25.7773425Z     
2025-08-14T21:17:25.7773777Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.7774154Z 
2025-08-14T21:17:25.7774706Z msg = Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=300.
2025-08-14T21:17:25.7775612Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.7776160Z Wraps another sampler to yield a mini-batch of indices.
2025-08-14T21:17:25.7776435Z 
2025-08-14T21:17:25.7776518Z     Args:
2025-08-14T21:17:25.7776875Z         sampler (Sampler or Iterable): Base sampler. Can be any iterable object
2025-08-14T21:17:25.7777347Z         batch_size (int): Size of mini-batch.
2025-08-14T21:17:25.7777768Z         drop_last (bool): If ``True``, the sampler will drop the last batch if
2025-08-14T21:17:25.7778223Z             its size would be less than ``batch_size``
2025-08-14T21:17:25.7778464Z 
2025-08-14T21:17:25.7778564Z     Example:
2025-08-14T21:17:25.7778785Z         >>> list(
2025-08-14T21:17:25.7779018Z         ...     BatchSampler(
2025-08-14T21:17:25.7779417Z         ...         SequentialSampler(range(10)), batch_size=3, drop_last=False
2025-08-14T21:17:25.7779831Z         ...     )
2025-08-14T21:17:25.7780040Z         ... )
2025-08-14T21:17:25.7780268Z         [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]
2025-08-14T21:17:25.7780563Z         >>> list(
2025-08-14T21:17:25.7780946Z         ...     BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True)
2025-08-14T21:17:25.7781408Z         ... )
2025-08-14T21:17:25.7781637Z         [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
2025-08-14T21:17:25.7781917Z     
2025-08-14T21:17:25.7782287Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.7782653Z 
2025-08-14T21:17:25.8023395Z msg = Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py line=56.
2025-08-14T21:17:25.8024409Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8024796Z 
2025-08-14T21:17:25.8024917Z Iterable-style DataPipe.
2025-08-14T21:17:25.8025355Z 
2025-08-14T21:17:25.8025622Z All DataPipes that represent an iterable of data samples should subclass this.
2025-08-14T21:17:25.8026266Z This style of DataPipes is particularly useful when data come from a stream, or
2025-08-14T21:17:25.8027000Z when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its
2025-08-14T21:17:25.8027781Z elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``.
2025-08-14T21:17:25.8028196Z 
2025-08-14T21:17:25.8028427Z All subclasses should overwrite :meth:`__iter__`, which would return an
2025-08-14T21:17:25.8029129Z iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its
2025-08-14T21:17:25.8029967Z method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should
2025-08-14T21:17:25.8030742Z override ``reset()`` if necessary. The common usages include resetting buffers, pointers,
2025-08-14T21:17:25.8031337Z and various state variables within the custom ``IterDataPipe``.
2025-08-14T21:17:25.8031738Z 
2025-08-14T21:17:25.8031824Z Note:
2025-08-14T21:17:25.8032163Z     Only `one` iterator can be valid for each ``IterDataPipe`` at a time,
2025-08-14T21:17:25.8032843Z     and the creation a second iterator will invalidate the first one. This constraint is necessary because
2025-08-14T21:17:25.8033775Z     some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators.
2025-08-14T21:17:25.8034601Z     The code example below presents details on how this constraint looks in practice.
2025-08-14T21:17:25.8035371Z     If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_.
2025-08-14T21:17:25.8035852Z 
2025-08-14T21:17:25.8036136Z These DataPipes can be invoked in two ways, using the class constructor or applying their
2025-08-14T21:17:25.8036919Z functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes).
2025-08-14T21:17:25.8037725Z You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple
2025-08-14T21:17:25.8038270Z operations in succession.
2025-08-14T21:17:25.8038445Z 
2025-08-14T21:17:25.8038580Z .. _GitHub IterDataPipe Single Iterator Issue:
2025-08-14T21:17:25.8038975Z     https://github.com/pytorch/data/issues/45
2025-08-14T21:17:25.8039220Z 
2025-08-14T21:17:25.8039315Z Note:
2025-08-14T21:17:25.8039650Z     When a subclass is used with :class:`~torch.utils.data.DataLoader`, each
2025-08-14T21:17:25.8040376Z     item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader`
2025-08-14T21:17:25.8040995Z     iterator. When :attr:`num_workers > 0`, each worker process will have a
2025-08-14T21:17:25.8041571Z     different copy of the DataPipe object, so it is often desired to configure
2025-08-14T21:17:25.8042158Z     each copy independently to avoid having duplicate data returned from the
2025-08-14T21:17:25.8042753Z     workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker
2025-08-14T21:17:25.8043364Z     process, returns information about the worker. It can be used in either the
2025-08-14T21:17:25.8043970Z     dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's
2025-08-14T21:17:25.8044522Z     :attr:`worker_init_fn` option to modify each copy's behavior.
2025-08-14T21:17:25.8044831Z 
2025-08-14T21:17:25.8044922Z Examples:
2025-08-14T21:17:25.8045145Z     General Usage:
2025-08-14T21:17:25.8045383Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:25.8045783Z         >>> from torchdata.datapipes.iter import IterableWrapper, Mapper
2025-08-14T21:17:25.8046231Z         >>> dp = IterableWrapper(range(10))
2025-08-14T21:17:25.8046636Z         >>> map_dp_1 = Mapper(dp, lambda x: x + 1)  # Using class constructor
2025-08-14T21:17:25.8047047Z         >>> map_dp_2 = dp.map(
2025-08-14T21:17:25.8047335Z         ...     lambda x: x + 1
2025-08-14T21:17:25.8047734Z         ... )  # Using functional form (recommended)
2025-08-14T21:17:25.8048086Z         >>> list(map_dp_1)
2025-08-14T21:17:25.8048360Z         [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
2025-08-14T21:17:25.8048671Z         >>> list(map_dp_2)
2025-08-14T21:17:25.8048929Z         [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
2025-08-14T21:17:25.8049290Z         >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0)
2025-08-14T21:17:25.8049660Z         >>> list(filter_dp)
2025-08-14T21:17:25.8049919Z         [2, 4, 6, 8, 10]
2025-08-14T21:17:25.8050198Z     Single Iterator Constraint Example:
2025-08-14T21:17:25.8050633Z         >>> from torchdata.datapipes.iter import IterableWrapper, Mapper
2025-08-14T21:17:25.8051078Z         >>> source_dp = IterableWrapper(range(10))
2025-08-14T21:17:25.8051426Z         >>> it1 = iter(source_dp)
2025-08-14T21:17:25.8051714Z         >>> list(it1)
2025-08-14T21:17:25.8051947Z         [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
2025-08-14T21:17:25.8052255Z         >>> it1 = iter(source_dp)
2025-08-14T21:17:25.8052536Z         >>> it2 = iter(
2025-08-14T21:17:25.8052784Z         ...     source_dp
2025-08-14T21:17:25.8053092Z         ... )  # The creation of a new iterator invalidates `it1`
2025-08-14T21:17:25.8053450Z         >>> next(it2)
2025-08-14T21:17:25.8053689Z         0
2025-08-14T21:17:25.8053981Z         >>> next(it1)  # Further usage of `it1` will raise a `RunTimeError`
2025-08-14T21:17:25.8054327Z 
2025-08-14T21:17:25.8054577Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8055003Z 
2025-08-14T21:17:25.8299016Z msg = Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=375.
2025-08-14T21:17:25.8300118Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8300547Z 
2025-08-14T21:17:25.8301217Z Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``).
2025-08-14T21:17:25.8302287Z 
2025-08-14T21:17:25.8302475Z A list of the child DataPipes is returned from this operation.
2025-08-14T21:17:25.8302791Z 
2025-08-14T21:17:25.8302873Z Args:
2025-08-14T21:17:25.8303128Z     datapipe: Iterable DataPipe being filtered
2025-08-14T21:17:25.8303553Z     num_instances: number of instances of the DataPipe to create
2025-08-14T21:17:25.8304271Z     classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None``
2025-08-14T21:17:25.8305470Z     drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None``
2025-08-14T21:17:25.8306576Z     buffer_size: this defines the maximum number of inputs that the buffer can hold across all child
2025-08-14T21:17:25.8307197Z         DataPipes while waiting for their values to be yielded.
2025-08-14T21:17:25.8307652Z         Defaults to ``1000``. Use ``-1`` for the unlimited buffer.
2025-08-14T21:17:25.8307954Z 
2025-08-14T21:17:25.8308043Z Examples:
2025-08-14T21:17:25.8308293Z     >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:25.8308692Z     >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:25.8309305Z     >>> def odd_or_even(n):
2025-08-14T21:17:25.8309593Z     ...     return n % 2
2025-08-14T21:17:25.8309880Z     >>> source_dp = IterableWrapper(range(5))
2025-08-14T21:17:25.8310334Z     >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even)
2025-08-14T21:17:25.8310765Z     >>> list(dp1)
2025-08-14T21:17:25.8310998Z     [0, 2, 4]
2025-08-14T21:17:25.8311202Z     >>> list(dp2)
2025-08-14T21:17:25.8311506Z     [1, 3]
2025-08-14T21:17:25.8311869Z     >>> # It can also filter out any element that gets `None` from the `classifier_fn`
2025-08-14T21:17:25.8312326Z     >>> def odd_or_even_no_zero(n):
2025-08-14T21:17:25.8312647Z     ...     return n % 2 if n != 0 else None
2025-08-14T21:17:25.8312977Z     >>> dp1, dp2 = source_dp.demux(
2025-08-14T21:17:25.8313624Z     ...     num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True
2025-08-14T21:17:25.8314068Z     ... )
2025-08-14T21:17:25.8314281Z     >>> list(dp1)
2025-08-14T21:17:25.8314501Z     [2, 4]
2025-08-14T21:17:25.8314714Z     >>> list(dp2)
2025-08-14T21:17:25.8314944Z     [1, 3]
2025-08-14T21:17:25.8315062Z 
2025-08-14T21:17:25.8315327Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8315696Z 
2025-08-14T21:17:25.8316393Z msg = Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=594.
2025-08-14T21:17:25.8317457Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8317836Z 
2025-08-14T21:17:25.8318161Z Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``).
2025-08-14T21:17:25.8318586Z 
2025-08-14T21:17:25.8318950Z As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration,
2025-08-14T21:17:25.8319597Z and so on. It ends when the shortest input DataPipe is exhausted.
2025-08-14T21:17:25.8319914Z 
2025-08-14T21:17:25.8319999Z Args:
2025-08-14T21:17:25.8320534Z     datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted
2025-08-14T21:17:25.8321104Z 
2025-08-14T21:17:25.8321206Z Example:
2025-08-14T21:17:25.8321491Z     >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:25.8321913Z     >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:25.8322299Z     >>> dp1, dp2, dp3 = (
2025-08-14T21:17:25.8322578Z     ...     IterableWrapper(range(3)),
2025-08-14T21:17:25.8322918Z     ...     IterableWrapper(range(10, 15)),
2025-08-14T21:17:25.8323262Z     ...     IterableWrapper(range(20, 25)),
2025-08-14T21:17:25.8323563Z     ... )
2025-08-14T21:17:25.8323788Z     >>> list(dp1.mux(dp2, dp3))
2025-08-14T21:17:25.8324077Z     [0, 10, 20, 1, 11, 21, 2, 12, 22]
2025-08-14T21:17:25.8324270Z 
2025-08-14T21:17:25.8324522Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8324902Z 
2025-08-14T21:17:25.8325558Z msg = Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=665.
2025-08-14T21:17:25.8326590Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8326966Z 
2025-08-14T21:17:25.8327279Z Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``).
2025-08-14T21:17:25.8327699Z 
2025-08-14T21:17:25.8327937Z The output is stopped as soon as the shortest input DataPipe is exhausted.
2025-08-14T21:17:25.8328283Z 
2025-08-14T21:17:25.8328365Z Args:
2025-08-14T21:17:25.8328631Z     *datapipes: Iterable DataPipes being aggregated
2025-08-14T21:17:25.8328889Z 
2025-08-14T21:17:25.8328983Z Example:
2025-08-14T21:17:25.8329222Z     >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:25.8329634Z     >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:25.8330021Z     >>> dp1, dp2, dp3 = (
2025-08-14T21:17:25.8330296Z     ...     IterableWrapper(range(5)),
2025-08-14T21:17:25.8330639Z     ...     IterableWrapper(range(10, 15)),
2025-08-14T21:17:25.8330987Z     ...     IterableWrapper(range(20, 25)),
2025-08-14T21:17:25.8331302Z     ... )
2025-08-14T21:17:25.8331521Z     >>> list(dp1.zip(dp2, dp3))
2025-08-14T21:17:25.8331844Z     [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)]
2025-08-14T21:17:25.8332090Z 
2025-08-14T21:17:25.8332353Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8332719Z 
2025-08-14T21:17:25.8337617Z msg = Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18.
2025-08-14T21:17:25.8338863Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8339254Z 
2025-08-14T21:17:25.8339626Z Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``).
2025-08-14T21:17:25.8340129Z 
2025-08-14T21:17:25.8340210Z Args:
2025-08-14T21:17:25.8340497Z     datapipe: Iterable datapipe that provides pathnames
2025-08-14T21:17:25.8340946Z     mode: An optional string that specifies the mode in which
2025-08-14T21:17:25.8341456Z         the file is opened by ``open()``. It defaults to ``r``, other options are
2025-08-14T21:17:25.8341952Z         ``b`` for reading in binary mode and ``t`` for text mode.
2025-08-14T21:17:25.8342417Z     encoding: An optional string that specifies the encoding of the
2025-08-14T21:17:25.8342999Z         underlying file. It defaults to ``None`` to match the default encoding of ``open``.
2025-08-14T21:17:25.8343508Z     length: Nominal length of the datapipe
2025-08-14T21:17:25.8343734Z 
2025-08-14T21:17:25.8343832Z Note:
2025-08-14T21:17:25.8344206Z     The opened file handles will be closed by Python's GC periodically. Users can choose
2025-08-14T21:17:25.8344703Z     to close them explicitly.
2025-08-14T21:17:25.8344890Z 
2025-08-14T21:17:25.8344989Z Example:
2025-08-14T21:17:25.8345196Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.8345498Z     >>> from torchdata.datapipes.iter import (
2025-08-14T21:17:25.8345864Z     ...     FileLister,
2025-08-14T21:17:25.8346104Z     ...     FileOpener,
2025-08-14T21:17:25.8346398Z     ...     StreamReader,
2025-08-14T21:17:25.8346650Z     ... )
2025-08-14T21:17:25.8346971Z     >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt"))
2025-08-14T21:17:25.8347407Z     >>> dp = FileOpener(dp)
2025-08-14T21:17:25.8347687Z     >>> dp = StreamReader(dp)
2025-08-14T21:17:25.8347964Z     >>> list(dp)
2025-08-14T21:17:25.8348187Z     [('./abc.txt', 'abc')]
2025-08-14T21:17:25.8348364Z 
2025-08-14T21:17:25.8348626Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8348996Z 
2025-08-14T21:17:25.8377217Z msg = Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155.
2025-08-14T21:17:25.8378266Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:25.8378645Z 
2025-08-14T21:17:25.8379058Z Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``.
2025-08-14T21:17:25.8379596Z 
2025-08-14T21:17:25.8379702Z (functional name: ``groupby``).
2025-08-14T21:17:25.8379905Z 
2025-08-14T21:17:25.8380305Z The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group
2025-08-14T21:17:25.8381098Z will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full,
2025-08-14T21:17:25.8381822Z the DataPipe will yield the largest batch with the same key, provided that its size is larger
2025-08-14T21:17:25.8382555Z than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``.
2025-08-14T21:17:25.8383001Z 
2025-08-14T21:17:25.8383379Z After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity
2025-08-14T21:17:25.8384199Z will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``.
2025-08-14T21:17:25.8384636Z 
2025-08-14T21:17:25.8384728Z Args:
2025-08-14T21:17:25.8384969Z     datapipe: Iterable datapipe to be grouped
2025-08-14T21:17:25.8385488Z     group_key_fn: Function used to generate group key from the data of the source datapipe
2025-08-14T21:17:25.8386120Z     keep_key: Option to yield the matching key along with the items in a tuple,
2025-08-14T21:17:25.8386640Z         resulting in `(key, [items])` otherwise returning [items]
2025-08-14T21:17:25.8387087Z     buffer_size: The size of buffer for ungrouped data
2025-08-14T21:17:25.8387746Z     group_size: The max size of each group, a batch is yielded as soon as it reaches this size
2025-08-14T21:17:25.8388488Z     guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full
2025-08-14T21:17:25.8389293Z     drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer
2025-08-14T21:17:25.8389878Z         when the buffer is full
2025-08-14T21:17:25.8390067Z 
2025-08-14T21:17:25.8390163Z Example:
2025-08-14T21:17:25.8390363Z     >>> import os
2025-08-14T21:17:25.8390604Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:25.8390952Z     >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:25.8391334Z     >>> def group_fn(file):
2025-08-14T21:17:25.8391746Z     ...     return os.path.basename(file).split(".")[0]
2025-08-14T21:17:25.8392122Z     >>> source_dp = IterableWrapper(
2025-08-14T21:17:25.8392496Z     ...     ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"]
2025-08-14T21:17:25.8392853Z     ... )
2025-08-14T21:17:25.8393131Z     >>> dp0 = source_dp.groupby(group_key_fn=group_fn)
2025-08-14T21:17:25.8393485Z     >>> list(dp0)
2025-08-14T21:17:25.8393780Z     [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']]
2025-08-14T21:17:25.8394252Z     >>> # A group is yielded as soon as its size equals to `group_size`
2025-08-14T21:17:25.8394747Z     >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2)
2025-08-14T21:17:25.8395207Z     >>> list(dp1)
2025-08-14T21:17:25.8395519Z     [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']]
2025-08-14T21:17:25.8396148Z     >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size`
2025-08-14T21:17:25.8396728Z     >>> dp2 = source_dp.groupby(
2025-08-14T21:17:25.8397026Z     ...     group_key_fn=group_fn,
2025-08-14T21:17:25.8397335Z     ...     buffer_size=3,
2025-08-14T21:17:25.8397608Z     ...     group_size=3,
2025-08-14T21:17:25.8397878Z     ...     guaranteed_group_size=2,
2025-08-14T21:17:25.8398174Z     ... )
2025-08-14T21:17:25.8398387Z     >>> list(dp2)
2025-08-14T21:17:25.8398685Z     [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']]
2025-08-14T21:17:25.8398973Z 
2025-08-14T21:17:25.8399227Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:25.8399596Z 
2025-08-14T21:17:26.1839138Z gathering tests
2025-08-14T21:17:26.1850833Z running 732 test(s)
2025-08-14T21:17:26.1893781Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0, line 1082 <- wrt source file
2025-08-14T21:17:26.1901982Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0
2025-08-14T21:17:26.1903260Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0, line 1118 <- wrt source file
2025-08-14T21:17:26.1907210Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0
2025-08-14T21:17:26.1908926Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0, line 1203 <- wrt source file
2025-08-14T21:17:26.1910725Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0
2025-08-14T21:17:26.1912523Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1252 <- wrt source file
2025-08-14T21:17:26.1914026Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0
2025-08-14T21:17:26.1915280Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0, line 1289 <- wrt source file
2025-08-14T21:17:26.1916932Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0
2025-08-14T21:17:26.1918378Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1444 <- wrt source file
2025-08-14T21:17:26.1920021Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0
2025-08-14T21:17:26.1921522Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0, line 2567 <- wrt source file
2025-08-14T21:17:26.1922681Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0
2025-08-14T21:17:26.1923905Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2840 <- wrt source file
2025-08-14T21:17:26.1925275Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0
2025-08-14T21:17:26.1926593Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0, line 15 <- wrt source file
2025-08-14T21:17:26.1927932Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0
2025-08-14T21:17:26.1929316Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0, line 5 <- wrt source file
2025-08-14T21:17:26.1930748Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0
2025-08-14T21:17:26.1931965Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file
2025-08-14T21:17:26.1933109Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0
2025-08-14T21:17:26.1934190Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file
2025-08-14T21:17:26.1935285Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0
2025-08-14T21:17:26.1936401Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file
2025-08-14T21:17:26.2337090Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0
2025-08-14T21:17:26.2338897Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file
2025-08-14T21:17:26.2340224Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0
2025-08-14T21:17:26.2341477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 649 <- wrt source file
2025-08-14T21:17:26.2349291Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0
2025-08-14T21:17:26.2350604Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 706 <- wrt source file
2025-08-14T21:17:26.2369068Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0
2025-08-14T21:17:26.2370366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1333 <- wrt source file
2025-08-14T21:17:26.2479571Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0
2025-08-14T21:17:26.2483328Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1378 <- wrt source file
2025-08-14T21:17:26.2488293Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0
2025-08-14T21:17:26.2489426Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0, line 1451 <- wrt source file
2025-08-14T21:17:26.2495763Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0
2025-08-14T21:17:26.2496936Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1481 <- wrt source file
2025-08-14T21:17:26.2501759Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0
2025-08-14T21:17:26.2502951Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file
2025-08-14T21:17:26.2524093Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0
2025-08-14T21:17:26.2525308Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file
2025-08-14T21:17:26.2531118Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0
2025-08-14T21:17:26.2532320Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file
2025-08-14T21:17:26.2534195Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0
2025-08-14T21:17:26.2535360Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0, line 193 <- wrt source file
2025-08-14T21:17:26.2547279Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0
2025-08-14T21:17:26.2548385Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0, line 307 <- wrt source file
2025-08-14T21:17:26.2565624Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0
2025-08-14T21:17:26.2566828Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 1041 <- wrt source file
2025-08-14T21:17:26.2578027Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0
2025-08-14T21:17:26.2579258Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0, line 1316 <- wrt source file
2025-08-14T21:17:26.2589271Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0
2025-08-14T21:17:26.2590434Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0, line 1400 <- wrt source file
2025-08-14T21:17:26.2596937Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0
2025-08-14T21:17:26.2598122Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0, line 1434 <- wrt source file
2025-08-14T21:17:26.2607219Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0
2025-08-14T21:17:26.2608343Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0, line 1490 <- wrt source file
2025-08-14T21:17:26.2622588Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0
2025-08-14T21:17:26.2623728Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0, line 1531 <- wrt source file
2025-08-14T21:17:26.2639558Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0
2025-08-14T21:17:26.2640719Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0, line 1569 <- wrt source file
2025-08-14T21:17:26.2657493Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0
2025-08-14T21:17:26.2658623Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0, line 1609 <- wrt source file
2025-08-14T21:17:26.2679427Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0
2025-08-14T21:17:26.2680540Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0, line 1784 <- wrt source file
2025-08-14T21:17:26.2712485Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0
2025-08-14T21:17:26.2713620Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0, line 1952 <- wrt source file
2025-08-14T21:17:26.2739563Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0
2025-08-14T21:17:26.2741727Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0, line 2052 <- wrt source file
2025-08-14T21:17:26.2743470Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0
2025-08-14T21:17:26.2744602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0, line 2153 <- wrt source file
2025-08-14T21:17:26.2745737Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0
2025-08-14T21:17:26.2747414Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0, line 473 <- wrt source file
2025-08-14T21:17:26.2748546Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0
2025-08-14T21:17:26.2749558Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0, line 533 <- wrt source file
2025-08-14T21:17:26.2750566Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0
2025-08-14T21:17:26.2751726Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0, line 153 <- wrt source file
2025-08-14T21:17:26.2752912Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0
2025-08-14T21:17:26.2754134Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 247 <- wrt source file
2025-08-14T21:17:26.2773753Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0
2025-08-14T21:17:26.2774983Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0, line 307 <- wrt source file
2025-08-14T21:17:26.2778290Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0
2025-08-14T21:17:26.2779394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0, line 512 <- wrt source file
2025-08-14T21:17:26.2799506Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0
2025-08-14T21:17:26.2800572Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0, line 618 <- wrt source file
2025-08-14T21:17:26.2815601Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0
2025-08-14T21:17:26.2817025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0, line 799 <- wrt source file
2025-08-14T21:17:26.2818223Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0
2025-08-14T21:17:26.2819371Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0, line 867 <- wrt source file
2025-08-14T21:17:26.2820557Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0
2025-08-14T21:17:26.2821773Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0, line 1232 <- wrt source file
2025-08-14T21:17:26.2907191Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0
2025-08-14T21:17:26.2908362Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0, line 1321 <- wrt source file
2025-08-14T21:17:26.3052590Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0
2025-08-14T21:17:26.3053783Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0, line 116 <- wrt source file
2025-08-14T21:17:26.3058790Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0
2025-08-14T21:17:26.3060033Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0, line 422 <- wrt source file
2025-08-14T21:17:26.3096425Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0
2025-08-14T21:17:26.3097657Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0, line 1577 <- wrt source file
2025-08-14T21:17:26.3099598Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0
2025-08-14T21:17:26.3100828Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0, line 1712 <- wrt source file
2025-08-14T21:17:26.3102767Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0
2025-08-14T21:17:26.3104044Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1960 <- wrt source file
2025-08-14T21:17:26.3129448Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0
2025-08-14T21:17:26.3130686Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0, line 1979 <- wrt source file
2025-08-14T21:17:26.3136565Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0
2025-08-14T21:17:26.3137977Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file
2025-08-14T21:17:26.3139524Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0
2025-08-14T21:17:26.3141577Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0, line 299 <- wrt source file
2025-08-14T21:17:26.3142844Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0
2025-08-14T21:17:26.3144245Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0, line 324 <- wrt source file
2025-08-14T21:17:26.3146573Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0
2025-08-14T21:17:26.3147904Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0, line 400 <- wrt source file
2025-08-14T21:17:26.3149461Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0
2025-08-14T21:17:26.3150755Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0, line 472 <- wrt source file
2025-08-14T21:17:26.3152070Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0
2025-08-14T21:17:26.3153239Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0, line 950 <- wrt source file
2025-08-14T21:17:26.3154375Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0
2025-08-14T21:17:26.3155662Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file
2025-08-14T21:17:26.3156851Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0
2025-08-14T21:17:26.3158063Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 320 <- wrt source file
2025-08-14T21:17:26.3159346Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0
2025-08-14T21:17:26.3160575Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0, line 357 <- wrt source file
2025-08-14T21:17:26.3162667Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0
2025-08-14T21:17:26.3163952Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 113 <- wrt source file
2025-08-14T21:17:26.3168365Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0
2025-08-14T21:17:26.3170649Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0, line 249 <- wrt source file
2025-08-14T21:17:26.3171930Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0
2025-08-14T21:17:26.3173230Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 125 <- wrt source file
2025-08-14T21:17:26.3174484Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0
2025-08-14T21:17:26.3175736Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 181 <- wrt source file
2025-08-14T21:17:27.2102765Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0
2025-08-14T21:17:27.2104045Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 411 <- wrt source file
2025-08-14T21:17:27.2105831Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::wrap_numpy:0
2025-08-14T21:17:27.2107073Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_compiling:0, line 443 <- wrt source file
2025-08-14T21:17:27.2108321Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_compiling:0
2025-08-14T21:17:27.2110223Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0, line 464 <- wrt source file
2025-08-14T21:17:27.2111626Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0
2025-08-14T21:17:27.2113166Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_exporting:0, line 482 <- wrt source file
2025-08-14T21:17:27.2114891Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_exporting:0
2025-08-14T21:17:27.2116845Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 497 <- wrt source file
2025-08-14T21:17:27.2118739Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0
2025-08-14T21:17:27.2120470Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 512 <- wrt source file
2025-08-14T21:17:27.2122353Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0
2025-08-14T21:17:27.2123900Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1760 <- wrt source file
2025-08-14T21:17:27.2125538Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py::_compile_kernel:0
2025-08-14T21:17:27.2126672Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::save:0, line 345 <- wrt source file
2025-08-14T21:17:27.2127825Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::save:0
2025-08-14T21:17:27.2128951Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::load:0, line 415 <- wrt source file
2025-08-14T21:17:27.2130068Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::load:0
2025-08-14T21:17:27.2131249Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::register_dataclass:0, line 572 <- wrt source file
2025-08-14T21:17:27.2132655Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/__init__.py::register_dataclass:0
2025-08-14T21:17:27.2133940Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 197 <- wrt source file
2025-08-14T21:17:27.2135268Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0
2025-08-14T21:17:27.2136567Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 261 <- wrt source file
2025-08-14T21:17:27.2137871Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.set_exception:0
2025-08-14T21:17:27.2139097Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::collect_all:0, line 295 <- wrt source file
2025-08-14T21:17:27.2140454Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::collect_all:0
2025-08-14T21:17:27.2141591Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/__init__.py::annotate:0, line 147 <- wrt source file
2025-08-14T21:17:27.2142732Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/__init__.py::annotate:0
2025-08-14T21:17:27.2143976Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0, line 22 <- wrt source file
2025-08-14T21:17:27.2155536Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0
2025-08-14T21:17:27.2156792Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::as_nested_tensor:0, line 61 <- wrt source file
2025-08-14T21:17:27.2196082Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::as_nested_tensor:0
2025-08-14T21:17:27.2198477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor:0, line 240 <- wrt source file
2025-08-14T21:17:27.2200882Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor:0
2025-08-14T21:17:27.2203254Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::narrow:0, line 315 <- wrt source file
2025-08-14T21:17:27.2282152Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::narrow:0
2025-08-14T21:17:27.2284569Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0, line 405 <- wrt source file
2025-08-14T21:17:27.2302114Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0
2025-08-14T21:17:27.2304581Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::masked_select:0, line 481 <- wrt source file
2025-08-14T21:17:27.2319497Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::masked_select:0
2025-08-14T21:17:27.2322044Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0, line 475 <- wrt source file
2025-08-14T21:17:27.2334529Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0
2025-08-14T21:17:27.2337169Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0, line 349 <- wrt source file
2025-08-14T21:17:27.2339814Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0
2025-08-14T21:17:27.2342348Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/eval_frame.py::fullgraph_capture:0, line 2328 <- wrt source file
2025-08-14T21:17:27.2344925Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/eval_frame.py::fullgraph_capture:0
2025-08-14T21:17:27.2347622Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0, line 322 <- wrt source file
2025-08-14T21:17:27.2350513Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0
2025-08-14T21:17:27.2353366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0, line 1386 <- wrt source file
2025-08-14T21:17:27.2356424Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0
2025-08-14T21:17:27.2359424Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0, line 157 <- wrt source file
2025-08-14T21:17:27.2362595Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0
2025-08-14T21:17:27.2365391Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/aot_autograd.py::aot_function:0, line 768 <- wrt source file
2025-08-14T21:17:27.2648993Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/aot_autograd.py::aot_function:0
2025-08-14T21:17:27.2651707Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0, line 184 <- wrt source file
2025-08-14T21:17:27.2654541Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0
2025-08-14T21:17:27.2657125Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::vjp:0, line 233 <- wrt source file
2025-08-14T21:17:27.2691306Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::vjp:0
2025-08-14T21:17:27.2693869Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacrev:0, line 475 <- wrt source file
2025-08-14T21:17:27.2751354Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacrev:0
2025-08-14T21:17:27.2753916Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jvp:0, line 1023 <- wrt source file
2025-08-14T21:17:27.3226727Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jvp:0
2025-08-14T21:17:27.3229227Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0, line 1181 <- wrt source file
2025-08-14T21:17:27.3294502Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0
2025-08-14T21:17:27.3297024Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::hessian:0, line 1341 <- wrt source file
2025-08-14T21:17:27.3313466Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::hessian:0
2025-08-14T21:17:27.3316067Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1505 <- wrt source file
2025-08-14T21:17:27.3318792Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0
2025-08-14T21:17:27.3321390Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1704 <- wrt source file
2025-08-14T21:17:27.3494935Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0
2025-08-14T21:17:27.3497565Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file
2025-08-14T21:17:27.3500282Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0
2025-08-14T21:17:27.3503126Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file
2025-08-14T21:17:27.3505620Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0
2025-08-14T21:17:27.3508395Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1131 <- wrt source file
2025-08-14T21:17:27.3511768Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0
2025-08-14T21:17:27.3514813Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0, line 1186 <- wrt source file
2025-08-14T21:17:27.3517897Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0
2025-08-14T21:17:27.3520779Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 133 <- wrt source file
2025-08-14T21:17:27.3523651Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0
2025-08-14T21:17:27.3526638Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 269 <- wrt source file
2025-08-14T21:17:27.3529728Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0
2025-08-14T21:17:27.3532317Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 105 <- wrt source file
2025-08-14T21:17:27.3534690Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0
2025-08-14T21:17:27.3537194Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file
2025-08-14T21:17:27.3539955Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0
2025-08-14T21:17:27.3542437Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0, line 77 <- wrt source file
2025-08-14T21:17:27.3544764Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0
2025-08-14T21:17:27.3547072Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 155 <- wrt source file
2025-08-14T21:17:27.3549435Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0
2025-08-14T21:17:27.3551953Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0, line 423 <- wrt source file
2025-08-14T21:17:27.3554548Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0
2025-08-14T21:17:27.3557147Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/codecache.py::WritableTempFile:0, line 371 <- wrt source file
2025-08-14T21:17:27.3559755Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/codecache.py::WritableTempFile:0
2025-08-14T21:17:27.3562624Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1501 <- wrt source file
2025-08-14T21:17:27.3565615Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0
2025-08-14T21:17:27.3568478Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 3349 <- wrt source file
2025-08-14T21:17:27.3571278Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0
2025-08-14T21:17:27.3574089Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0, line 45 <- wrt source file
2025-08-14T21:17:27.3577041Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0
2025-08-14T21:17:27.3579637Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0, line 98 <- wrt source file
2025-08-14T21:17:27.4083595Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0
2025-08-14T21:17:27.4086190Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 238 <- wrt source file
2025-08-14T21:17:27.4170328Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0
2025-08-14T21:17:27.4173100Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 307 <- wrt source file
2025-08-14T21:17:27.4175877Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0
2025-08-14T21:17:27.4178639Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0, line 541 <- wrt source file
2025-08-14T21:17:27.4339641Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0
2025-08-14T21:17:27.4341078Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 709 <- wrt source file
2025-08-14T21:17:27.4505238Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0
2025-08-14T21:17:27.4506829Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 795 <- wrt source file
2025-08-14T21:17:27.4508470Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0
2025-08-14T21:17:27.4510022Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 230 <- wrt source file
2025-08-14T21:17:27.4511506Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0
2025-08-14T21:17:27.4512898Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file
2025-08-14T21:17:27.4585215Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0
2025-08-14T21:17:27.4586539Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 51 <- wrt source file
2025-08-14T21:17:27.4591741Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0
2025-08-14T21:17:27.4593085Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0, line 459 <- wrt source file
2025-08-14T21:17:27.4594306Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0
2025-08-14T21:17:27.4595527Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0, line 171 <- wrt source file
2025-08-14T21:17:27.4643626Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0
2025-08-14T21:17:27.4644916Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file
2025-08-14T21:17:27.4700068Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0
2025-08-14T21:17:27.4701405Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file
2025-08-14T21:17:27.4702749Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0
2025-08-14T21:17:27.4704225Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file
2025-08-14T21:17:27.4746139Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0
2025-08-14T21:17:27.4747492Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file
2025-08-14T21:17:27.4750163Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0
2025-08-14T21:17:27.4751602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file
2025-08-14T21:17:27.4754854Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0
2025-08-14T21:17:27.4756610Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file
2025-08-14T21:17:27.4757859Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0
2025-08-14T21:17:27.4759093Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file
2025-08-14T21:17:27.4761237Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0
2025-08-14T21:17:27.4762831Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file
2025-08-14T21:17:27.4764379Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0
2025-08-14T21:17:27.4766028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file
2025-08-14T21:17:27.4767567Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0
2025-08-14T21:17:27.4768899Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 30 <- wrt source file
2025-08-14T21:17:27.4770631Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0
2025-08-14T21:17:27.4772194Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file
2025-08-14T21:17:27.4773875Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0
2025-08-14T21:17:27.4775455Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file
2025-08-14T21:17:27.4777011Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0
2025-08-14T21:17:27.4778581Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file
2025-08-14T21:17:27.4780217Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0
2025-08-14T21:17:27.4781784Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file
2025-08-14T21:17:27.4783435Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0
2025-08-14T21:17:27.4784861Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 30 <- wrt source file
2025-08-14T21:17:27.4788826Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0
2025-08-14T21:17:27.4790236Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file
2025-08-14T21:17:27.4820380Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0
2025-08-14T21:17:27.4822910Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 211 <- wrt source file
2025-08-14T21:17:27.4825180Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0
2025-08-14T21:17:27.4826748Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0, line 283 <- wrt source file
2025-08-14T21:17:27.4828053Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0
2025-08-14T21:17:27.4829364Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 359 <- wrt source file
2025-08-14T21:17:27.4831125Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0
2025-08-14T21:17:27.4832512Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file
2025-08-14T21:17:27.4833967Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0
2025-08-14T21:17:27.4835639Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file
2025-08-14T21:17:27.4837702Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0
2025-08-14T21:17:27.4839492Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file
2025-08-14T21:17:27.4841492Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0
2025-08-14T21:17:27.4843510Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 124 <- wrt source file
2025-08-14T21:17:27.4845179Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0
2025-08-14T21:17:27.4846634Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 209 <- wrt source file
2025-08-14T21:17:27.4848262Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0
2025-08-14T21:17:27.4850146Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 296 <- wrt source file
2025-08-14T21:17:27.4852128Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0
2025-08-14T21:17:27.4853997Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 378 <- wrt source file
2025-08-14T21:17:27.4855544Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0
2025-08-14T21:17:27.4857031Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 460 <- wrt source file
2025-08-14T21:17:27.4858556Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0
2025-08-14T21:17:27.4860009Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file
2025-08-14T21:17:27.4861462Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0
2025-08-14T21:17:27.4862845Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 515 <- wrt source file
2025-08-14T21:17:27.4864232Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0
2025-08-14T21:17:27.4865585Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 801 <- wrt source file
2025-08-14T21:17:27.4867583Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0
2025-08-14T21:17:27.4870307Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1206 <- wrt source file
2025-08-14T21:17:27.4873203Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0
2025-08-14T21:17:27.4875980Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1273 <- wrt source file
2025-08-14T21:17:27.4878822Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0
2025-08-14T21:17:27.4881714Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1326 <- wrt source file
2025-08-14T21:17:27.4884540Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0
2025-08-14T21:17:27.4887244Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file
2025-08-14T21:17:27.4890004Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0
2025-08-14T21:17:27.4892591Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 505 <- wrt source file
2025-08-14T21:17:27.4895203Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0
2025-08-14T21:17:27.4897760Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 635 <- wrt source file
2025-08-14T21:17:27.4900354Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0
2025-08-14T21:17:27.4903027Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 892 <- wrt source file
2025-08-14T21:17:27.4905911Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0
2025-08-14T21:17:27.4908691Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1014 <- wrt source file
2025-08-14T21:17:27.4911774Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0
2025-08-14T21:17:27.4914562Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1140 <- wrt source file
2025-08-14T21:17:27.4917385Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0
2025-08-14T21:17:27.4920187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file
2025-08-14T21:17:27.4923095Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0
2025-08-14T21:17:27.4925964Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file
2025-08-14T21:17:27.4928940Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0
2025-08-14T21:17:27.4931929Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file
2025-08-14T21:17:27.4935080Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0
2025-08-14T21:17:27.4938128Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file
2025-08-14T21:17:27.4941202Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0
2025-08-14T21:17:27.4944112Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 138 <- wrt source file
2025-08-14T21:17:27.4946775Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0
2025-08-14T21:17:27.4949833Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file
2025-08-14T21:17:27.4953477Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0
2025-08-14T21:17:27.4956612Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file
2025-08-14T21:17:27.5023385Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0
2025-08-14T21:17:27.5026368Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file
2025-08-14T21:17:27.5029466Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0
2025-08-14T21:17:27.5032904Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 176 <- wrt source file
2025-08-14T21:17:27.5036363Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0
2025-08-14T21:17:27.5039133Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 31 <- wrt source file
2025-08-14T21:17:27.5042394Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0
2025-08-14T21:17:27.5045503Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 76 <- wrt source file
2025-08-14T21:17:27.5048543Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0
2025-08-14T21:17:27.5051495Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 130 <- wrt source file
2025-08-14T21:17:27.5054457Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0
2025-08-14T21:17:27.5057477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 163 <- wrt source file
2025-08-14T21:17:27.5060609Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0
2025-08-14T21:17:27.5063414Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file
2025-08-14T21:17:27.5066362Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0
2025-08-14T21:17:27.5069253Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file
2025-08-14T21:17:27.5072283Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0
2025-08-14T21:17:27.5075143Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file
2025-08-14T21:17:27.5077742Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0
2025-08-14T21:17:27.5080885Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file
2025-08-14T21:17:27.5083898Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0
2025-08-14T21:17:27.5086575Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file
2025-08-14T21:17:27.5089333Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0
2025-08-14T21:17:27.5091992Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file
2025-08-14T21:17:27.5094671Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0
2025-08-14T21:17:27.5097433Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file
2025-08-14T21:17:27.5100530Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0
2025-08-14T21:17:27.5103564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file
2025-08-14T21:17:27.5106772Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0
2025-08-14T21:17:27.5109905Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file
2025-08-14T21:17:27.5112786Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0
2025-08-14T21:17:27.5115554Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file
2025-08-14T21:17:27.5118406Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0
2025-08-14T21:17:27.5121148Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file
2025-08-14T21:17:27.5123924Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0
2025-08-14T21:17:27.5126610Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 172 <- wrt source file
2025-08-14T21:17:27.5129296Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0
2025-08-14T21:17:27.5131938Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 544 <- wrt source file
2025-08-14T21:17:27.5134687Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0
2025-08-14T21:17:27.5137390Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 566 <- wrt source file
2025-08-14T21:17:27.5140372Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0
2025-08-14T21:17:27.5143060Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 580 <- wrt source file
2025-08-14T21:17:27.5145757Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0
2025-08-14T21:17:27.5148394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 602 <- wrt source file
2025-08-14T21:17:27.5151076Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0
2025-08-14T21:17:27.5153743Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 729 <- wrt source file
2025-08-14T21:17:27.5156396Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0
2025-08-14T21:17:27.5159264Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file
2025-08-14T21:17:27.5162457Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0
2025-08-14T21:17:27.5165733Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0, line 102 <- wrt source file
2025-08-14T21:17:27.5168898Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0
2025-08-14T21:17:27.5172116Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0, line 148 <- wrt source file
2025-08-14T21:17:27.5175247Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0
2025-08-14T21:17:27.5178284Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0, line 188 <- wrt source file
2025-08-14T21:17:27.5181353Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0
2025-08-14T21:17:27.5184485Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0, line 436 <- wrt source file
2025-08-14T21:17:27.5187713Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0
2025-08-14T21:17:27.5190548Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0, line 28 <- wrt source file
2025-08-14T21:17:27.5193215Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0
2025-08-14T21:17:27.5195663Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file
2025-08-14T21:17:27.5198096Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0
2025-08-14T21:17:27.5200487Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0, line 151 <- wrt source file
2025-08-14T21:17:27.5203081Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0
2025-08-14T21:17:27.5205499Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0, line 187 <- wrt source file
2025-08-14T21:17:27.5207943Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0
2025-08-14T21:17:27.5210665Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0, line 71 <- wrt source file
2025-08-14T21:17:27.5213527Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0
2025-08-14T21:17:27.5216308Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0, line 115 <- wrt source file
2025-08-14T21:17:27.5219126Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0
2025-08-14T21:17:27.5221848Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0, line 167 <- wrt source file
2025-08-14T21:17:27.5224518Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0
2025-08-14T21:17:27.5227487Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0, line 214 <- wrt source file
2025-08-14T21:17:27.5230465Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0
2025-08-14T21:17:27.5233441Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0, line 243 <- wrt source file
2025-08-14T21:17:27.5236375Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0
2025-08-14T21:17:27.5238983Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::Function:0, line 485 <- wrt source file
2025-08-14T21:17:27.5241382Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::Function:0
2025-08-14T21:17:27.5243705Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vjp:0, line 293 <- wrt source file
2025-08-14T21:17:27.5246033Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vjp:0
2025-08-14T21:17:27.5248336Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jvp:0, line 395 <- wrt source file
2025-08-14T21:17:27.5250672Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jvp:0
2025-08-14T21:17:27.5253021Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0, line 630 <- wrt source file
2025-08-14T21:17:27.5255446Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0
2025-08-14T21:17:27.5257829Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0, line 894 <- wrt source file
2025-08-14T21:17:27.5260238Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0
2025-08-14T21:17:27.5262572Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0, line 1010 <- wrt source file
2025-08-14T21:17:27.5265034Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0
2025-08-14T21:17:27.5267322Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0, line 1109 <- wrt source file
2025-08-14T21:17:27.5269664Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0
2025-08-14T21:17:27.5271999Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0, line 50 <- wrt source file
2025-08-14T21:17:27.5274366Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0
2025-08-14T21:17:27.5276699Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0, line 108 <- wrt source file
2025-08-14T21:17:27.5279155Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0
2025-08-14T21:17:27.5281593Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0, line 166 <- wrt source file
2025-08-14T21:17:27.5284135Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0
2025-08-14T21:17:27.5286656Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0, line 238 <- wrt source file
2025-08-14T21:17:27.5289217Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0
2025-08-14T21:17:27.5291586Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0, line 53 <- wrt source file
2025-08-14T21:17:27.5293916Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0
2025-08-14T21:17:27.5296281Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0, line 110 <- wrt source file
2025-08-14T21:17:27.5298884Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0
2025-08-14T21:17:27.5301398Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 147 <- wrt source file
2025-08-14T21:17:27.5303978Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0
2025-08-14T21:17:27.5306506Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 283 <- wrt source file
2025-08-14T21:17:27.5309173Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0
2025-08-14T21:17:27.5311650Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::save_on_cpu:0, line 353 <- wrt source file
2025-08-14T21:17:27.5314000Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::save_on_cpu:0
2025-08-14T21:17:27.5316512Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0, line 410 <- wrt source file
2025-08-14T21:17:27.5319222Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0
2025-08-14T21:17:27.5321852Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0, line 487 <- wrt source file
2025-08-14T21:17:27.5324612Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0
2025-08-14T21:17:27.5327301Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0, line 753 <- wrt source file
2025-08-14T21:17:27.5330085Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0
2025-08-14T21:17:27.5332630Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0, line 182 <- wrt source file
2025-08-14T21:17:27.5334997Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0
2025-08-14T21:17:27.5337309Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0, line 880 <- wrt source file
2025-08-14T21:17:27.5339695Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0
2025-08-14T21:17:27.5342031Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0, line 953 <- wrt source file
2025-08-14T21:17:27.5344432Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0
2025-08-14T21:17:27.5346799Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 42 <- wrt source file
2025-08-14T21:17:27.5349219Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0
2025-08-14T21:17:27.5351633Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 58 <- wrt source file
2025-08-14T21:17:27.5354059Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0
2025-08-14T21:17:27.5356286Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0, line 85 <- wrt source file
2025-08-14T21:17:27.5358445Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0
2025-08-14T21:17:27.5360704Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file
2025-08-14T21:17:27.5363112Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0
2025-08-14T21:17:27.5365475Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file
2025-08-14T21:17:27.5367879Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1
2025-08-14T21:17:27.5370268Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file
2025-08-14T21:17:27.5372667Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2
2025-08-14T21:17:27.5375178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file
2025-08-14T21:17:27.5377872Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0
2025-08-14T21:17:27.5380307Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file
2025-08-14T21:17:27.5382583Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0
2025-08-14T21:17:27.5385065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0, line 431 <- wrt source file
2025-08-14T21:17:27.5387642Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0
2025-08-14T21:17:27.5390319Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0, line 976 <- wrt source file
2025-08-14T21:17:27.5393260Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0
2025-08-14T21:17:27.5396100Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0, line 1122 <- wrt source file
2025-08-14T21:17:27.5398798Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0
2025-08-14T21:17:27.5401644Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0, line 2574 <- wrt source file
2025-08-14T21:17:27.5404545Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0
2025-08-14T21:17:27.5407302Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2676 <- wrt source file
2025-08-14T21:17:27.5410313Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0
2025-08-14T21:17:27.5413072Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3143 <- wrt source file
2025-08-14T21:17:27.5415914Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0
2025-08-14T21:17:27.5418682Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3372 <- wrt source file
2025-08-14T21:17:27.5421470Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0
2025-08-14T21:17:27.5424245Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0, line 3474 <- wrt source file
2025-08-14T21:17:27.5427045Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0
2025-08-14T21:17:27.5429864Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0, line 3588 <- wrt source file
2025-08-14T21:17:27.5432851Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0
2025-08-14T21:17:27.5435697Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0, line 3711 <- wrt source file
2025-08-14T21:17:27.5438584Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0
2025-08-14T21:17:27.5441421Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0, line 3920 <- wrt source file
2025-08-14T21:17:27.5444348Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0
2025-08-14T21:17:27.5447353Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0, line 4058 <- wrt source file
2025-08-14T21:17:27.5450258Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0
2025-08-14T21:17:27.5452951Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::gather:0, line 4164 <- wrt source file
2025-08-14T21:17:27.5455574Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::gather:0
2025-08-14T21:17:27.5458128Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter:0, line 4249 <- wrt source file
2025-08-14T21:17:27.5460767Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter:0
2025-08-14T21:17:27.5463508Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0, line 4387 <- wrt source file
2025-08-14T21:17:27.5466450Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0
2025-08-14T21:17:27.5469258Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::monitored_barrier:0, line 4869 <- wrt source file
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2025-08-14T21:17:27.5476135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0, line 5411 <- wrt source file
2025-08-14T21:17:27.5478901Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0
2025-08-14T21:17:27.5481769Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups_by_enumeration:0, line 5505 <- wrt source file
2025-08-14T21:17:27.5484840Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups_by_enumeration:0
2025-08-14T21:17:27.5487430Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/run.py::__doc__:0, line 57 <- wrt source file
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2025-08-14T21:17:27.5492135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/autograd/__init__.py::context:0, line 47 <- wrt source file
2025-08-14T21:17:27.5494737Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/autograd/__init__.py::context:0
2025-08-14T21:17:27.5497552Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0, line 53 <- wrt source file
2025-08-14T21:17:27.5500615Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0
2025-08-14T21:17:27.5503440Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/contract.py::contract:0, line 66 <- wrt source file
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2025-08-14T21:17:27.5508856Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/replicate.py::replicate:0, line 190 <- wrt source file
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2025-08-14T21:17:27.5514765Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_composable/replicate_with_fsdp.py::replicate:0, line 247 <- wrt source file
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2025-08-14T21:17:27.5520815Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0, line 31 <- wrt source file
2025-08-14T21:17:27.5524150Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0
2025-08-14T21:17:27.5527320Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py::custom_sharded_op_impl:0, line 457 <- wrt source file
2025-08-14T21:17:27.5530481Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py::custom_sharded_op_impl:0
2025-08-14T21:17:27.5533564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/_ops/_common.py::_sharded_op_common:0, line 18 <- wrt source file
2025-08-14T21:17:27.5536805Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/_ops/_common.py::_sharded_op_common:0
2025-08-14T21:17:27.5539770Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::put:0, line 142 <- wrt source file
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2025-08-14T21:17:27.5545463Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::get:0, line 195 <- wrt source file
2025-08-14T21:17:27.5548329Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::get:0
2025-08-14T21:17:27.5551305Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::putmem_signal_block:0, line 268 <- wrt source file
2025-08-14T21:17:27.5554575Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::putmem_signal_block:0
2025-08-14T21:17:27.5557608Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::wait_until:0, line 323 <- wrt source file
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2025-08-14T21:17:27.5563628Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::signal_wait_until:0, line 386 <- wrt source file
2025-08-14T21:17:27.5566770Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::signal_wait_until:0
2025-08-14T21:17:27.5569760Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::signal_op:0, line 437 <- wrt source file
2025-08-14T21:17:27.5572732Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::signal_op:0
2025-08-14T21:17:27.5575713Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::fence:0, line 490 <- wrt source file
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2025-08-14T21:17:27.5581470Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::quiet:0, line 536 <- wrt source file
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2025-08-14T21:17:27.5587218Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::my_pe:0, line 580 <- wrt source file
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2025-08-14T21:17:27.5593002Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::n_pes:0, line 623 <- wrt source file
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2025-08-14T21:17:27.5598863Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::barrier_all:0, line 674 <- wrt source file
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2025-08-14T21:17:27.5604852Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::sync_all:0, line 720 <- wrt source file
2025-08-14T21:17:27.5607815Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::sync_all:0
2025-08-14T21:17:27.5610906Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::alltoall:0, line 759 <- wrt source file
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2025-08-14T21:17:27.5616810Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::broadcast:0, line 814 <- wrt source file
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2025-08-14T21:17:27.5622710Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::reduce:0, line 875 <- wrt source file
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2025-08-14T21:17:27.5628669Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::reduce_extern_wrapper:0, line 921 <- wrt source file
2025-08-14T21:17:27.5631987Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::reduce_extern_wrapper:0
2025-08-14T21:17:27.5634964Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_tools/memory_tracker.py::MemoryTracker:0, line 55 <- wrt source file
2025-08-14T21:17:27.5637943Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_tools/memory_tracker.py::MemoryTracker:0
2025-08-14T21:17:27.5640606Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/join.py::Join:0, line 141 <- wrt source file
2025-08-14T21:17:27.5643131Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/join.py::Join:0
2025-08-14T21:17:27.5645984Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0, line 107 <- wrt source file
2025-08-14T21:17:27.5649287Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0
2025-08-14T21:17:27.5652477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0, line 23 <- wrt source file
2025-08-14T21:17:27.5655701Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0
2025-08-14T21:17:27.5658870Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::allreduce_hook:0, line 49 <- wrt source file
2025-08-14T21:17:27.5662204Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::allreduce_hook:0
2025-08-14T21:17:27.5665495Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::fp16_compress_hook:0, line 104 <- wrt source file
2025-08-14T21:17:27.5668854Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::fp16_compress_hook:0
2025-08-14T21:17:27.5672195Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_hook:0, line 125 <- wrt source file
2025-08-14T21:17:27.5675532Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_hook:0
2025-08-14T21:17:27.5678831Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::fp16_compress_wrapper:0, line 143 <- wrt source file
2025-08-14T21:17:27.5682261Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::fp16_compress_wrapper:0
2025-08-14T21:17:27.5685596Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_wrapper:0, line 182 <- wrt source file
2025-08-14T21:17:27.5689008Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_wrapper:0
2025-08-14T21:17:27.5692341Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py::batched_powerSGD_hook:0, line 708 <- wrt source file
2025-08-14T21:17:27.5695751Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py::batched_powerSGD_hook:0
2025-08-14T21:17:27.5699228Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_pertensor_hook:0, line 64 <- wrt source file
2025-08-14T21:17:27.5703003Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_pertensor_hook:0
2025-08-14T21:17:27.5706656Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_perchannel_hook:0, line 145 <- wrt source file
2025-08-14T21:17:27.5710535Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_perchannel_hook:0
2025-08-14T21:17:27.5713915Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py::_patch_model_state_dict:0, line 1395 <- wrt source file
2025-08-14T21:17:27.5717000Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py::_patch_model_state_dict:0
2025-08-14T21:17:27.5720081Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py::_patch_optimizer_state_dict:0, line 1454 <- wrt source file
2025-08-14T21:17:27.5723273Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py::_patch_optimizer_state_dict:0
2025-08-14T21:17:27.5726377Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/barriers.py::BarrierConfig:0, line 50 <- wrt source file
2025-08-14T21:17:27.5729654Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/barriers.py::BarrierConfig:0
2025-08-14T21:17:27.5732910Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_sync_checkpointer:0, line 77 <- wrt source file
2025-08-14T21:17:27.5736243Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_sync_checkpointer:0
2025-08-14T21:17:27.5739503Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_async_checkpointer:0, line 138 <- wrt source file
2025-08-14T21:17:27.5742851Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_async_checkpointer:0
2025-08-14T21:17:27.5746137Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::SyncCheckpointer:0, line 104 <- wrt source file
2025-08-14T21:17:27.5749522Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::SyncCheckpointer:0
2025-08-14T21:17:27.5753036Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::SyncCheckpointer.save:0, line 142 <- wrt source file
2025-08-14T21:17:27.5756515Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::SyncCheckpointer.save:0
2025-08-14T21:17:27.5759888Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::AsyncCheckpointer:0, line 213 <- wrt source file
2025-08-14T21:17:27.5763280Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::AsyncCheckpointer:0
2025-08-14T21:17:27.5766628Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::AsyncCheckpointer.save:0, line 260 <- wrt source file
2025-08-14T21:17:27.5770306Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/checkpointer.py::AsyncCheckpointer.save:0
2025-08-14T21:17:27.5773611Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/staging.py::DefaultStager.close:0, line 206 <- wrt source file
2025-08-14T21:17:27.5776915Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/_experimental/staging.py::DefaultStager.close:0
2025-08-14T21:17:27.5780121Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/rendezvous/api.py::RendezvousHandler.shutdown:0, line 231 <- wrt source file
2025-08-14T21:17:27.5783401Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/rendezvous/api.py::RendezvousHandler.shutdown:0
2025-08-14T21:17:27.5786492Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/utils/distributed.py::get_free_port:0, line 141 <- wrt source file
2025-08-14T21:17:27.5789499Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/utils/distributed.py::get_free_port:0
2025-08-14T21:17:27.5792331Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py::StateDictType:0, line 262 <- wrt source file
2025-08-14T21:17:27.5794928Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py::StateDictType:0
2025-08-14T21:17:27.5798029Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0, line 125 <- wrt source file
2025-08-14T21:17:27.5801425Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0
2025-08-14T21:17:27.5805052Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0, line 1490 <- wrt source file
2025-08-14T21:17:27.5808993Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0
2025-08-14T21:17:27.5813029Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.scatter_full_optim_state_dict:0, line 1610 <- wrt source file
2025-08-14T21:17:27.5817058Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.scatter_full_optim_state_dict:0
2025-08-14T21:17:27.5820911Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.rekey_optim_state_dict:0, line 1695 <- wrt source file
2025-08-14T21:17:27.5824755Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.rekey_optim_state_dict:0
2025-08-14T21:17:27.5828128Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/sharded_grad_scaler.py::ShardedGradScaler:0, line 54 <- wrt source file
2025-08-14T21:17:27.5831167Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/sharded_grad_scaler.py::ShardedGradScaler:0
2025-08-14T21:17:27.5834005Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0, line 224 <- wrt source file
2025-08-14T21:17:27.5836624Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0
2025-08-14T21:17:27.5839455Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0, line 134 <- wrt source file
2025-08-14T21:17:27.5842200Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0
2025-08-14T21:17:27.5845232Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/apply_optimizer_in_backward.py::_apply_optimizer_in_backward:0, line 43 <- wrt source file
2025-08-14T21:17:27.5848656Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/apply_optimizer_in_backward.py::_apply_optimizer_in_backward:0
2025-08-14T21:17:27.5851994Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/apply_optimizer_in_backward.py::_get_in_backward_optimizers:0, line 114 <- wrt source file
2025-08-14T21:17:27.5855378Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/apply_optimizer_in_backward.py::_get_in_backward_optimizers:0
2025-08-14T21:17:27.5858452Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/named_optimizer.py::_NamedOptimizer:0, line 43 <- wrt source file
2025-08-14T21:17:27.5861369Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/named_optimizer.py::_NamedOptimizer:0
2025-08-14T21:17:27.5864346Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/utils.py::register_functional_optim:0, line 37 <- wrt source file
2025-08-14T21:17:27.5867244Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/utils.py::register_functional_optim:0
2025-08-14T21:17:27.5869973Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/_IR.py::pipe_split:0, line 333 <- wrt source file
2025-08-14T21:17:27.5872684Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/_IR.py::pipe_split:0
2025-08-14T21:17:27.5875584Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_tuple:0, line 83 <- wrt source file
2025-08-14T21:17:27.5878808Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_tuple:0
2025-08-14T21:17:27.5882321Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_dict:0, line 102 <- wrt source file
2025-08-14T21:17:27.5885884Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_dict:0
2025-08-14T21:17:27.5889000Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::_wait_all:0, line 174 <- wrt source file
2025-08-14T21:17:27.5891729Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::_wait_all:0
2025-08-14T21:17:27.5894431Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::shutdown:0, line 345 <- wrt source file
2025-08-14T21:17:27.5897185Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::shutdown:0
2025-08-14T21:17:27.5899805Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::remote:0, line 606 <- wrt source file
2025-08-14T21:17:27.5902495Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::remote:0
2025-08-14T21:17:27.5905389Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::rpc_sync:0, line 786 <- wrt source file
2025-08-14T21:17:27.5908122Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::rpc_sync:0
2025-08-14T21:17:27.5910991Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::rpc_async:0, line 878 <- wrt source file
2025-08-14T21:17:27.5913841Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::rpc_async:0
2025-08-14T21:17:27.5916652Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_api.py::_shard_tensor:0, line 837 <- wrt source file
2025-08-14T21:17:27.5919606Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_api.py::_shard_tensor:0
2025-08-14T21:17:27.5922897Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_random.py::OffsetBasedRNGTracker._set_pre_op_offset:0, line 280 <- wrt source file
2025-08-14T21:17:27.5926658Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_random.py::OffsetBasedRNGTracker._set_pre_op_offset:0
2025-08-14T21:17:27.5930065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_ops/_common_rules.py::pointwise_rule:0, line 230 <- wrt source file
2025-08-14T21:17:27.5933277Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/_ops/_common_rules.py::pointwise_rule:0
2025-08-14T21:17:27.5936217Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/api.py::parallelize_module:0, line 56 <- wrt source file
2025-08-14T21:17:27.5939179Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/api.py::parallelize_module:0
2025-08-14T21:17:27.5942135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/ddp.py::_pre_dp_module_transform:0, line 88 <- wrt source file
2025-08-14T21:17:27.5945206Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/ddp.py::_pre_dp_module_transform:0
2025-08-14T21:17:27.5948124Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/loss.py::loss_parallel:0, line 56 <- wrt source file
2025-08-14T21:17:27.5950979Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/loss.py::loss_parallel:0
2025-08-14T21:17:27.5953932Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::ColwiseParallel:0, line 64 <- wrt source file
2025-08-14T21:17:27.5956912Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::ColwiseParallel:0
2025-08-14T21:17:27.5959824Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::RowwiseParallel:0, line 198 <- wrt source file
2025-08-14T21:17:27.5962810Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::RowwiseParallel:0
2025-08-14T21:17:27.5965745Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0, line 350 <- wrt source file
2025-08-14T21:17:27.5968770Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0
2025-08-14T21:17:27.5971612Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0, line 30 <- wrt source file
2025-08-14T21:17:27.5974191Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0
2025-08-14T21:17:27.5976567Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0, line 21 <- wrt source file
2025-08-14T21:17:27.5978910Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0
2025-08-14T21:17:27.5981294Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0, line 31 <- wrt source file
2025-08-14T21:17:27.5983806Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0
2025-08-14T21:17:27.5986335Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0, line 42 <- wrt source file
2025-08-14T21:17:27.5989004Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0
2025-08-14T21:17:27.5991540Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file
2025-08-14T21:17:27.5993965Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0
2025-08-14T21:17:27.5996349Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file
2025-08-14T21:17:27.5998666Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0
2025-08-14T21:17:27.6001140Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0, line 166 <- wrt source file
2025-08-14T21:17:27.6003823Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0
2025-08-14T21:17:27.6006537Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 187 <- wrt source file
2025-08-14T21:17:27.6009504Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0
2025-08-14T21:17:27.6012410Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file
2025-08-14T21:17:27.6015496Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0
2025-08-14T21:17:27.6018240Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 42 <- wrt source file
2025-08-14T21:17:27.6020801Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0
2025-08-14T21:17:27.6023374Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file
2025-08-14T21:17:27.6026045Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0
2025-08-14T21:17:27.6028752Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file
2025-08-14T21:17:27.6031640Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0
2025-08-14T21:17:27.6034301Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file
2025-08-14T21:17:27.6036688Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0
2025-08-14T21:17:27.6039342Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file
2025-08-14T21:17:27.6042320Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0
2025-08-14T21:17:27.6045007Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file
2025-08-14T21:17:27.6047579Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0
2025-08-14T21:17:27.6050028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file
2025-08-14T21:17:27.6052435Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0
2025-08-14T21:17:27.6054881Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file
2025-08-14T21:17:27.6057547Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0
2025-08-14T21:17:27.6060163Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file
2025-08-14T21:17:27.6062774Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0
2025-08-14T21:17:27.6065367Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file
2025-08-14T21:17:27.6068044Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0
2025-08-14T21:17:27.6070670Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file
2025-08-14T21:17:27.6073469Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0
2025-08-14T21:17:27.6076117Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file
2025-08-14T21:17:27.6078774Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0
2025-08-14T21:17:27.6081281Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file
2025-08-14T21:17:27.6083743Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0
2025-08-14T21:17:27.6086250Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file
2025-08-14T21:17:27.6088910Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0
2025-08-14T21:17:27.6091464Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file
2025-08-14T21:17:27.6094023Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0
2025-08-14T21:17:27.6096764Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file
2025-08-14T21:17:27.6099573Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0
2025-08-14T21:17:27.6102260Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file
2025-08-14T21:17:27.6104940Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0
2025-08-14T21:17:27.6107757Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file
2025-08-14T21:17:27.6110952Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0
2025-08-14T21:17:27.6113643Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file
2025-08-14T21:17:27.6116069Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0
2025-08-14T21:17:27.6118730Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file
2025-08-14T21:17:27.6121863Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0
2025-08-14T21:17:27.6124472Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file
2025-08-14T21:17:27.6126910Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0
2025-08-14T21:17:27.6129319Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file
2025-08-14T21:17:27.6131797Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0
2025-08-14T21:17:27.6134220Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file
2025-08-14T21:17:27.6136720Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0
2025-08-14T21:17:27.6139285Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1065 <- wrt source file
2025-08-14T21:17:27.6141957Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0
2025-08-14T21:17:27.6144621Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::StackTransform:0, line 1177 <- wrt source file
2025-08-14T21:17:27.6147349Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::StackTransform:0
2025-08-14T21:17:27.6150255Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0, line 1253 <- wrt source file
2025-08-14T21:17:27.6153488Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0
2025-08-14T21:17:27.6156192Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/uniform.py::Uniform:0, line 21 <- wrt source file
2025-08-14T21:17:27.6158792Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/uniform.py::Uniform:0
2025-08-14T21:17:27.6161221Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/utils.py::clamp_probs:0, line 114 <- wrt source file
2025-08-14T21:17:27.6163721Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/utils.py::clamp_probs:0
2025-08-14T21:17:27.6166184Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/von_mises.py::VonMises:0, line 117 <- wrt source file
2025-08-14T21:17:27.6168688Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/von_mises.py::VonMises:0
2025-08-14T21:17:27.6171129Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/weibull.py::Weibull:0, line 22 <- wrt source file
2025-08-14T21:17:27.6173585Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/weibull.py::Weibull:0
2025-08-14T21:17:27.6175988Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file
2025-08-14T21:17:27.6178438Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0
2025-08-14T21:17:27.6180790Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 103 <- wrt source file
2025-08-14T21:17:27.6183287Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0
2025-08-14T21:17:27.6185782Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0, line 715 <- wrt source file
2025-08-14T21:17:27.6188464Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0
2025-08-14T21:17:27.6191088Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1, line 731 <- wrt source file
2025-08-14T21:17:27.6193805Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1
2025-08-14T21:17:27.6196427Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0, line 815 <- wrt source file
2025-08-14T21:17:27.6199097Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0
2025-08-14T21:17:27.6201454Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0, line 102 <- wrt source file
2025-08-14T21:17:27.6203669Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0
2025-08-14T21:17:27.6206025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0, line 1873 <- wrt source file
2025-08-14T21:17:27.6208568Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0
2025-08-14T21:17:27.6211248Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.on_generate_code:0, line 1967 <- wrt source file
2025-08-14T21:17:27.6213716Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::Graph.on_generate_code:0
2025-08-14T21:17:27.6232578Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Interpreter:0, line 49 <- wrt source file
2025-08-14T21:17:27.6235215Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Interpreter:0
2025-08-14T21:17:27.6237864Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Transformer:0, line 480 <- wrt source file
2025-08-14T21:17:27.6240287Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/interpreter.py::Transformer:0
2025-08-14T21:17:27.6242740Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/subgraph_rewriter.py::replace_pattern:0, line 125 <- wrt source file
2025-08-14T21:17:27.6245348Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/subgraph_rewriter.py::replace_pattern:0
2025-08-14T21:17:27.6247739Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::TensorType:0, line 12 <- wrt source file
2025-08-14T21:17:27.6250070Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::TensorType:0
2025-08-14T21:17:27.6252387Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_consistent:0, line 65 <- wrt source file
2025-08-14T21:17:27.6254773Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_consistent:0
2025-08-14T21:17:27.6257115Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_more_precise:0, line 93 <- wrt source file
2025-08-14T21:17:27.6259647Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_more_precise:0
2025-08-14T21:17:27.6262324Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/rewriter.py::AST_Rewriter.visit_AnnAssign:0, line 96 <- wrt source file
2025-08-14T21:17:27.6265331Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/rewriter.py::AST_Rewriter.visit_AnnAssign:0
2025-08-14T21:17:27.6268111Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/core.py::reify:0, line 58 <- wrt source file
2025-08-14T21:17:27.6270815Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/core.py::reify:0
2025-08-14T21:17:27.6273629Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/match.py::VarDispatcher:0, line 48 <- wrt source file
2025-08-14T21:17:27.6276569Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/match.py::VarDispatcher:0
2025-08-14T21:17:27.6279367Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::unifiable:0, line 11 <- wrt source file
2025-08-14T21:17:27.6282151Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::unifiable:0
2025-08-14T21:17:27.6284892Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::reify_object:0, line 37 <- wrt source file
2025-08-14T21:17:27.6287736Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::reify_object:0
2025-08-14T21:17:27.6290514Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::unify_object:0, line 93 <- wrt source file
2025-08-14T21:17:27.6293328Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/more.py::unify_object:0
2025-08-14T21:17:27.6296201Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::merge:0, line 37 <- wrt source file
2025-08-14T21:17:27.6299327Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::merge:0
2025-08-14T21:17:27.6302320Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::merge_with:0, line 64 <- wrt source file
2025-08-14T21:17:27.6305465Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::merge_with:0
2025-08-14T21:17:27.6308480Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::valmap:0, line 90 <- wrt source file
2025-08-14T21:17:27.6311717Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::valmap:0
2025-08-14T21:17:27.6314716Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::keymap:0, line 106 <- wrt source file
2025-08-14T21:17:27.6317769Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::keymap:0
2025-08-14T21:17:27.6320756Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::itemmap:0, line 122 <- wrt source file
2025-08-14T21:17:27.6323927Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::itemmap:0
2025-08-14T21:17:27.6327658Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::valfilter:0, line 138 <- wrt source file
2025-08-14T21:17:27.6330789Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::valfilter:0
2025-08-14T21:17:27.6333846Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::keyfilter:0, line 158 <- wrt source file
2025-08-14T21:17:27.6336954Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::keyfilter:0
2025-08-14T21:17:27.6340030Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::itemfilter:0, line 178 <- wrt source file
2025-08-14T21:17:27.6343173Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::itemfilter:0
2025-08-14T21:17:27.6346187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::assoc:0, line 204 <- wrt source file
2025-08-14T21:17:27.6349207Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::assoc:0
2025-08-14T21:17:27.6352224Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::dissoc:0, line 221 <- wrt source file
2025-08-14T21:17:27.6355261Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::dissoc:0
2025-08-14T21:17:27.6358242Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::first:0, line 416 <- wrt source file
2025-08-14T21:17:27.6361275Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::first:0
2025-08-14T21:17:27.6364162Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::transitive_get:0, line 15 <- wrt source file
2025-08-14T21:17:27.6367221Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::transitive_get:0
2025-08-14T21:17:27.6370026Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0, line 42 <- wrt source file
2025-08-14T21:17:27.6372855Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0
2025-08-14T21:17:27.6375626Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0, line 70 <- wrt source file
2025-08-14T21:17:27.6378517Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0
2025-08-14T21:17:27.6381284Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::freeze:0, line 95 <- wrt source file
2025-08-14T21:17:27.6384035Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::freeze:0
2025-08-14T21:17:27.6386811Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/variable.py::variables:0, line 67 <- wrt source file
2025-08-14T21:17:27.6389755Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/variable.py::variables:0
2025-08-14T21:17:27.6392896Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0, line 20 <- wrt source file
2025-08-14T21:17:27.6396145Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0
2025-08-14T21:17:27.6399438Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher:0, line 113 <- wrt source file
2025-08-14T21:17:27.6402875Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher:0
2025-08-14T21:17:27.6406354Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.register:0, line 138 <- wrt source file
2025-08-14T21:17:27.6410136Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.register:0
2025-08-14T21:17:27.6413663Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.add:0, line 191 <- wrt source file
2025-08-14T21:17:27.6417190Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.add:0
2025-08-14T21:17:27.6420694Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0, line 304 <- wrt source file
2025-08-14T21:17:27.6424361Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0
2025-08-14T21:17:27.6427850Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::str_signature:0, line 434 <- wrt source file
2025-08-14T21:17:27.6431359Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::str_signature:0
2025-08-14T21:17:27.6434907Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::expand_tuples:0, line 18 <- wrt source file
2025-08-14T21:17:27.6438262Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::expand_tuples:0
2025-08-14T21:17:27.6441467Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::_toposort:0, line 41 <- wrt source file
2025-08-14T21:17:27.6444715Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::_toposort:0
2025-08-14T21:17:27.6447924Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::reverse_dict:0, line 68 <- wrt source file
2025-08-14T21:17:27.6451327Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::reverse_dict:0
2025-08-14T21:17:27.6454512Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0, line 87 <- wrt source file
2025-08-14T21:17:27.6457744Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0
2025-08-14T21:17:27.6461035Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0, line 117 <- wrt source file
2025-08-14T21:17:27.6464281Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0
2025-08-14T21:17:27.6467953Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::isvariadic:0, line 47 <- wrt source file
2025-08-14T21:17:27.6471891Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::isvariadic:0
2025-08-14T21:17:27.6475694Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::Variadic:0, line 83 <- wrt source file
2025-08-14T21:17:27.6479524Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::Variadic:0
2025-08-14T21:17:27.6483010Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/graph_drawer.py::FxGraphDrawer.get_dot_graph:0, line 129 <- wrt source file
2025-08-14T21:17:27.6486369Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/graph_drawer.py::FxGraphDrawer.get_dot_graph:0
2025-08-14T21:17:27.6489412Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0, line 99 <- wrt source file
2025-08-14T21:17:27.6492271Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0
2025-08-14T21:17:27.6495130Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0, line 89 <- wrt source file
2025-08-14T21:17:27.6498096Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0
2025-08-14T21:17:27.6501604Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0, line 51 <- wrt source file
2025-08-14T21:17:27.6505859Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0
2025-08-14T21:17:27.6509596Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0, line 36 <- wrt source file
2025-08-14T21:17:27.6512878Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0
2025-08-14T21:17:27.6515970Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0, line 22 <- wrt source file
2025-08-14T21:17:27.6519149Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0
2025-08-14T21:17:27.6522384Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0, line 122 <- wrt source file
2025-08-14T21:17:27.6525704Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0
2025-08-14T21:17:27.6528835Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0, line 214 <- wrt source file
2025-08-14T21:17:27.6532045Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0
2025-08-14T21:17:27.6534962Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/_ops.py::logaddexp:0, line 1530 <- wrt source file
2025-08-14T21:17:27.6537556Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/_ops.py::logaddexp:0
2025-08-14T21:17:27.6540394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0, line 25 <- wrt source file
2025-08-14T21:17:27.6543536Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0
2025-08-14T21:17:27.6546694Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0, line 460 <- wrt source file
2025-08-14T21:17:27.6550001Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0
2025-08-14T21:17:27.6553350Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0, line 579 <- wrt source file
2025-08-14T21:17:27.7131672Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0
2025-08-14T21:17:27.7153116Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2174 <- wrt source file
2025-08-14T21:17:27.7162140Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0
2025-08-14T21:17:27.7164872Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0, line 2478 <- wrt source file
2025-08-14T21:17:27.7170893Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0
2025-08-14T21:17:27.7173224Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0, line 2618 <- wrt source file
2025-08-14T21:17:27.7180932Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0
2025-08-14T21:17:27.7183517Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0, line 3051 <- wrt source file
2025-08-14T21:17:27.7198498Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0
2025-08-14T21:17:27.7200872Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0, line 3121 <- wrt source file
2025-08-14T21:17:27.7205186Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0
2025-08-14T21:17:27.7207874Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0, line 3430 <- wrt source file
2025-08-14T21:17:27.7214748Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0
2025-08-14T21:17:27.7217602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3495 <- wrt source file
2025-08-14T21:17:27.7221734Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0
2025-08-14T21:17:27.7224482Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3565 <- wrt source file
2025-08-14T21:17:27.7228378Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0
2025-08-14T21:17:27.7231546Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0, line 5263 <- wrt source file
2025-08-14T21:17:27.7238772Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0
2025-08-14T21:17:27.7240917Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file
2025-08-14T21:17:27.7246740Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0
2025-08-14T21:17:27.7248928Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file
2025-08-14T21:17:27.7252127Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0
2025-08-14T21:17:27.7254319Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file
2025-08-14T21:17:27.7259800Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0
2025-08-14T21:17:27.7262004Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file
2025-08-14T21:17:27.7264609Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0
2025-08-14T21:17:27.7266813Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file
2025-08-14T21:17:27.7298285Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0
2025-08-14T21:17:27.7301285Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file
2025-08-14T21:17:27.7330061Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0
2025-08-14T21:17:27.7332584Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0, line 230 <- wrt source file
2025-08-14T21:17:27.7334908Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0
2025-08-14T21:17:27.7337215Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0, line 257 <- wrt source file
2025-08-14T21:17:27.7339363Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0
2025-08-14T21:17:27.7341517Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0, line 292 <- wrt source file
2025-08-14T21:17:27.7353911Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0
2025-08-14T21:17:27.7356078Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0, line 306 <- wrt source file
2025-08-14T21:17:27.7358284Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0
2025-08-14T21:17:27.7360389Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0, line 323 <- wrt source file
2025-08-14T21:17:27.7362490Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0
2025-08-14T21:17:27.7364544Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0, line 336 <- wrt source file
2025-08-14T21:17:27.7366654Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0
2025-08-14T21:17:27.7368869Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0, line 352 <- wrt source file
2025-08-14T21:17:27.7370955Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0
2025-08-14T21:17:27.7373032Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0, line 374 <- wrt source file
2025-08-14T21:17:27.7375128Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0
2025-08-14T21:17:27.7377318Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0, line 460 <- wrt source file
2025-08-14T21:17:27.7379623Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0
2025-08-14T21:17:27.7381864Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0, line 492 <- wrt source file
2025-08-14T21:17:27.7384120Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0
2025-08-14T21:17:27.7386369Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 543 <- wrt source file
2025-08-14T21:17:27.7388676Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0
2025-08-14T21:17:27.7390941Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0, line 608 <- wrt source file
2025-08-14T21:17:27.7393282Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0
2025-08-14T21:17:27.7395471Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0, line 647 <- wrt source file
2025-08-14T21:17:27.7397695Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0
2025-08-14T21:17:27.7399818Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0, line 700 <- wrt source file
2025-08-14T21:17:27.7401965Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0
2025-08-14T21:17:27.7404375Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 120 <- wrt source file
2025-08-14T21:17:27.7406880Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0
2025-08-14T21:17:27.7409482Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 95 <- wrt source file
2025-08-14T21:17:27.7411926Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0
2025-08-14T21:17:27.7414329Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file
2025-08-14T21:17:27.7416833Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0
2025-08-14T21:17:27.7419235Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0, line 120 <- wrt source file
2025-08-14T21:17:27.7421643Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0
2025-08-14T21:17:27.7423990Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0, line 185 <- wrt source file
2025-08-14T21:17:27.7426525Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0
2025-08-14T21:17:27.7428992Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 247 <- wrt source file
2025-08-14T21:17:27.7431566Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0
2025-08-14T21:17:27.7433966Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 318 <- wrt source file
2025-08-14T21:17:27.7436398Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0
2025-08-14T21:17:27.7438780Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 349 <- wrt source file
2025-08-14T21:17:27.7441240Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0
2025-08-14T21:17:27.7443710Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 384 <- wrt source file
2025-08-14T21:17:27.7446259Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0
2025-08-14T21:17:27.7448663Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0, line 420 <- wrt source file
2025-08-14T21:17:27.7451074Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0
2025-08-14T21:17:27.7453425Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0, line 456 <- wrt source file
2025-08-14T21:17:27.7455813Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0
2025-08-14T21:17:27.7458157Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0, line 501 <- wrt source file
2025-08-14T21:17:27.7460511Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0
2025-08-14T21:17:27.7462924Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 552 <- wrt source file
2025-08-14T21:17:27.7465586Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0
2025-08-14T21:17:27.7467972Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0, line 598 <- wrt source file
2025-08-14T21:17:27.7470343Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0
2025-08-14T21:17:27.7472787Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0, line 646 <- wrt source file
2025-08-14T21:17:27.7475188Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0
2025-08-14T21:17:27.7477521Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0, line 705 <- wrt source file
2025-08-14T21:17:27.7479911Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0
2025-08-14T21:17:27.7482247Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0, line 751 <- wrt source file
2025-08-14T21:17:27.7484608Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0
2025-08-14T21:17:27.7487003Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0, line 799 <- wrt source file
2025-08-14T21:17:27.7489465Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0
2025-08-14T21:17:27.7491865Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 848 <- wrt source file
2025-08-14T21:17:27.7494415Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0
2025-08-14T21:17:27.7496873Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 903 <- wrt source file
2025-08-14T21:17:27.7499374Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0
2025-08-14T21:17:27.7501830Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 945 <- wrt source file
2025-08-14T21:17:27.7504364Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0
2025-08-14T21:17:27.7506818Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0, line 981 <- wrt source file
2025-08-14T21:17:27.7509554Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0
2025-08-14T21:17:27.7512066Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 1030 <- wrt source file
2025-08-14T21:17:27.7514611Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0
2025-08-14T21:17:27.7517233Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1144 <- wrt source file
2025-08-14T21:17:27.7519998Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0
2025-08-14T21:17:27.7522643Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1609 <- wrt source file
2025-08-14T21:17:27.7525590Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0
2025-08-14T21:17:27.7528397Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1660 <- wrt source file
2025-08-14T21:17:27.7531065Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0
2025-08-14T21:17:27.7533545Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1686 <- wrt source file
2025-08-14T21:17:27.7536058Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0
2025-08-14T21:17:27.7538519Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1724 <- wrt source file
2025-08-14T21:17:27.7540983Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0
2025-08-14T21:17:27.7543414Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1788 <- wrt source file
2025-08-14T21:17:27.7545865Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0
2025-08-14T21:17:27.7548319Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1835 <- wrt source file
2025-08-14T21:17:27.7550976Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0
2025-08-14T21:17:27.7553538Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1874 <- wrt source file
2025-08-14T21:17:27.7556089Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0
2025-08-14T21:17:27.7558564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 332 <- wrt source file
2025-08-14T21:17:27.7561101Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0
2025-08-14T21:17:27.7563578Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 443 <- wrt source file
2025-08-14T21:17:27.7796635Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0
2025-08-14T21:17:27.7799349Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 554 <- wrt source file
2025-08-14T21:17:28.0267533Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0
2025-08-14T21:17:28.0437957Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file
2025-08-14T21:17:28.0459538Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0
2025-08-14T21:17:28.0462170Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file
2025-08-14T21:17:28.0464727Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0
2025-08-14T21:17:28.0467272Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 260 <- wrt source file
2025-08-14T21:17:28.0470477Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0
2025-08-14T21:17:28.0473585Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 283 <- wrt source file
2025-08-14T21:17:28.0479576Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0
2025-08-14T21:17:28.0482250Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 314 <- wrt source file
2025-08-14T21:17:28.0488994Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0
2025-08-14T21:17:28.0491668Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0, line 343 <- wrt source file
2025-08-14T21:17:28.0494199Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0
2025-08-14T21:17:28.0496694Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 523 <- wrt source file
2025-08-14T21:17:28.0499225Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0
2025-08-14T21:17:28.0501791Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0, line 653 <- wrt source file
2025-08-14T21:17:28.0504605Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0
2025-08-14T21:17:28.0507175Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 808 <- wrt source file
2025-08-14T21:17:28.0509955Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0
2025-08-14T21:17:28.0512669Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file
2025-08-14T21:17:28.0515345Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0
2025-08-14T21:17:28.0517906Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 81 <- wrt source file
2025-08-14T21:17:28.0520551Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0
2025-08-14T21:17:28.0523017Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file
2025-08-14T21:17:28.0525435Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0
2025-08-14T21:17:28.0527816Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 108 <- wrt source file
2025-08-14T21:17:28.0530275Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0
2025-08-14T21:17:28.0532666Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 163 <- wrt source file
2025-08-14T21:17:28.0545735Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0
2025-08-14T21:17:28.0548502Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 211 <- wrt source file
2025-08-14T21:17:28.0618297Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0
2025-08-14T21:17:28.0621558Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 257 <- wrt source file
2025-08-14T21:17:28.0624091Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0
2025-08-14T21:17:28.0626655Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 309 <- wrt source file
2025-08-14T21:17:28.0696622Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0
2025-08-14T21:17:28.0699539Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 30 <- wrt source file
2025-08-14T21:17:28.0705070Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0
2025-08-14T21:17:28.0707400Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file
2025-08-14T21:17:28.0711215Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0
2025-08-14T21:17:28.0713533Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0, line 395 <- wrt source file
2025-08-14T21:17:28.0727062Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0
2025-08-14T21:17:28.0729702Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 187 <- wrt source file
2025-08-14T21:17:28.0740612Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0
2025-08-14T21:17:28.0743311Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 303 <- wrt source file
2025-08-14T21:17:28.0922454Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0
2025-08-14T21:17:28.0925135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 419 <- wrt source file
2025-08-14T21:17:28.3364098Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0
2025-08-14T21:17:28.3527622Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file
2025-08-14T21:17:28.3530171Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0
2025-08-14T21:17:28.3532559Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file
2025-08-14T21:17:28.3536988Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0
2025-08-14T21:17:28.3539311Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0, line 83 <- wrt source file
2025-08-14T21:17:28.3546159Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0
2025-08-14T21:17:28.3548481Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 191 <- wrt source file
2025-08-14T21:17:28.3568606Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0
2025-08-14T21:17:28.3571974Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 115 <- wrt source file
2025-08-14T21:17:28.3578019Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0
2025-08-14T21:17:28.3605820Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 215 <- wrt source file
2025-08-14T21:17:28.3608433Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0
2025-08-14T21:17:28.3610966Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 329 <- wrt source file
2025-08-14T21:17:28.3613444Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0
2025-08-14T21:17:28.3615882Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 418 <- wrt source file
2025-08-14T21:17:28.3628720Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0
2025-08-14T21:17:28.3631071Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 535 <- wrt source file
2025-08-14T21:17:28.3637335Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0
2025-08-14T21:17:28.3640154Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 617 <- wrt source file
2025-08-14T21:17:28.3645554Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0
2025-08-14T21:17:28.3647836Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 703 <- wrt source file
2025-08-14T21:17:28.3652919Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0
2025-08-14T21:17:28.3655311Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 778 <- wrt source file
2025-08-14T21:17:28.3665129Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0
2025-08-14T21:17:28.3667616Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 826 <- wrt source file
2025-08-14T21:17:28.3672408Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1
2025-08-14T21:17:28.3675297Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 974 <- wrt source file
2025-08-14T21:17:28.3681029Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0
2025-08-14T21:17:28.3683575Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1306 <- wrt source file
2025-08-14T21:17:28.3690398Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0
2025-08-14T21:17:28.3693274Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1, line 1333 <- wrt source file
2025-08-14T21:17:28.3695989Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1
2025-08-14T21:17:28.3698504Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1495 <- wrt source file
2025-08-14T21:17:28.3703260Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0
2025-08-14T21:17:28.3705806Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1562 <- wrt source file
2025-08-14T21:17:28.3711529Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0
2025-08-14T21:17:28.3714051Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1643 <- wrt source file
2025-08-14T21:17:28.3720244Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0
2025-08-14T21:17:28.3722752Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1745 <- wrt source file
2025-08-14T21:17:28.3732511Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0
2025-08-14T21:17:28.3735092Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 551 <- wrt source file
2025-08-14T21:17:28.3737773Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0
2025-08-14T21:17:28.3740497Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1039 <- wrt source file
2025-08-14T21:17:28.3748911Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0
2025-08-14T21:17:28.3751308Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0, line 1290 <- wrt source file
2025-08-14T21:17:28.3756741Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0
2025-08-14T21:17:28.3759199Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2229 <- wrt source file
2025-08-14T21:17:28.3761770Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0
2025-08-14T21:17:28.3764310Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2670 <- wrt source file
2025-08-14T21:17:28.3766893Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0
2025-08-14T21:17:28.3769477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2698 <- wrt source file
2025-08-14T21:17:28.3772183Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0
2025-08-14T21:17:28.3774722Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2725 <- wrt source file
2025-08-14T21:17:28.3777204Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0
2025-08-14T21:17:28.3779727Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2752 <- wrt source file
2025-08-14T21:17:28.3782342Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0
2025-08-14T21:17:28.3784920Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2783 <- wrt source file
2025-08-14T21:17:28.3787749Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0
2025-08-14T21:17:28.3790135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2807 <- wrt source file
2025-08-14T21:17:28.3792725Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0
2025-08-14T21:17:28.3795646Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2845 <- wrt source file
2025-08-14T21:17:28.3798576Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0
2025-08-14T21:17:28.3802164Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file
2025-08-14T21:17:28.3815012Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0
2025-08-14T21:17:28.3818187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 163 <- wrt source file
2025-08-14T21:17:28.3824359Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0
2025-08-14T21:17:28.3827523Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 274 <- wrt source file
2025-08-14T21:17:28.3832537Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0
2025-08-14T21:17:28.3835436Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 367 <- wrt source file
2025-08-14T21:17:28.3838639Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0
2025-08-14T21:17:28.3841180Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file
2025-08-14T21:17:28.3845101Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0
2025-08-14T21:17:28.3847597Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 122 <- wrt source file
2025-08-14T21:17:28.3866990Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0
2025-08-14T21:17:28.3869483Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 187 <- wrt source file
2025-08-14T21:17:29.0010442Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0
2025-08-14T21:17:29.0316521Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 241 <- wrt source file
2025-08-14T21:17:29.0326684Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0
2025-08-14T21:17:29.0329205Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 294 <- wrt source file
2025-08-14T21:17:29.0333476Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0
2025-08-14T21:17:29.0335971Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 350 <- wrt source file
2025-08-14T21:17:29.0359548Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0
2025-08-14T21:17:29.0362080Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 395 <- wrt source file
2025-08-14T21:17:29.0365745Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0
2025-08-14T21:17:29.0368280Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 439 <- wrt source file
2025-08-14T21:17:29.0372290Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0
2025-08-14T21:17:29.0374824Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 497 <- wrt source file
2025-08-14T21:17:29.0377398Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0
2025-08-14T21:17:29.0379932Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 556 <- wrt source file
2025-08-14T21:17:29.0383108Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0
2025-08-14T21:17:29.0385842Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 600 <- wrt source file
2025-08-14T21:17:29.0389828Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0
2025-08-14T21:17:29.0392444Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 658 <- wrt source file
2025-08-14T21:17:29.5466734Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0
2025-08-14T21:17:29.5753942Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 692 <- wrt source file
2025-08-14T21:17:29.5763418Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0
2025-08-14T21:17:29.5767456Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 750 <- wrt source file
2025-08-14T21:17:29.5771658Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0
2025-08-14T21:17:29.5773859Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 812 <- wrt source file
2025-08-14T21:17:29.5797103Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0
2025-08-14T21:17:29.5799391Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file
2025-08-14T21:17:29.5804964Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0
2025-08-14T21:17:29.5807579Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 99 <- wrt source file
2025-08-14T21:17:29.5813107Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0
2025-08-14T21:17:29.5815609Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file
2025-08-14T21:17:29.5822086Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0
2025-08-14T21:17:29.5824709Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 207 <- wrt source file
2025-08-14T21:17:29.5878270Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0
2025-08-14T21:17:29.5880412Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 291 <- wrt source file
2025-08-14T21:17:29.8099962Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0
2025-08-14T21:17:29.8157004Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 366 <- wrt source file
2025-08-14T21:17:29.8169109Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0
2025-08-14T21:17:29.8171325Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 550 <- wrt source file
2025-08-14T21:17:29.8948663Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0
2025-08-14T21:17:29.8951501Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 642 <- wrt source file
2025-08-14T21:17:29.8969406Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0
2025-08-14T21:17:29.8971822Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 738 <- wrt source file
2025-08-14T21:17:29.9008760Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0
2025-08-14T21:17:29.9011337Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 855 <- wrt source file
2025-08-14T21:17:30.0614116Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0
2025-08-14T21:17:30.0674186Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 946 <- wrt source file
2025-08-14T21:17:30.0725416Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0
2025-08-14T21:17:30.0728109Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1033 <- wrt source file
2025-08-14T21:17:30.1441037Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0
2025-08-14T21:17:30.1443570Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1152 <- wrt source file
2025-08-14T21:17:30.1449800Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0
2025-08-14T21:17:30.1452552Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1204 <- wrt source file
2025-08-14T21:17:30.1503104Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0
2025-08-14T21:17:30.1506120Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1264 <- wrt source file
2025-08-14T21:17:30.3687978Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0
2025-08-14T21:17:30.3746597Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1320 <- wrt source file
2025-08-14T21:17:30.3760969Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0
2025-08-14T21:17:30.3763617Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1355 <- wrt source file
2025-08-14T21:17:30.3769864Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0
2025-08-14T21:17:30.3772469Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1399 <- wrt source file
2025-08-14T21:17:30.3795504Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0
2025-08-14T21:17:30.3798126Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1447 <- wrt source file
2025-08-14T21:17:30.3800942Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0
2025-08-14T21:17:30.3803534Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1481 <- wrt source file
2025-08-14T21:17:30.3808786Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0
2025-08-14T21:17:30.3811578Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1521 <- wrt source file
2025-08-14T21:17:30.3828538Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0
2025-08-14T21:17:30.3830893Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0, line 595 <- wrt source file
2025-08-14T21:17:30.3841729Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0
2025-08-14T21:17:30.3844124Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 953 <- wrt source file
2025-08-14T21:17:30.4255921Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0
2025-08-14T21:17:30.4258168Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1288 <- wrt source file
2025-08-14T21:17:30.4273448Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0
2025-08-14T21:17:30.4275709Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1537 <- wrt source file
2025-08-14T21:17:30.4285709Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0
2025-08-14T21:17:30.4287993Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1659 <- wrt source file
2025-08-14T21:17:30.4296431Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0
2025-08-14T21:17:30.4298730Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1773 <- wrt source file
2025-08-14T21:17:30.4311546Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0
2025-08-14T21:17:30.4314153Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file
2025-08-14T21:17:30.4325728Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0
2025-08-14T21:17:30.4328279Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file
2025-08-14T21:17:30.4331374Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0
2025-08-14T21:17:30.4334178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 521 <- wrt source file
2025-08-14T21:17:30.4337888Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0
2025-08-14T21:17:30.4340548Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 90 <- wrt source file
2025-08-14T21:17:31.2565034Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0
2025-08-14T21:17:31.2580503Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 336 <- wrt source file
2025-08-14T21:17:31.3723739Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0
2025-08-14T21:17:31.3788530Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 562 <- wrt source file
2025-08-14T21:17:31.6244224Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0
2025-08-14T21:17:31.6252726Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 686 <- wrt source file
2025-08-14T21:17:31.6541409Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0
2025-08-14T21:17:31.6544392Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 995 <- wrt source file
2025-08-14T21:17:31.7082280Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0
2025-08-14T21:17:31.7085106Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file
2025-08-14T21:17:31.7108268Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0
2025-08-14T21:17:31.7111127Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 229 <- wrt source file
2025-08-14T21:17:31.7121455Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0
2025-08-14T21:17:31.7124187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 279 <- wrt source file
2025-08-14T21:17:31.7130025Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0
2025-08-14T21:17:31.7132681Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 127 <- wrt source file
2025-08-14T21:17:31.7135780Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0
2025-08-14T21:17:31.7138569Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 642 <- wrt source file
2025-08-14T21:17:31.7141527Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0
2025-08-14T21:17:31.7144473Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1446 <- wrt source file
2025-08-14T21:17:31.7147548Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0
2025-08-14T21:17:31.7150714Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 1999 <- wrt source file
2025-08-14T21:17:31.7154104Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0
2025-08-14T21:17:31.7157375Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2009 <- wrt source file
2025-08-14T21:17:31.7160610Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1
2025-08-14T21:17:31.7164097Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2044 <- wrt source file
2025-08-14T21:17:31.7167565Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0
2025-08-14T21:17:31.7170594Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file
2025-08-14T21:17:31.7173394Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0
2025-08-14T21:17:31.7175885Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file
2025-08-14T21:17:31.7178180Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0
2025-08-14T21:17:31.7180620Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 265 <- wrt source file
2025-08-14T21:17:31.7183260Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0
2025-08-14T21:17:31.7185829Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 360 <- wrt source file
2025-08-14T21:17:31.7188477Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0
2025-08-14T21:17:31.7191090Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 591 <- wrt source file
2025-08-14T21:17:31.7193859Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0
2025-08-14T21:17:31.7196289Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0, line 849 <- wrt source file
2025-08-14T21:17:31.7198544Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0
2025-08-14T21:17:31.7201060Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 885 <- wrt source file
2025-08-14T21:17:31.7203609Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0
2025-08-14T21:17:31.7206025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 928 <- wrt source file
2025-08-14T21:17:31.7208443Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0
2025-08-14T21:17:31.7211080Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0, line 968 <- wrt source file
2025-08-14T21:17:31.7213572Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0
2025-08-14T21:17:31.7215913Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0, line 1197 <- wrt source file
2025-08-14T21:17:31.7218176Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0
2025-08-14T21:17:31.7220431Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1225 <- wrt source file
2025-08-14T21:17:31.7222884Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0
2025-08-14T21:17:31.7225251Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 439 <- wrt source file
2025-08-14T21:17:31.7227569Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0
2025-08-14T21:17:31.7229887Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 500 <- wrt source file
2025-08-14T21:17:31.7233587Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0
2025-08-14T21:17:31.7235899Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 556 <- wrt source file
2025-08-14T21:17:31.7241982Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0
2025-08-14T21:17:31.7244288Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 584 <- wrt source file
2025-08-14T21:17:31.7258790Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0
2025-08-14T21:17:31.7261258Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file
2025-08-14T21:17:31.7266077Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0
2025-08-14T21:17:31.7268676Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 346 <- wrt source file
2025-08-14T21:17:31.7273916Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0
2025-08-14T21:17:31.7276471Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 196 <- wrt source file
2025-08-14T21:17:31.7279037Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0
2025-08-14T21:17:31.7281690Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file
2025-08-14T21:17:31.7284905Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0
2025-08-14T21:17:31.7287404Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file
2025-08-14T21:17:31.7290529Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0
2025-08-14T21:17:31.7293192Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file
2025-08-14T21:17:31.7295960Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0
2025-08-14T21:17:31.7299025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0, line 178 <- wrt source file
2025-08-14T21:17:31.7302525Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0
2025-08-14T21:17:31.7305383Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 280 <- wrt source file
2025-08-14T21:17:31.7307851Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0
2025-08-14T21:17:31.7310461Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 388 <- wrt source file
2025-08-14T21:17:31.7313139Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0
2025-08-14T21:17:31.7315531Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 491 <- wrt source file
2025-08-14T21:17:31.7317870Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0
2025-08-14T21:17:31.7320172Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 547 <- wrt source file
2025-08-14T21:17:31.7322626Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0
2025-08-14T21:17:31.7325009Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 608 <- wrt source file
2025-08-14T21:17:31.7327370Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0
2025-08-14T21:17:31.7329736Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 683 <- wrt source file
2025-08-14T21:17:31.7332105Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0
2025-08-14T21:17:31.7334510Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 773 <- wrt source file
2025-08-14T21:17:31.7337020Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0
2025-08-14T21:17:31.7339469Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0, line 971 <- wrt source file
2025-08-14T21:17:31.7341954Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0
2025-08-14T21:17:31.7344588Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1062 <- wrt source file
2025-08-14T21:17:31.7347233Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0
2025-08-14T21:17:31.7349794Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1134 <- wrt source file
2025-08-14T21:17:31.7352441Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0
2025-08-14T21:17:31.7355206Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 1803 <- wrt source file
2025-08-14T21:17:31.7358153Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0
2025-08-14T21:17:31.7361070Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 1819 <- wrt source file
2025-08-14T21:17:31.7363971Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1
2025-08-14T21:17:31.7366516Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0, line 337 <- wrt source file
2025-08-14T21:17:31.7368975Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0
2025-08-14T21:17:31.7371299Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file
2025-08-14T21:17:31.7373725Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0
2025-08-14T21:17:31.7376461Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 295 <- wrt source file
2025-08-14T21:17:31.7379562Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0
2025-08-14T21:17:31.7382215Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::profile:0, line 617 <- wrt source file
2025-08-14T21:17:31.7384590Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::profile:0
2025-08-14T21:17:31.7387137Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0, line 339 <- wrt source file
2025-08-14T21:17:31.7389996Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0
2025-08-14T21:17:31.7392604Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_creation.py::make_tensor:0, line 114 <- wrt source file
2025-08-14T21:17:31.7395030Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_creation.py::make_tensor:0
2025-08-14T21:17:31.7397572Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::parametrize:0, line 615 <- wrt source file
2025-08-14T21:17:31.7400319Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::parametrize:0
2025-08-14T21:17:31.7402991Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0, line 736 <- wrt source file
2025-08-14T21:17:31.7405874Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0
2025-08-14T21:17:31.7408537Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0, line 825 <- wrt source file
2025-08-14T21:17:31.7411383Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0
2025-08-14T21:17:31.7414229Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_symmetric_psd_matrix:0, line 4734 <- wrt source file
2025-08-14T21:17:31.7417179Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_symmetric_psd_matrix:0
2025-08-14T21:17:31.7420161Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_psd_matrix:0, line 4748 <- wrt source file
2025-08-14T21:17:31.7423192Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_psd_matrix:0
2025-08-14T21:17:31.7426088Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0, line 4778 <- wrt source file
2025-08-14T21:17:31.7429221Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0
2025-08-14T21:17:31.7432187Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0, line 194 <- wrt source file
2025-08-14T21:17:31.7434956Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0
2025-08-14T21:17:31.7437773Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0, line 220 <- wrt source file
2025-08-14T21:17:31.7440733Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0
2025-08-14T21:17:31.7443836Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0, line 331 <- wrt source file
2025-08-14T21:17:31.7447199Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0
2025-08-14T21:17:31.7450538Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0, line 29 <- wrt source file
2025-08-14T21:17:31.7454003Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0
2025-08-14T21:17:31.7456794Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 277 <- wrt source file
2025-08-14T21:17:31.7459123Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0
2025-08-14T21:17:31.7461484Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 320 <- wrt source file
2025-08-14T21:17:31.7463903Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0
2025-08-14T21:17:31.7466297Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 357 <- wrt source file
2025-08-14T21:17:31.7468929Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0
2025-08-14T21:17:31.7471288Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 387 <- wrt source file
2025-08-14T21:17:31.7473683Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0
2025-08-14T21:17:31.7476002Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 422 <- wrt source file
2025-08-14T21:17:31.7478388Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0
2025-08-14T21:17:31.7480779Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 457 <- wrt source file
2025-08-14T21:17:31.7483244Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0
2025-08-14T21:17:31.7485588Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 494 <- wrt source file
2025-08-14T21:17:31.7487913Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0
2025-08-14T21:17:31.7490349Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 893 <- wrt source file
2025-08-14T21:17:31.7492911Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0
2025-08-14T21:17:31.7495360Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 303 <- wrt source file
2025-08-14T21:17:31.7497836Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0
2025-08-14T21:17:31.7500239Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0, line 419 <- wrt source file
2025-08-14T21:17:31.7502697Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0
2025-08-14T21:17:31.7505025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1026 <- wrt source file
2025-08-14T21:17:31.7507352Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0
2025-08-14T21:17:31.7509749Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0, line 1345 <- wrt source file
2025-08-14T21:17:31.7512126Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0
2025-08-14T21:17:31.7514688Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 69 <- wrt source file
2025-08-14T21:17:31.7517647Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0
2025-08-14T21:17:31.7520696Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 375 <- wrt source file
2025-08-14T21:17:31.7523910Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0
2025-08-14T21:17:31.7526849Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0, line 410 <- wrt source file
2025-08-14T21:17:31.7529840Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0
2025-08-14T21:17:31.7532534Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0, line 547 <- wrt source file
2025-08-14T21:17:31.7535171Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0
2025-08-14T21:17:31.7537801Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0, line 749 <- wrt source file
2025-08-14T21:17:31.7540509Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0
2025-08-14T21:17:31.7542950Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0, line 93 <- wrt source file
2025-08-14T21:17:31.7545241Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0
2025-08-14T21:17:31.7547825Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 724 <- wrt source file
2025-08-14T21:17:31.8109484Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0
2025-08-14T21:17:31.8112743Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file
2025-08-14T21:17:31.8115356Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::IterableDataset:0
2025-08-14T21:17:31.8117858Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::StackDataset:0, line 219 <- wrt source file
2025-08-14T21:17:31.8120346Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::StackDataset:0
2025-08-14T21:17:31.8122787Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::random_split:0, line 441 <- wrt source file
2025-08-14T21:17:31.8125269Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::random_split:0
2025-08-14T21:17:31.8127648Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::Sampler:0, line 40 <- wrt source file
2025-08-14T21:17:31.8130017Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py::Sampler:0
2025-08-14T21:17:31.8132507Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file
2025-08-14T21:17:31.8135193Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0
2025-08-14T21:17:31.8137716Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file
2025-08-14T21:17:31.8140222Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0
2025-08-14T21:17:31.8142765Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 364 <- wrt source file
2025-08-14T21:17:31.8145448Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0
2025-08-14T21:17:31.8148269Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 268 <- wrt source file
2025-08-14T21:17:31.8151050Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0
2025-08-14T21:17:31.8153982Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 53 <- wrt source file
2025-08-14T21:17:31.8157069Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0
2025-08-14T21:17:31.8160122Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 201 <- wrt source file
2025-08-14T21:17:31.8163262Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0
2025-08-14T21:17:31.8166376Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 90 <- wrt source file
2025-08-14T21:17:31.8169630Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0
2025-08-14T21:17:31.8172854Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file
2025-08-14T21:17:31.8176121Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0
2025-08-14T21:17:31.8179180Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 88 <- wrt source file
2025-08-14T21:17:31.8182269Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0
2025-08-14T21:17:31.8185239Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0, line 304 <- wrt source file
2025-08-14T21:17:31.8188225Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0
2025-08-14T21:17:31.8191271Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0, line 30 <- wrt source file
2025-08-14T21:17:31.8194555Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0
2025-08-14T21:17:31.8197628Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0, line 53 <- wrt source file
2025-08-14T21:17:31.8200890Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0
2025-08-14T21:17:31.8203959Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 113 <- wrt source file
2025-08-14T21:17:31.8207102Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0
2025-08-14T21:17:31.8210317Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0, line 37 <- wrt source file
2025-08-14T21:17:31.8213396Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0
2025-08-14T21:17:31.8216754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0, line 25 <- wrt source file
2025-08-14T21:17:31.8220089Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0
2025-08-14T21:17:31.8223292Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file
2025-08-14T21:17:31.8226493Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0
2025-08-14T21:17:31.8229556Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0, line 35 <- wrt source file
2025-08-14T21:17:31.8232666Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0
2025-08-14T21:17:31.8235750Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file
2025-08-14T21:17:31.8238991Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0
2025-08-14T21:17:31.8242231Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file
2025-08-14T21:17:31.8245378Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0
2025-08-14T21:17:31.8248417Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 73 <- wrt source file
2025-08-14T21:17:31.8251469Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0
2025-08-14T21:17:31.8254454Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0, line 29 <- wrt source file
2025-08-14T21:17:31.8257535Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0
2025-08-14T21:17:31.8260598Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0, line 29 <- wrt source file
2025-08-14T21:17:31.8263742Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0
2025-08-14T21:17:31.8266746Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0, line 37 <- wrt source file
2025-08-14T21:17:31.8269755Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0
2025-08-14T21:17:31.8272751Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file
2025-08-14T21:17:31.8276584Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0
2025-08-14T21:17:31.8279368Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file
2025-08-14T21:17:31.8282268Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0
2025-08-14T21:17:31.8285034Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file
2025-08-14T21:17:31.8287900Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0
2025-08-14T21:17:31.8290726Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0, line 216 <- wrt source file
2025-08-14T21:17:31.8293581Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0
2025-08-14T21:17:31.8296424Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 314 <- wrt source file
2025-08-14T21:17:31.8299351Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0
2025-08-14T21:17:31.8302226Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0, line 362 <- wrt source file
2025-08-14T21:17:31.8305149Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0
2025-08-14T21:17:31.8308110Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0, line 394 <- wrt source file
2025-08-14T21:17:31.8311200Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0
2025-08-14T21:17:31.8314143Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0, line 441 <- wrt source file
2025-08-14T21:17:31.8317071Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0
2025-08-14T21:17:31.8319991Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 480 <- wrt source file
2025-08-14T21:17:31.8322978Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0
2025-08-14T21:17:31.8325939Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 533 <- wrt source file
2025-08-14T21:17:31.8329004Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0
2025-08-14T21:17:31.8331937Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 599 <- wrt source file
2025-08-14T21:17:31.8334824Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0
2025-08-14T21:17:31.8337680Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0, line 648 <- wrt source file
2025-08-14T21:17:31.8340566Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0
2025-08-14T21:17:31.8343394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0, line 811 <- wrt source file
2025-08-14T21:17:31.8398784Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0
2025-08-14T21:17:31.8401993Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0, line 878 <- wrt source file
2025-08-14T21:17:31.8405027Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0
2025-08-14T21:17:31.8407956Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 989 <- wrt source file
2025-08-14T21:17:31.8411076Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0
2025-08-14T21:17:31.8414221Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1063 <- wrt source file
2025-08-14T21:17:31.8417610Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0
2025-08-14T21:17:31.8420906Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1084 <- wrt source file
2025-08-14T21:17:31.8424356Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0
2025-08-14T21:17:31.8427588Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1108 <- wrt source file
2025-08-14T21:17:31.8430677Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0
2025-08-14T21:17:31.8433662Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1154 <- wrt source file
2025-08-14T21:17:31.8436539Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0
2025-08-14T21:17:31.8438027Z ============
2025-08-14T21:17:31.8438533Z Finished doctests
2025-08-14T21:17:31.8438961Z 338 / 732 passed
2025-08-14T21:17:31.8439410Z 
2025-08-14T21:17:31.8439968Z === Found 146 parse-time warnings ===
2025-08-14T21:17:31.8440747Z --- Parse Warning: 1 / 146 ---
2025-08-14T21:17:31.8442905Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493.
2025-08-14T21:17:31.8445356Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8446267Z     
2025-08-14T21:17:31.8446701Z     dim_order(ambiguity_check=False) -> tuple
2025-08-14T21:17:31.8447309Z     
2025-08-14T21:17:31.8447979Z     Returns the uniquely determined tuple of int describing the dim order or
2025-08-14T21:17:31.8448875Z     physical layout of :attr:`self`.
2025-08-14T21:17:31.8449428Z     
2025-08-14T21:17:31.8450141Z     The dim order represents how dimensions are laid out in memory of dense tensors,
2025-08-14T21:17:31.8451199Z     starting from the outermost to the innermost dimension.
2025-08-14T21:17:31.8451904Z     
2025-08-14T21:17:31.8452463Z     Note that the dim order may not always be uniquely determined.
2025-08-14T21:17:31.8453820Z     If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined;
2025-08-14T21:17:31.8455595Z     If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted
2025-08-14T21:17:31.8457278Z     into exactly one of the given memory formats, or it cannot be uniquely determined.
2025-08-14T21:17:31.8458664Z     If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness.
2025-08-14T21:17:31.8459746Z     Otherwise, it will raise TypeError.
2025-08-14T21:17:31.8460328Z     
2025-08-14T21:17:31.8460698Z     Args:
2025-08-14T21:17:31.8461562Z         ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order.
2025-08-14T21:17:31.8462574Z     
2025-08-14T21:17:31.8462957Z     Examples::
2025-08-14T21:17:31.8463362Z     
2025-08-14T21:17:31.8463762Z         >>> torch.empty((2, 3, 5, 7)).dim_order()
2025-08-14T21:17:31.8464363Z         (0, 1, 2, 3)
2025-08-14T21:17:31.8464918Z         >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order()
2025-08-14T21:17:31.8465582Z         (0, 2, 1, 3)
2025-08-14T21:17:31.8466242Z         >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order()
2025-08-14T21:17:31.8467035Z         (0, 2, 3, 1)
2025-08-14T21:17:31.8467495Z         >>> torch.empty((1, 2, 3, 4)).dim_order()
2025-08-14T21:17:31.8468083Z         (0, 1, 2, 3)
2025-08-14T21:17:31.8468512Z         >>> try:
2025-08-14T21:17:31.8469065Z         ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True)
2025-08-14T21:17:31.8469830Z         ... except RuntimeError as e:
2025-08-14T21:17:31.8470456Z         ...     print(e)
2025-08-14T21:17:31.8471490Z         The tensor does not have unique dim order, or cannot map to exact one of the given memory formats.
2025-08-14T21:17:31.8472542Z         >>> torch.empty((1, 2, 3, 4)).dim_order(
2025-08-14T21:17:31.8473370Z         ...     ambiguity_check=[torch.contiguous_format, torch.channels_last]
2025-08-14T21:17:31.8474251Z         ... )  # It can be mapped to contiguous format
2025-08-14T21:17:31.8474856Z         (0, 1, 2, 3)
2025-08-14T21:17:31.8475290Z         >>> try:
2025-08-14T21:17:31.8475893Z         ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL")
2025-08-14T21:17:31.8476661Z         ... except TypeError as e:
2025-08-14T21:17:31.8477208Z         ...     print(e)
2025-08-14T21:17:31.8477947Z         The ambiguity_check argument must be a bool or a list of memory formats.
2025-08-14T21:17:31.8478790Z     
2025-08-14T21:17:31.8479152Z     .. warning::
2025-08-14T21:17:31.8479778Z         The dim_order tensor API is experimental and subject to change.
2025-08-14T21:17:31.8480543Z     
2025-08-14T21:17:31.8481229Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8482115Z     
2025-08-14T21:17:31.8482503Z       warnings.warn(msg)
2025-08-14T21:17:31.8482960Z     
2025-08-14T21:17:31.8483551Z --- Parse Warning: 2 / 146 ---
2025-08-14T21:17:31.8485687Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=446.
2025-08-14T21:17:31.8488092Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8489298Z     Creates grids of coordinates specified by the 1D inputs in `attr`:tensors.
2025-08-14T21:17:31.8490157Z     
2025-08-14T21:17:31.8490693Z             This is helpful when you want to visualize data over some
2025-08-14T21:17:31.8491537Z             range of inputs. See below for a plotting example.
2025-08-14T21:17:31.8492219Z     
2025-08-14T21:17:31.8492737Z             Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as
2025-08-14T21:17:31.8493611Z             inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`,
2025-08-14T21:17:31.8494565Z             this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots
2025-08-14T21:17:31.8495463Z             G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where
2025-08-14T21:17:31.8496345Z             the output :math:`G_i` is constructed by expanding :math:`T_i`
2025-08-14T21:17:31.8497223Z             to the result shape.
2025-08-14T21:17:31.8497748Z     
2025-08-14T21:17:31.8498124Z             .. note::
2025-08-14T21:17:31.8498687Z                 0D inputs are treated equivalently to 1D inputs of a
2025-08-14T21:17:31.8499403Z                 single element.
2025-08-14T21:17:31.8499904Z     
2025-08-14T21:17:31.8500267Z             .. warning::
2025-08-14T21:17:31.8500911Z                 `torch.meshgrid(*tensors)` currently has the same behavior
2025-08-14T21:17:31.8501805Z                 as calling `numpy.meshgrid(*arrays, indexing='ij')`.
2025-08-14T21:17:31.8502495Z     
2025-08-14T21:17:31.8502971Z                 In the future `torch.meshgrid` will transition to
2025-08-14T21:17:31.8503693Z                 `indexing='xy'` as the default.
2025-08-14T21:17:31.8504288Z     
2025-08-14T21:17:31.8504825Z                 https://github.com/pytorch/pytorch/issues/50276 tracks
2025-08-14T21:17:31.8505727Z                 this issue with the goal of migrating to NumPy's behavior.
2025-08-14T21:17:31.8506475Z     
2025-08-14T21:17:31.8506840Z             .. seealso::
2025-08-14T21:17:31.8507293Z     
2025-08-14T21:17:31.8507807Z                 :func:`torch.cartesian_prod` has the same effect but it
2025-08-14T21:17:31.8508591Z                 collects the data in a tensor of vectors.
2025-08-14T21:17:31.8509544Z     
2025-08-14T21:17:31.8509916Z             Args:
2025-08-14T21:17:31.8510789Z                 tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be
2025-08-14T21:17:31.8511960Z                     treated as tensors of size :math:`(1,)` automatically
2025-08-14T21:17:31.8512656Z     
2025-08-14T21:17:31.8513201Z                 indexing: (str, optional): the indexing mode, either "xy"
2025-08-14T21:17:31.8514070Z                     or "ij", defaults to "ij". See warning for future changes.
2025-08-14T21:17:31.8514775Z     
2025-08-14T21:17:31.8515264Z                     If "xy" is selected, the first dimension corresponds
2025-08-14T21:17:31.8516082Z                     to the cardinality of the second input and the second
2025-08-14T21:17:31.8516948Z                     dimension corresponds to the cardinality of the first
2025-08-14T21:17:31.8517670Z                     input.
2025-08-14T21:17:31.8518136Z     
2025-08-14T21:17:31.8518602Z                     If "ij" is selected, the dimensions are in the same
2025-08-14T21:17:31.8519356Z                     order as the cardinality of the inputs.
2025-08-14T21:17:31.8519982Z     
2025-08-14T21:17:31.8520339Z             Returns:
2025-08-14T21:17:31.8520911Z                 seq (sequence of Tensors): If the input has :math:`N`
2025-08-14T21:17:31.8521734Z                 tensors of size :math:`S_0 \ldots S_{N-1}``, then the
2025-08-14T21:17:31.8522580Z                 output will also have :math:`N` tensors, where each tensor
2025-08-14T21:17:31.8523380Z                 is of shape :math:`(S_0, ..., S_{N-1})`.
2025-08-14T21:17:31.8523980Z     
2025-08-14T21:17:31.8524364Z             Example::
2025-08-14T21:17:31.8524791Z     
2025-08-14T21:17:31.8525201Z                 >>> x = torch.tensor([1, 2, 3])
2025-08-14T21:17:31.8525830Z                 >>> y = torch.tensor([4, 5, 6])
2025-08-14T21:17:31.8526395Z     
2025-08-14T21:17:31.8526958Z                 Observe the element-wise pairings across the grid, (1, 4),
2025-08-14T21:17:31.8527790Z                 (1, 5), ..., (3, 6). This is the same thing as the
2025-08-14T21:17:31.8528439Z                 cartesian product.
2025-08-14T21:17:31.8529110Z                 >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij')
2025-08-14T21:17:31.8529812Z                 >>> grid_x
2025-08-14T21:17:31.8530291Z                 tensor([[1, 1, 1],
2025-08-14T21:17:31.8530823Z                         [2, 2, 2],
2025-08-14T21:17:31.8531348Z                         [3, 3, 3]])
2025-08-14T21:17:31.8531859Z                 >>> grid_y
2025-08-14T21:17:31.8532343Z                 tensor([[4, 5, 6],
2025-08-14T21:17:31.8532865Z                         [4, 5, 6],
2025-08-14T21:17:31.8533530Z                         [4, 5, 6]])
2025-08-14T21:17:31.8534036Z     
2025-08-14T21:17:31.8534552Z                 This correspondence can be seen when these grids are
2025-08-14T21:17:31.8535291Z                 stacked properly.
2025-08-14T21:17:31.8536021Z                 >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))),
2025-08-14T21:17:31.8536878Z                 ...             torch.cartesian_prod(x, y))
2025-08-14T21:17:31.8537517Z                 True
2025-08-14T21:17:31.8537929Z     
2025-08-14T21:17:31.8538459Z                 `torch.meshgrid` is commonly used to produce a grid for
2025-08-14T21:17:31.8539193Z                 plotting.
2025-08-14T21:17:31.8539731Z                 >>> # xdoctest: +REQUIRES(module:matplotlib)
2025-08-14T21:17:31.8540440Z                 >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW)
2025-08-14T21:17:31.8541138Z                 >>> import matplotlib.pyplot as plt
2025-08-14T21:17:31.8541826Z                 >>> xs = torch.linspace(-5, 5, steps=100)
2025-08-14T21:17:31.8542491Z                 >>> ys = torch.linspace(-5, 5, steps=100)
2025-08-14T21:17:31.8543190Z                 >>> x, y = torch.meshgrid(xs, ys, indexing='xy')
2025-08-14T21:17:31.8543899Z                 >>> z = torch.sin(torch.sqrt(x * x + y * y))
2025-08-14T21:17:31.8544563Z                 >>> ax = plt.axes(projection='3d')
2025-08-14T21:17:31.8545284Z                 >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy())
2025-08-14T21:17:31.8546055Z                 >>> plt.show()
2025-08-14T21:17:31.8546545Z     
2025-08-14T21:17:31.8546978Z             .. image:: ../_static/img/meshgrid.png
2025-08-14T21:17:31.8547594Z                 :width: 512
2025-08-14T21:17:31.8548051Z     
2025-08-14T21:17:31.8548416Z             
2025-08-14T21:17:31.8549131Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8550002Z     
2025-08-14T21:17:31.8550388Z       warnings.warn(msg)
2025-08-14T21:17:31.8550856Z     
2025-08-14T21:17:31.8551584Z --- Parse Warning: 3 / 146 ---
2025-08-14T21:17:31.8553735Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=842.
2025-08-14T21:17:31.8556163Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8557663Z     unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor]
2025-08-14T21:17:31.8558797Z     
2025-08-14T21:17:31.8559285Z         Returns the unique elements of the input tensor.
2025-08-14T21:17:31.8559948Z     
2025-08-14T21:17:31.8560721Z         .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that
2025-08-14T21:17:31.8561905Z             this function also eliminates non-consecutive duplicate values.
2025-08-14T21:17:31.8562682Z     
2025-08-14T21:17:31.8563325Z         .. note:: Currently in the CUDA implementation and the CPU implementation,
2025-08-14T21:17:31.8564544Z             `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument.
2025-08-14T21:17:31.8565897Z             Sorting could be slow, so if your input tensor is already sorted, it is recommended to use
2025-08-14T21:17:31.8567016Z             :func:`torch.unique_consecutive` which avoids the sorting.
2025-08-14T21:17:31.8567736Z     
2025-08-14T21:17:31.8568088Z         Args:
2025-08-14T21:17:31.8568531Z             input (Tensor): the input tensor
2025-08-14T21:17:31.8569353Z             sorted (bool): Whether to sort the unique elements in ascending order
2025-08-14T21:17:31.8570187Z                 before returning as output.
2025-08-14T21:17:31.8571007Z             return_inverse (bool): Whether to also return the indices for where
2025-08-14T21:17:31.8572073Z                 elements in the original input ended up in the returned unique list.
2025-08-14T21:17:31.8573280Z             return_counts (bool): Whether to also return the counts for each unique
2025-08-14T21:17:31.8574113Z                 element.
2025-08-14T21:17:31.8574799Z             dim (int, optional): the dimension to operate upon. If ``None``, the
2025-08-14T21:17:31.8575819Z                 unique of the flattened input is returned. Otherwise, each of the
2025-08-14T21:17:31.8576826Z                 tensors indexed by the given dimension is treated as one of the
2025-08-14T21:17:31.8577857Z                 elements to apply the unique operation upon. See examples for more
2025-08-14T21:17:31.8578707Z                 details. Default: ``None``
2025-08-14T21:17:31.8579258Z     
2025-08-14T21:17:31.8579622Z         Returns:
2025-08-14T21:17:31.8580422Z             (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing
2025-08-14T21:17:31.8581376Z     
2025-08-14T21:17:31.8581930Z                 - **output** (*Tensor*): the output list of unique scalar elements.
2025-08-14T21:17:31.8582801Z                 - **inverse_indices** (*Tensor*): (optional) if
2025-08-14T21:17:31.8583626Z                   :attr:`return_inverse` is True, there will be an additional
2025-08-14T21:17:31.8584579Z                   returned tensor (same shape as input) representing the indices
2025-08-14T21:17:31.8585584Z                   for where elements in the original input map to in the output;
2025-08-14T21:17:31.8586603Z                   otherwise, this function will only return a single tensor.
2025-08-14T21:17:31.8587449Z                 - **counts** (*Tensor*): (optional) if
2025-08-14T21:17:31.8588229Z                   :attr:`return_counts` is True, there will be an additional
2025-08-14T21:17:31.8589150Z                   returned tensor (same shape as output or output.size(dim),
2025-08-14T21:17:31.8590099Z                   if dim was specified) representing the number of occurrences
2025-08-14T21:17:31.8590895Z                   for each unique value or tensor.
2025-08-14T21:17:31.8591552Z     
2025-08-14T21:17:31.8591928Z         Example::
2025-08-14T21:17:31.8592328Z     
2025-08-14T21:17:31.8592939Z             >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long))
2025-08-14T21:17:31.8593753Z             >>> output
2025-08-14T21:17:31.8594200Z             tensor([1, 2, 3])
2025-08-14T21:17:31.8594684Z     
2025-08-14T21:17:31.8595128Z             >>> output, inverse_indices = torch.unique(
2025-08-14T21:17:31.8596037Z             ...     torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True)
2025-08-14T21:17:31.8596875Z             >>> output
2025-08-14T21:17:31.8597331Z             tensor([1, 2, 3])
2025-08-14T21:17:31.8597835Z             >>> inverse_indices
2025-08-14T21:17:31.8598340Z             tensor([0, 2, 1, 2])
2025-08-14T21:17:31.8598834Z     
2025-08-14T21:17:31.8599271Z             >>> output, inverse_indices = torch.unique(
2025-08-14T21:17:31.8600165Z             ...     torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True)
2025-08-14T21:17:31.8601022Z             >>> output
2025-08-14T21:17:31.8601475Z             tensor([1, 2, 3])
2025-08-14T21:17:31.8601973Z             >>> inverse_indices
2025-08-14T21:17:31.8602486Z             tensor([[0, 2],
2025-08-14T21:17:31.8602968Z                     [1, 2]])
2025-08-14T21:17:31.8603439Z     
2025-08-14T21:17:31.8603814Z             >>> a = torch.tensor([
2025-08-14T21:17:31.8604345Z             ...     [
2025-08-14T21:17:31.8604793Z             ...         [1, 1, 0, 0],
2025-08-14T21:17:31.8605318Z             ...         [1, 1, 0, 0],
2025-08-14T21:17:31.8605855Z             ...         [0, 0, 1, 1],
2025-08-14T21:17:31.8606381Z             ...     ],
2025-08-14T21:17:31.8606803Z             ...     [
2025-08-14T21:17:31.8607244Z             ...         [0, 0, 1, 1],
2025-08-14T21:17:31.8607776Z             ...         [0, 0, 1, 1],
2025-08-14T21:17:31.8608296Z             ...         [1, 1, 1, 1],
2025-08-14T21:17:31.8608819Z             ...     ],
2025-08-14T21:17:31.8609650Z             ...     [
2025-08-14T21:17:31.8610087Z             ...         [1, 1, 0, 0],
2025-08-14T21:17:31.8610620Z             ...         [1, 1, 0, 0],
2025-08-14T21:17:31.8611153Z             ...         [0, 0, 1, 1],
2025-08-14T21:17:31.8611664Z             ...     ],
2025-08-14T21:17:31.8612108Z             ... ])
2025-08-14T21:17:31.8612512Z     
2025-08-14T21:17:31.8613114Z             >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]`
2025-08-14T21:17:31.8614136Z             >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match
2025-08-14T21:17:31.8615014Z             >>> # each other, so one of them will be removed.
2025-08-14T21:17:31.8615677Z             >>> (a[0, :, :] == a[2, :, :]).all()
2025-08-14T21:17:31.8616245Z             tensor(True)
2025-08-14T21:17:31.8616781Z             >>> a_unique_dim0 = torch.unique(a, dim=0)
2025-08-14T21:17:31.8617409Z             >>> a_unique_dim0
2025-08-14T21:17:31.8617915Z             tensor([[[0, 0, 1, 1],
2025-08-14T21:17:31.8618446Z                      [0, 0, 1, 1],
2025-08-14T21:17:31.8618968Z                      [1, 1, 1, 1]],
2025-08-14T21:17:31.8619492Z                     [[1, 1, 0, 0],
2025-08-14T21:17:31.8619997Z                      [1, 1, 0, 0],
2025-08-14T21:17:31.8620513Z                      [0, 0, 1, 1]]])
2025-08-14T21:17:31.8621039Z     
2025-08-14T21:17:31.8621637Z             >>> # Notice which sub-tensors from `a` match with the sub-tensors from
2025-08-14T21:17:31.8622597Z             >>> # `a_unique_dim0`:
2025-08-14T21:17:31.8623181Z             >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all()
2025-08-14T21:17:31.8623794Z             tensor(True)
2025-08-14T21:17:31.8624320Z             >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all()
2025-08-14T21:17:31.8624948Z             tensor(True)
2025-08-14T21:17:31.8625385Z     
2025-08-14T21:17:31.8625968Z             >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are
2025-08-14T21:17:31.8626938Z             >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of
2025-08-14T21:17:31.8627704Z             >>> # them will be removed.
2025-08-14T21:17:31.8628278Z             >>> (a[:, 0, :] == a[:, 1, :]).all()
2025-08-14T21:17:31.8628861Z             tensor(True)
2025-08-14T21:17:31.8629354Z             >>> torch.unique(a, dim=1)
2025-08-14T21:17:31.8629906Z             tensor([[[0, 0, 1, 1],
2025-08-14T21:17:31.8630434Z                      [1, 1, 0, 0]],
2025-08-14T21:17:31.8630956Z                     [[1, 1, 1, 1],
2025-08-14T21:17:31.8631536Z                      [0, 0, 1, 1]],
2025-08-14T21:17:31.8632064Z                     [[0, 0, 1, 1],
2025-08-14T21:17:31.8632584Z                      [1, 1, 0, 0]]])
2025-08-14T21:17:31.8633088Z     
2025-08-14T21:17:31.8633682Z             >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared.
2025-08-14T21:17:31.8634610Z             >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and
2025-08-14T21:17:31.8635469Z             >>> # `a[:, :, 3]` match each other as well. So in this case, two of the
2025-08-14T21:17:31.8636234Z             >>> # sub-tensors will be removed.
2025-08-14T21:17:31.8636853Z             >>> (a[:, :, 0] == a[:, :, 1]).all()
2025-08-14T21:17:31.8637433Z             tensor(True)
2025-08-14T21:17:31.8637905Z             >>> (a[:, :, 2] == a[:, :, 3]).all()
2025-08-14T21:17:31.8638486Z             tensor(True)
2025-08-14T21:17:31.8638984Z             >>> torch.unique(a, dim=2)
2025-08-14T21:17:31.8639545Z             tensor([[[0, 1],
2025-08-14T21:17:31.8640036Z                      [0, 1],
2025-08-14T21:17:31.8640518Z                      [1, 0]],
2025-08-14T21:17:31.8640995Z                     [[1, 0],
2025-08-14T21:17:31.8641476Z                      [1, 0],
2025-08-14T21:17:31.8641958Z                      [1, 1]],
2025-08-14T21:17:31.8642440Z                     [[0, 1],
2025-08-14T21:17:31.8642900Z                      [0, 1],
2025-08-14T21:17:31.8643481Z                      [1, 0]]])
2025-08-14T21:17:31.8643968Z         
2025-08-14T21:17:31.8644662Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8645553Z     
2025-08-14T21:17:31.8645939Z       warnings.warn(msg)
2025-08-14T21:17:31.8646389Z     
2025-08-14T21:17:31.8647022Z --- Parse Warning: 4 / 146 ---
2025-08-14T21:17:31.8649040Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=565.
2025-08-14T21:17:31.8651337Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8652247Z     
2025-08-14T21:17:31.8652745Z     Load a model from a github repo or a local directory.
2025-08-14T21:17:31.8653424Z     
2025-08-14T21:17:31.8654052Z     Note: Loading a model is the typical use case, but this can also be used to
2025-08-14T21:17:31.8655145Z     for loading other objects such as tokenizers, loss functions, etc.
2025-08-14T21:17:31.8655936Z     
2025-08-14T21:17:31.8656438Z     If ``source`` is 'github', ``repo_or_dir`` is expected to be
2025-08-14T21:17:31.8657292Z     of the form ``repo_owner/repo_name[:ref]`` with an optional
2025-08-14T21:17:31.8658018Z     ref (a tag or a branch).
2025-08-14T21:17:31.8658498Z     
2025-08-14T21:17:31.8659016Z     If ``source`` is 'local', ``repo_or_dir`` is expected to be a
2025-08-14T21:17:31.8659843Z     path to a local directory.
2025-08-14T21:17:31.8660350Z     
2025-08-14T21:17:31.8660701Z     Args:
2025-08-14T21:17:31.8661169Z         repo_or_dir (str): If ``source`` is 'github',
2025-08-14T21:17:31.8662193Z             this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with
2025-08-14T21:17:31.8663562Z             an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified,
2025-08-14T21:17:31.8664898Z             the default branch is assumed to be ``main`` if it exists, and otherwise ``master``.
2025-08-14T21:17:31.8666025Z             If ``source`` is 'local'  then it should be a path to a local directory.
2025-08-14T21:17:31.8666996Z         model (str): the name of a callable (entrypoint) defined in the
2025-08-14T21:17:31.8667798Z             repo/dir's ``hubconf.py``.
2025-08-14T21:17:31.8668571Z         *args (optional): the corresponding args for callable ``model``.
2025-08-14T21:17:31.8669523Z         source (str, optional): 'github' or 'local'. Specifies how
2025-08-14T21:17:31.8670381Z             ``repo_or_dir`` is to be interpreted. Default is 'github'.
2025-08-14T21:17:31.8671332Z         trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``.
2025-08-14T21:17:31.8672487Z             This parameter was introduced in v1.12 and helps ensuring that users
2025-08-14T21:17:31.8673389Z             only run code from repos that they trust.
2025-08-14T21:17:31.8674006Z     
2025-08-14T21:17:31.8674587Z             - If ``False``, a prompt will ask the user whether the repo should
2025-08-14T21:17:31.8675353Z               be trusted.
2025-08-14T21:17:31.8676002Z             - If ``True``, the repo will be added to the trusted list and loaded
2025-08-14T21:17:31.8676845Z               without requiring explicit confirmation.
2025-08-14T21:17:31.8677626Z             - If ``"check"``, the repo will be checked against the list of
2025-08-14T21:17:31.8678571Z               trusted repos in the cache. If it is not present in that list, the
2025-08-14T21:17:31.8679580Z               behaviour will fall back onto the ``trust_repo=False`` option.
2025-08-14T21:17:31.8680542Z             - If ``None``: this will raise a warning, inviting the user to set
2025-08-14T21:17:31.8681470Z               ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This
2025-08-14T21:17:31.8682440Z               is only present for backward compatibility and will be removed in
2025-08-14T21:17:31.8683233Z               v2.0.
2025-08-14T21:17:31.8683637Z     
2025-08-14T21:17:31.8684324Z             Default is ``None`` and will eventually change to ``"check"`` in v2.0.
2025-08-14T21:17:31.8685361Z         force_reload (bool, optional): whether to force a fresh download of
2025-08-14T21:17:31.8686371Z             the github repo unconditionally. Does not have any effect if
2025-08-14T21:17:31.8687202Z             ``source = 'local'``. Default is ``False``.
2025-08-14T21:17:31.8688029Z         verbose (bool, optional): If ``False``, mute messages about hitting
2025-08-14T21:17:31.8689056Z             local caches. Note that the message about first download cannot be
2025-08-14T21:17:31.8689998Z             muted. Does not have any effect if ``source = 'local'``.
2025-08-14T21:17:31.8690751Z             Default is ``True``.
2025-08-14T21:17:31.8691676Z         skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit
2025-08-14T21:17:31.8693044Z             specified by the ``github`` argument properly belongs to the repo owner. This will make
2025-08-14T21:17:31.8694343Z             requests to the GitHub API; you can specify a non-default GitHub token by setting the
2025-08-14T21:17:31.8695472Z             ``GITHUB_TOKEN`` environment variable. Default is ``False``.
2025-08-14T21:17:31.8696459Z         **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-08-14T21:17:31.8697255Z     
2025-08-14T21:17:31.8697629Z     Returns:
2025-08-14T21:17:31.8698276Z         The output of the ``model`` callable when called with the given
2025-08-14T21:17:31.8699093Z         ``*args`` and ``**kwargs``.
2025-08-14T21:17:31.8699618Z     
2025-08-14T21:17:31.8699991Z     Example:
2025-08-14T21:17:31.8700472Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:31.8701114Z         >>> # from a github repo
2025-08-14T21:17:31.8701666Z         >>> repo = "pytorch/vision"
2025-08-14T21:17:31.8702236Z         >>> model = torch.hub.load(
2025-08-14T21:17:31.8702947Z         ...     repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1"
2025-08-14T21:17:31.8703692Z         ... )
2025-08-14T21:17:31.8704119Z         >>> # from a local directory
2025-08-14T21:17:31.8704722Z         >>> path = "/some/local/path/pytorch/vision"
2025-08-14T21:17:31.8705377Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.8706175Z         >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT")
2025-08-14T21:17:31.8707020Z     
2025-08-14T21:17:31.8707711Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8708591Z     
2025-08-14T21:17:31.8708973Z       warnings.warn(msg)
2025-08-14T21:17:31.8709588Z     
2025-08-14T21:17:31.8710212Z --- Parse Warning: 5 / 146 ---
2025-08-14T21:17:31.8712347Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=657.
2025-08-14T21:17:31.8714693Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8715603Z     
2025-08-14T21:17:31.8716133Z     Load a model from a local directory with a ``hubconf.py``.
2025-08-14T21:17:31.8716840Z     
2025-08-14T21:17:31.8717186Z     Args:
2025-08-14T21:17:31.8717751Z         hubconf_dir (str): path to a local directory that contains a
2025-08-14T21:17:31.8718513Z             ``hubconf.py``.
2025-08-14T21:17:31.8719169Z         model (str): name of an entrypoint defined in the directory's
2025-08-14T21:17:31.8719925Z             ``hubconf.py``.
2025-08-14T21:17:31.8720621Z         *args (optional): the corresponding args for callable ``model``.
2025-08-14T21:17:31.8721618Z         **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-08-14T21:17:31.8722426Z     
2025-08-14T21:17:31.8722793Z     Returns:
2025-08-14T21:17:31.8723325Z         a single model with corresponding pretrained weights.
2025-08-14T21:17:31.8724018Z     
2025-08-14T21:17:31.8724383Z     Example:
2025-08-14T21:17:31.8725117Z         >>> # xdoctest: +SKIP("stub local path")
2025-08-14T21:17:31.8725804Z         >>> path = "/some/local/path/pytorch/vision"
2025-08-14T21:17:31.8726452Z         >>> model = _load_local(
2025-08-14T21:17:31.8726973Z         ...     path,
2025-08-14T21:17:31.8727409Z         ...     "resnet50",
2025-08-14T21:17:31.8727986Z         ...     weights="ResNet50_Weights.IMAGENET1K_V1",
2025-08-14T21:17:31.8728631Z         ... )
2025-08-14T21:17:31.8729008Z     
2025-08-14T21:17:31.8729700Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8730585Z     
2025-08-14T21:17:31.8730963Z       warnings.warn(msg)
2025-08-14T21:17:31.8731434Z     
2025-08-14T21:17:31.8731998Z --- Parse Warning: 6 / 146 ---
2025-08-14T21:17:31.8734132Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=696.
2025-08-14T21:17:31.8736565Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8737593Z     Download object at the given URL to a local path.
2025-08-14T21:17:31.8738254Z     
2025-08-14T21:17:31.8738605Z         Args:
2025-08-14T21:17:31.8739066Z             url (str): URL of the object to download
2025-08-14T21:17:31.8740035Z             dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file``
2025-08-14T21:17:31.8741411Z             hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``.
2025-08-14T21:17:31.8742466Z                 Default: None
2025-08-14T21:17:31.8743279Z             progress (bool, optional): whether or not to display a progress bar to stderr
2025-08-14T21:17:31.8744185Z                 Default: True
2025-08-14T21:17:31.8744667Z     
2025-08-14T21:17:31.8745041Z         Example:
2025-08-14T21:17:31.8745543Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:31.8746221Z             >>> # xdoctest: +REQUIRES(POSIX)
2025-08-14T21:17:31.8746859Z             >>> torch.hub.download_url_to_file(
2025-08-14T21:17:31.8747707Z             ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth",
2025-08-14T21:17:31.8748537Z             ...     "/tmp/temporary_file",
2025-08-14T21:17:31.8749101Z             ... )
2025-08-14T21:17:31.8749507Z     
2025-08-14T21:17:31.8749855Z         
2025-08-14T21:17:31.8750557Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8751504Z     
2025-08-14T21:17:31.8751884Z       warnings.warn(msg)
2025-08-14T21:17:31.8752345Z     
2025-08-14T21:17:31.8752901Z --- Parse Warning: 7 / 146 ---
2025-08-14T21:17:31.8755077Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=821.
2025-08-14T21:17:31.8757551Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8758582Z     Loads the Torch serialized object at the given URL.
2025-08-14T21:17:31.8759238Z     
2025-08-14T21:17:31.8759769Z         If downloaded file is a zip file, it will be automatically
2025-08-14T21:17:31.8760518Z         decompressed.
2025-08-14T21:17:31.8760959Z     
2025-08-14T21:17:31.8761571Z         If the object is already present in `model_dir`, it's deserialized and
2025-08-14T21:17:31.8762378Z         returned.
2025-08-14T21:17:31.8763031Z         The default value of ``model_dir`` is ``<hub_dir>/checkpoints`` where
2025-08-14T21:17:31.8764043Z         ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`.
2025-08-14T21:17:31.8764792Z     
2025-08-14T21:17:31.8765159Z         Args:
2025-08-14T21:17:31.8765629Z             url (str): URL of the object to download
2025-08-14T21:17:31.8766542Z             model_dir (str, optional): directory in which to save the object
2025-08-14T21:17:31.8767843Z             map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load)
2025-08-14T21:17:31.8769254Z             progress (bool, optional): whether or not to display a progress bar to stderr.
2025-08-14T21:17:31.8770171Z                 Default: True
2025-08-14T21:17:31.8771122Z             check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention
2025-08-14T21:17:31.8772410Z                 ``filename-<sha256>.ext`` where ``<sha256>`` is the first eight or more
2025-08-14T21:17:31.8773499Z                 digits of the SHA256 hash of the contents of the file. The hash is used to
2025-08-14T21:17:31.8774524Z                 ensure unique names and to verify the contents of the file.
2025-08-14T21:17:31.8775309Z                 Default: False
2025-08-14T21:17:31.8776308Z             file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set.
2025-08-14T21:17:31.8777834Z             weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects.
2025-08-14T21:17:31.8779189Z                 Recommended for untrusted sources. See :func:`~torch.load` for more details.
2025-08-14T21:17:31.8780085Z     
2025-08-14T21:17:31.8780453Z         Example:
2025-08-14T21:17:31.8780946Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-08-14T21:17:31.8781775Z             >>> state_dict = torch.hub.load_state_dict_from_url(
2025-08-14T21:17:31.8782683Z             ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth"
2025-08-14T21:17:31.8783481Z             ... )
2025-08-14T21:17:31.8783879Z     
2025-08-14T21:17:31.8784247Z         
2025-08-14T21:17:31.8784953Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8785812Z     
2025-08-14T21:17:31.8786193Z       warnings.warn(msg)
2025-08-14T21:17:31.8786660Z     
2025-08-14T21:17:31.8787200Z --- Parse Warning: 8 / 146 ---
2025-08-14T21:17:31.8789357Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=375.
2025-08-14T21:17:31.8791857Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.8793042Z     Registers the function implementation as the fallback for the given key.
2025-08-14T21:17:31.8793886Z     
2025-08-14T21:17:31.8794503Z             This function only works for a library with global namespace ("_").
2025-08-14T21:17:31.8795312Z     
2025-08-14T21:17:31.8795660Z             Args:
2025-08-14T21:17:31.8796451Z                 fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel`
2025-08-14T21:17:31.8797441Z                     to register a fallthrough.
2025-08-14T21:17:31.8798498Z                 dispatch_key: dispatch key that the input function should be registered for. By default, it uses
2025-08-14T21:17:31.8799677Z                               the dispatch key that the library was created with.
2025-08-14T21:17:31.8800961Z                 with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument
2025-08-14T21:17:31.8802556Z                              to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls.
2025-08-14T21:17:31.8803562Z     
2025-08-14T21:17:31.8803955Z             Example::
2025-08-14T21:17:31.8804389Z     
2025-08-14T21:17:31.8804785Z                 >>> my_lib = Library("_", "IMPL")
2025-08-14T21:17:31.8805459Z                 >>> def fallback_kernel(op, *args, **kwargs):
2025-08-14T21:17:31.8806167Z                 >>>     # Handle all autocast ops generically
2025-08-14T21:17:31.8806794Z                 >>>     # ...
2025-08-14T21:17:31.8807463Z                 >>> my_lib.fallback(fallback_kernel, "Autocast")
2025-08-14T21:17:31.8808120Z             
2025-08-14T21:17:31.8809767Z     Original Error: IndentationError('expected an indented block after function definition on line 2', ('<source_block>', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7))
2025-08-14T21:17:31.8811403Z     
2025-08-14T21:17:31.8811861Z     my_lib.fallback(fallback_kernel, "Autocast")
2025-08-14T21:17:31.8812494Z     ^
2025-08-14T21:17:31.8812880Z       warnings.warn(msg)
2025-08-14T21:17:31.8813354Z     
2025-08-14T21:17:31.8813913Z --- Parse Warning: 9 / 146 ---
2025-08-14T21:17:31.8816029Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=948.
2025-08-14T21:17:31.8818402Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.8819570Z     Register a FakeTensor implementation ("fake impl") for this operator.
2025-08-14T21:17:31.8820402Z     
2025-08-14T21:17:31.8820937Z         Also sometimes known as a "meta kernel", "abstract impl".
2025-08-14T21:17:31.8821654Z     
2025-08-14T21:17:31.8822326Z         An "FakeTensor implementation" specifies the behavior of this operator on
2025-08-14T21:17:31.8823463Z         Tensors that carry no data ("FakeTensor"). Given some input Tensors with
2025-08-14T21:17:31.8824677Z         certain properties (sizes/strides/storage_offset/device), it specifies
2025-08-14T21:17:31.8825699Z         what the properties of the output Tensors are.
2025-08-14T21:17:31.8826344Z     
2025-08-14T21:17:31.8826984Z         The FakeTensor implementation has the same signature as the operator.
2025-08-14T21:17:31.8828063Z         It is run for both FakeTensors and meta tensors. To write a FakeTensor
2025-08-14T21:17:31.8829117Z         implementation, assume that all Tensor inputs to the operator are
2025-08-14T21:17:31.8830155Z         regular CPU/CUDA/Meta tensors, but they do not have storage, and
2025-08-14T21:17:31.8831172Z         you are trying to return regular CPU/CUDA/Meta tensor(s) as output.
2025-08-14T21:17:31.8832301Z         The FakeTensor implementation must consist of only PyTorch operations
2025-08-14T21:17:31.8833353Z         (and may not directly access the storage or data of any input or
2025-08-14T21:17:31.8834129Z         intermediate Tensors).
2025-08-14T21:17:31.8834641Z     
2025-08-14T21:17:31.8835127Z         This API may be used as a decorator (see examples).
2025-08-14T21:17:31.8835779Z     
2025-08-14T21:17:31.8836240Z         For a detailed guide on custom ops, please see
2025-08-14T21:17:31.8837159Z         https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html
2025-08-14T21:17:31.8837974Z     
2025-08-14T21:17:31.8838343Z         Args:
2025-08-14T21:17:31.8839004Z             op_name: Operator name (along with the overload) or OpOverload object.
2025-08-14T21:17:31.8839891Z             func: Fake tensor implementation.
2025-08-14T21:17:31.8840692Z             lib (Optional[Library]): Library to register the fake tensor to.
2025-08-14T21:17:31.8841658Z             allow_override: Flag controlling if we want to override an
2025-08-14T21:17:31.8842563Z                             existing registered fake impl. This is by default off,
2025-08-14T21:17:31.8843449Z                             and will error you're trying to register a fake impl to
2025-08-14T21:17:31.8844351Z                             an operator that already has a fake impl. This also only
2025-08-14T21:17:31.8845230Z                             applies if the custom operator was not created via
2025-08-14T21:17:31.8846123Z                             torch.library.custom_op, as overriding and existing fake
2025-08-14T21:17:31.8846917Z                             impl is already allowed.
2025-08-14T21:17:31.8847524Z     
2025-08-14T21:17:31.8847893Z         Examples:
2025-08-14T21:17:31.8848314Z             >>> import torch
2025-08-14T21:17:31.8848962Z             >>> import numpy as np
2025-08-14T21:17:31.8849545Z             >>> from torch import Tensor
2025-08-14T21:17:31.8850102Z             >>>
2025-08-14T21:17:31.8850703Z             >>> # Example 1: an operator without data-dependent output shape
2025-08-14T21:17:31.8851713Z             >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=())
2025-08-14T21:17:31.8852778Z             >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-08-14T21:17:31.8853768Z             >>>     raise NotImplementedError("Implementation goes here")
2025-08-14T21:17:31.8854500Z             >>>
2025-08-14T21:17:31.8855060Z             >>> @torch.library.register_fake("mylib::custom_linear")
2025-08-14T21:17:31.8855778Z             >>> def _(x, weight, bias):
2025-08-14T21:17:31.8856371Z             >>>     assert x.dim() == 2
2025-08-14T21:17:31.8856975Z             >>>     assert weight.dim() == 2
2025-08-14T21:17:31.8857579Z             >>>     assert bias.dim() == 1
2025-08-14T21:17:31.8858226Z             >>>     assert x.shape[1] == weight.shape[1]
2025-08-14T21:17:31.8858919Z             >>>     assert weight.shape[0] == bias.shape[0]
2025-08-14T21:17:31.8859611Z             >>>     assert x.device == weight.device
2025-08-14T21:17:31.8860200Z             >>>
2025-08-14T21:17:31.8860650Z             >>>     return (x @ weight.t()) + bias
2025-08-14T21:17:31.8861239Z             >>>
2025-08-14T21:17:31.8861828Z             >>> with torch._subclasses.fake_tensor.FakeTensorMode():
2025-08-14T21:17:31.8862627Z             >>>     x = torch.randn(2, 3)
2025-08-14T21:17:31.8863221Z             >>>     w = torch.randn(3, 3)
2025-08-14T21:17:31.8863792Z             >>>     b = torch.randn(3)
2025-08-14T21:17:31.8864423Z             >>>     y = torch.ops.mylib.custom_linear(x, w, b)
2025-08-14T21:17:31.8865060Z             >>>
2025-08-14T21:17:31.8865495Z             >>> assert y.shape == (2, 3)
2025-08-14T21:17:31.8866038Z             >>>
2025-08-14T21:17:31.8866608Z             >>> # Example 2: an operator with data-dependent output shape
2025-08-14T21:17:31.8867588Z             >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=())
2025-08-14T21:17:31.8868461Z             >>> def custom_nonzero(x: Tensor) -> Tensor:
2025-08-14T21:17:31.8869126Z             >>>     x_np = x.numpy(force=True)
2025-08-14T21:17:31.8869791Z             >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-08-14T21:17:31.8870496Z             >>>     return torch.tensor(res, device=x.device)
2025-08-14T21:17:31.8871133Z             >>>
2025-08-14T21:17:31.8871802Z             >>> @torch.library.register_fake("mylib::custom_nonzero")
2025-08-14T21:17:31.8872520Z             >>> def _(x):
2025-08-14T21:17:31.8873082Z             >>> # Number of nonzero-elements is data-dependent.
2025-08-14T21:17:31.8873864Z             >>> # Since we cannot peek at the data in an fake impl,
2025-08-14T21:17:31.8874674Z             >>> # we use the ctx object to construct a new symint that
2025-08-14T21:17:31.8875426Z             >>> # represents the data-dependent size.
2025-08-14T21:17:31.8876096Z             >>>     ctx = torch.library.get_ctx()
2025-08-14T21:17:31.8876744Z             >>>     nnz = ctx.new_dynamic_size()
2025-08-14T21:17:31.8877358Z             >>>     shape = [nnz, x.dim()]
2025-08-14T21:17:31.8878036Z             >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-08-14T21:17:31.8878716Z             >>>     return result
2025-08-14T21:17:31.8879242Z             >>>
2025-08-14T21:17:31.8879807Z             >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-08-14T21:17:31.8880531Z             >>>
2025-08-14T21:17:31.8880986Z             >>> x = torch.tensor([0, 1, 2, 3, 4, 0])
2025-08-14T21:17:31.8881866Z             >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x)
2025-08-14T21:17:31.8882778Z             >>> trace.print_readable()
2025-08-14T21:17:31.8883338Z             >>>
2025-08-14T21:17:31.8884072Z             >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x))
2025-08-14T21:17:31.8884899Z     
2025-08-14T21:17:31.8885261Z         
2025-08-14T21:17:31.8886529Z     Original Error: IndentationError('expected an indented block after function definition on line 37', ('<source_block>', 38, 1, '_._ = None\n', 38, 2))
2025-08-14T21:17:31.8887960Z     
2025-08-14T21:17:31.8888332Z     _._ = None
2025-08-14T21:17:31.8888734Z     ^
2025-08-14T21:17:31.8889117Z       warnings.warn(msg)
2025-08-14T21:17:31.8889584Z     
2025-08-14T21:17:31.8890177Z --- Parse Warning: 10 / 146 ---
2025-08-14T21:17:31.8892355Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1083.
2025-08-14T21:17:31.8894831Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.8895851Z     Register a backward formula for this custom op.
2025-08-14T21:17:31.8896508Z     
2025-08-14T21:17:31.8897086Z         In order for an operator to work with autograd, you need to register
2025-08-14T21:17:31.8897899Z         a backward formula:
2025-08-14T21:17:31.8898606Z         1. You must tell us how to compute gradients during the backward pass
2025-08-14T21:17:31.8899443Z         by providing us a "backward" function.
2025-08-14T21:17:31.8900286Z         2. If you need any values from the forward to compute gradients, you can
2025-08-14T21:17:31.8901271Z         use `setup_context` to save values for backward.
2025-08-14T21:17:31.8901894Z     
2025-08-14T21:17:31.8902524Z         ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``:
2025-08-14T21:17:31.8903550Z         - ``grads`` is one or more gradients. The number of gradients matches
2025-08-14T21:17:31.8904374Z         the number of outputs of the operator.
2025-08-14T21:17:31.8905216Z         The ``ctx`` object is `the same ctx object <context_method_mixins>`_ used by
2025-08-14T21:17:31.8906333Z         :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the
2025-08-14T21:17:31.8907321Z         same as :meth:`torch.autograd.Function.backward`.
2025-08-14T21:17:31.8907973Z     
2025-08-14T21:17:31.8908586Z         ``setup_context(ctx, inputs, output)`` runs during the forward pass.
2025-08-14T21:17:31.8909824Z         Please save quantities needed for backward onto the ``ctx`` object via
2025-08-14T21:17:31.8910949Z         either :meth:`torch.autograd.function.FunctionCtx.save_for_backward`
2025-08-14T21:17:31.8912061Z         or assigning them as attributes of ``ctx``. If your custom op has
2025-08-14T21:17:31.8913086Z         kwarg-only arguments, we expect the signature of ``setup_context``
2025-08-14T21:17:31.8914094Z         to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``.
2025-08-14T21:17:31.8914838Z     
2025-08-14T21:17:31.8915458Z         Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is,
2025-08-14T21:17:31.8916550Z         they may not directly access :meth:`torch.Tensor.data_ptr` and they must
2025-08-14T21:17:31.8917671Z         not depend on or mutate global state. If you need a non-traceable backward,
2025-08-14T21:17:31.8918781Z         you can make it a separate custom_op that you call inside ``backward_fn``.
2025-08-14T21:17:31.8919614Z     
2025-08-14T21:17:31.8920238Z         If you need different autograd behavior on different devices, then we
2025-08-14T21:17:31.8921331Z         recommend creating two different custom operators, one for each device
2025-08-14T21:17:31.8922451Z         that needs different behavior, and switching between them at runtime.
2025-08-14T21:17:31.8923282Z     
2025-08-14T21:17:31.8923641Z         Examples:
2025-08-14T21:17:31.8924078Z             >>> import torch
2025-08-14T21:17:31.8924601Z             >>> import numpy as np
2025-08-14T21:17:31.8925166Z             >>> from torch import Tensor
2025-08-14T21:17:31.8925734Z             >>>
2025-08-14T21:17:31.8926526Z             >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=())
2025-08-14T21:17:31.8927371Z             >>> def numpy_sin(x: Tensor) -> Tensor:
2025-08-14T21:17:31.8927992Z             >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:31.8928587Z             >>>     y_np = np.sin(x_np)
2025-08-14T21:17:31.8929268Z             >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-08-14T21:17:31.8929942Z             >>>
2025-08-14T21:17:31.8930467Z             >>> def setup_context(ctx, inputs, output) -> Tensor:
2025-08-14T21:17:31.8931153Z             >>>     x, = inputs
2025-08-14T21:17:31.8931682Z             >>>     ctx.save_for_backward(x)
2025-08-14T21:17:31.8932261Z             >>>
2025-08-14T21:17:31.8932708Z             >>> def backward(ctx, grad):
2025-08-14T21:17:31.8933306Z             >>>     x, = ctx.saved_tensors
2025-08-14T21:17:31.8933886Z             >>>     return grad * x.cos()
2025-08-14T21:17:31.8934452Z             >>>
2025-08-14T21:17:31.8934927Z             >>> torch.library.register_autograd(
2025-08-14T21:17:31.8935692Z             ...     "mylib::numpy_sin", backward, setup_context=setup_context
2025-08-14T21:17:31.8936420Z             ... )
2025-08-14T21:17:31.8936825Z             >>>
2025-08-14T21:17:31.8937282Z             >>> x = torch.randn(3, requires_grad=True)
2025-08-14T21:17:31.8937909Z             >>> y = numpy_sin(x)
2025-08-14T21:17:31.8938568Z             >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-08-14T21:17:31.8939434Z             >>> assert torch.allclose(grad_x, x.cos())
2025-08-14T21:17:31.8940045Z             >>>
2025-08-14T21:17:31.8940502Z             >>> # Example with a keyword-only arg
2025-08-14T21:17:31.8941323Z             >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-08-14T21:17:31.8942211Z             >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor:
2025-08-14T21:17:31.8942912Z             >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:31.8943500Z             >>>     y_np = x_np * val
2025-08-14T21:17:31.8944157Z             >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-08-14T21:17:31.8944837Z             >>>
2025-08-14T21:17:31.8945508Z             >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor:
2025-08-14T21:17:31.8946420Z             >>>     ctx.val = keyword_only_inputs["val"]
2025-08-14T21:17:31.8947016Z             >>>
2025-08-14T21:17:31.8947454Z             >>> def backward(ctx, grad):
2025-08-14T21:17:31.8948054Z             >>>     return grad * ctx.val
2025-08-14T21:17:31.8948606Z             >>>
2025-08-14T21:17:31.8949073Z             >>> torch.library.register_autograd(
2025-08-14T21:17:31.8949853Z             ...     "mylib::numpy_mul", backward, setup_context=setup_context
2025-08-14T21:17:31.8950567Z             ... )
2025-08-14T21:17:31.8950978Z             >>>
2025-08-14T21:17:31.8951524Z             >>> x = torch.randn(3, requires_grad=True)
2025-08-14T21:17:31.8952166Z             >>> y = numpy_mul(x, val=3.14)
2025-08-14T21:17:31.8952896Z             >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-08-14T21:17:31.8953779Z             >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14))
2025-08-14T21:17:31.8954496Z     
2025-08-14T21:17:31.8954848Z         
2025-08-14T21:17:31.8955551Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.8956438Z     
2025-08-14T21:17:31.8956811Z       warnings.warn(msg)
2025-08-14T21:17:31.8957286Z     
2025-08-14T21:17:31.8957883Z --- Parse Warning: 11 / 146 ---
2025-08-14T21:17:31.8959990Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482.
2025-08-14T21:17:31.8962363Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.8963488Z     Returns the computed kernel for a given operator and dispatch key.
2025-08-14T21:17:31.8964376Z     
2025-08-14T21:17:31.8964999Z         This function retrieves the kernel that would be executed for a given
2025-08-14T21:17:31.8966117Z         operator and dispatch key combination. The returned SafeKernelFunction
2025-08-14T21:17:31.8967167Z         can be used to call the kernel in a boxed fashion. The intended use
2025-08-14T21:17:31.8968171Z         case for this function is to retrieve the original kernel for a given
2025-08-14T21:17:31.8969250Z         dispatch key and then register another kernel to the same dispatch key
2025-08-14T21:17:31.8970235Z         that calls into the original kernel for certain cases.
2025-08-14T21:17:31.8970932Z     
2025-08-14T21:17:31.8971286Z         Args:
2025-08-14T21:17:31.8971904Z             op: Operator name (along with the overload) or OpOverload object
2025-08-14T21:17:31.8972938Z                 Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef.
2025-08-14T21:17:31.8974082Z             dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for.
2025-08-14T21:17:31.8975179Z                 Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value.
2025-08-14T21:17:31.8975932Z     
2025-08-14T21:17:31.8976284Z         Returns:
2025-08-14T21:17:31.8976989Z             torch._C._SafeKernelFunction: A safe kernel function that can be used to
2025-08-14T21:17:31.8977866Z                 call the kernel.
2025-08-14T21:17:31.8978412Z     
2025-08-14T21:17:31.8978801Z         Raises:
2025-08-14T21:17:31.8979313Z             RuntimeError: If the operator does not exist.
2025-08-14T21:17:31.8979956Z     
2025-08-14T21:17:31.8980309Z         Example:
2025-08-14T21:17:31.8980779Z             >>> # Get the CPU kernel for torch.add
2025-08-14T21:17:31.8981584Z             >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU")
2025-08-14T21:17:31.8982327Z             >>>
2025-08-14T21:17:31.8982786Z             >>> # You can also use DispatchKey enum
2025-08-14T21:17:31.8983724Z             >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU)
2025-08-14T21:17:31.8984608Z             >>>
2025-08-14T21:17:31.8985047Z             >>> # Or use an OpOverload directly
2025-08-14T21:17:31.8985904Z             >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU")
2025-08-14T21:17:31.8986733Z             >>>
2025-08-14T21:17:31.8987379Z             >>> # Example: Using get_kernel in a custom op with conditional dispatch
2025-08-14T21:17:31.8988265Z             >>> # Get the original kernel for torch.sin
2025-08-14T21:17:31.8989129Z             >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU")
2025-08-14T21:17:31.8989926Z             >>>
2025-08-14T21:17:31.8990604Z             >>> # If input has negative values, use original sin, otherwise return zeros
2025-08-14T21:17:31.8991618Z             >>> def conditional_sin_impl(dispatch_keys, x):
2025-08-14T21:17:31.8992289Z             >>>     if (x < 0).any():
2025-08-14T21:17:31.8993003Z             >>>         return original_sin_kernel.call_boxed(dispatch_keys, x)
2025-08-14T21:17:31.8993758Z             >>>     else:
2025-08-14T21:17:31.8994273Z             >>>         return torch.zeros_like(x)
2025-08-14T21:17:31.8994858Z             >>>
2025-08-14T21:17:31.8995355Z             >>> lib = torch.library.Library("aten", "IMPL")
2025-08-14T21:17:31.8996336Z             >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet
2025-08-14T21:17:31.8997441Z             >>> which needs to be the first argument to ``kernel.call_boxed``
2025-08-14T21:17:31.8998382Z             >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True)
2025-08-14T21:17:31.8999142Z             >>>
2025-08-14T21:17:31.8999609Z             >>> # Test the conditional behavior
2025-08-14T21:17:31.9000259Z             >>> x_positive = torch.tensor([1.0, 2.0])
2025-08-14T21:17:31.9000923Z             >>> x_mixed = torch.tensor([-1.0, 2.0])
2025-08-14T21:17:31.9001655Z             >>> torch.sin(x_positive)
2025-08-14T21:17:31.9002212Z             tensor([0., 0.])
2025-08-14T21:17:31.9002730Z             >>> torch.sin(x_mixed)
2025-08-14T21:17:31.9003284Z             tensor([-0.8415, 0.9093])
2025-08-14T21:17:31.9003808Z         
2025-08-14T21:17:31.9004969Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12))
2025-08-14T21:17:31.9006306Z     
2025-08-14T21:17:31.9006850Z     which needs to be the first argument to ``kernel.call_boxed``
2025-08-14T21:17:31.9007568Z           ^
2025-08-14T21:17:31.9007966Z       warnings.warn(msg)
2025-08-14T21:17:31.9008429Z     
2025-08-14T21:17:31.9008985Z --- Parse Warning: 12 / 146 ---
2025-08-14T21:17:31.9011229Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1571.
2025-08-14T21:17:31.9013614Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9014777Z     Given an operator and some sample arguments, tests if the operator is
2025-08-14T21:17:31.9015605Z         registered correctly.
2025-08-14T21:17:31.9016106Z     
2025-08-14T21:17:31.9016714Z         That is, when you use the torch.library/TORCH_LIBRARY APIs to create a
2025-08-14T21:17:31.9017911Z         custom op, you specified metadata (e.g. mutability info) about the custom op
2025-08-14T21:17:31.9019111Z         and these APIs require that the functions you pass them satisfy certain
2025-08-14T21:17:31.9020220Z         properties (e.g. no data pointer access in the fake/meta/abstract kernel)
2025-08-14T21:17:31.9021155Z         ``opcheck`` tests these metadata and properties.
2025-08-14T21:17:31.9021805Z     
2025-08-14T21:17:31.9022221Z         Concretely, we test the following:
2025-08-14T21:17:31.9022798Z     
2025-08-14T21:17:31.9023321Z         - test_schema: If the schema matches the implementation of
2025-08-14T21:17:31.9024304Z           the operator. For example: if the schema specifies a Tensor is mutated,
2025-08-14T21:17:31.9024694Z           then we check the implementation mutates the Tensor. If the schema
2025-08-14T21:17:31.9025065Z           specifies that we return a new Tensor, then we check that the
2025-08-14T21:17:31.9025483Z           implementation returns a new Tensor (instead of an existing one or
2025-08-14T21:17:31.9025685Z           a view of an existing one).
2025-08-14T21:17:31.9026084Z         - test_autograd_registration: If the operator supports training
2025-08-14T21:17:31.9026442Z           (autograd): we check that its autograd formula is registered via
2025-08-14T21:17:31.9026851Z           torch.library.register_autograd or a manual registration to one
2025-08-14T21:17:31.9027233Z           or more DispatchKey::Autograd keys. Any other DispatchKey-based
2025-08-14T21:17:31.9027495Z           registrations may lead to undefined behavior.
2025-08-14T21:17:31.9027847Z         - test_faketensor: If the operator has a FakeTensor kernel
2025-08-14T21:17:31.9028165Z           (and if it is correct). The FakeTensor kernel is necessary (
2025-08-14T21:17:31.9028584Z           but not sufficient) for the operator to work with PyTorch compilation
2025-08-14T21:17:31.9028990Z           APIs (torch.compile/export/FX). We check that a FakeTensor kernel
2025-08-14T21:17:31.9029355Z           (also sometimes known as a meta kernel) was registered for the
2025-08-14T21:17:31.9029729Z           operator and that it is correct. This test takes the result of
2025-08-14T21:17:31.9030097Z           running the operator on real tensors and the result of running
2025-08-14T21:17:31.9030459Z           the operator on FakeTensors and checks that they have the same
2025-08-14T21:17:31.9030753Z           Tensor metadata (sizes/strides/dtype/device/etc).
2025-08-14T21:17:31.9031134Z         - test_aot_dispatch_dynamic: If the operator has correct behavior
2025-08-14T21:17:31.9031628Z           with PyTorch compilation APIs (torch.compile/export/FX).
2025-08-14T21:17:31.9032044Z           This checks that the outputs (and gradients, if applicable) are the
2025-08-14T21:17:31.9032312Z           same under eager-mode PyTorch and torch.compile.
2025-08-14T21:17:31.9032685Z           This test is a superset of ``test_faketensor`` and is an e2e test;
2025-08-14T21:17:31.9032982Z           other things it tests are that the operator supports
2025-08-14T21:17:31.9033393Z           functionalization and that the backward pass (if it exists) also
2025-08-14T21:17:31.9033664Z           supports FakeTensor and functionalization.
2025-08-14T21:17:31.9033816Z     
2025-08-14T21:17:31.9034182Z         For best results, please call ``opcheck`` multiple times with a
2025-08-14T21:17:31.9034538Z         representative set of inputs. If your operator supports
2025-08-14T21:17:31.9034983Z         autograd, please use ``opcheck`` with inputs with ``requires_grad = True``;
2025-08-14T21:17:31.9035429Z         if your operator supports multiple devices (e.g. CPU and CUDA), please
2025-08-14T21:17:31.9035716Z         use ``opcheck`` with inputs on all supported devices.
2025-08-14T21:17:31.9035873Z     
2025-08-14T21:17:31.9036047Z         Args:
2025-08-14T21:17:31.9036372Z             op: The operator. Must either be a function decorated with
2025-08-14T21:17:31.9036770Z                 :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket
2025-08-14T21:17:31.9037245Z                 found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo)
2025-08-14T21:17:31.9037449Z             args: The args to the operator
2025-08-14T21:17:31.9037676Z             kwargs: The kwargs to the operator
2025-08-14T21:17:31.9038014Z             test_utils: Tests that we should run. Default: all of them.
2025-08-14T21:17:31.9038253Z                 Example: ("test_schema", "test_faketensor")
2025-08-14T21:17:31.9038624Z             raise_exception: If we should raise an exception on the first
2025-08-14T21:17:31.9038934Z                 error. If False, we will return a dict with information
2025-08-14T21:17:31.9039142Z                 on if each test passed or not.
2025-08-14T21:17:31.9039605Z             rtol (Optional[float]): Relative tolerance for floating point comparisons.
2025-08-14T21:17:31.9039854Z                 If specified ``atol`` must also be specified.
2025-08-14T21:17:31.9040223Z                 If omitted, default values based on the ``dtype`` are selected
2025-08-14T21:17:31.9040526Z                 (see the table in :func:`torch.testing.assert_close`).
2025-08-14T21:17:31.9040972Z             atol (Optional[float]): Absolute tolerance for floating point comparisons.
2025-08-14T21:17:31.9041234Z                 If specified ``rtol`` must also be specified.
2025-08-14T21:17:31.9041585Z                 If omitted, default values based on the ``dtype`` are selected
2025-08-14T21:17:31.9041884Z                 (see the table in :func:`torch.testing.assert_close`).
2025-08-14T21:17:31.9042049Z     
2025-08-14T21:17:31.9042223Z         .. warning::
2025-08-14T21:17:31.9042372Z     
2025-08-14T21:17:31.9042787Z             opcheck and :func:`torch.autograd.gradcheck` test different things;
2025-08-14T21:17:31.9043177Z             opcheck tests if your usage of torch.library APIs is correct while
2025-08-14T21:17:31.9043585Z             :func:`torch.autograd.gradcheck` tests if your autograd formula is
2025-08-14T21:17:31.9043995Z             mathematically correct. Use both to test custom ops that support
2025-08-14T21:17:31.9044183Z             gradient computation.
2025-08-14T21:17:31.9044347Z     
2025-08-14T21:17:31.9044508Z         Example:
2025-08-14T21:17:31.9044655Z     
2025-08-14T21:17:31.9044915Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:31.9045287Z             >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-08-14T21:17:31.9045549Z             >>> def numpy_mul(x: Tensor, y: float) -> Tensor:
2025-08-14T21:17:31.9045815Z             >>>     x_np = x.numpy(force=True)
2025-08-14T21:17:31.9045993Z             >>>     z_np = x_np * y
2025-08-14T21:17:31.9046251Z             >>>     return torch.from_numpy(z_np).to(x.device)
2025-08-14T21:17:31.9046405Z             >>>
2025-08-14T21:17:31.9046599Z             >>> @numpy_mul.register_fake
2025-08-14T21:17:31.9046781Z             >>> def _(x, y):
2025-08-14T21:17:31.9046984Z             >>>     return torch.empty_like(x)
2025-08-14T21:17:31.9047140Z             >>>
2025-08-14T21:17:31.9047389Z             >>> def setup_context(ctx, inputs, output):
2025-08-14T21:17:31.9047554Z             >>>     y, = inputs
2025-08-14T21:17:31.9047722Z             >>>     ctx.y = y
2025-08-14T21:17:31.9047890Z             >>>
2025-08-14T21:17:31.9048086Z             >>> def backward(ctx, grad):
2025-08-14T21:17:31.9048295Z             >>>     return grad * ctx.y, None
2025-08-14T21:17:31.9048450Z             >>>
2025-08-14T21:17:31.9048870Z             >>> numpy_mul.register_autograd(backward, setup_context=setup_context)
2025-08-14T21:17:31.9049040Z             >>>
2025-08-14T21:17:31.9049222Z             >>> sample_inputs = [
2025-08-14T21:17:31.9049412Z             >>>     (torch.randn(3), 3.14),
2025-08-14T21:17:31.9068736Z             >>>     (torch.randn(2, 3, device='cuda'), 2.718),
2025-08-14T21:17:31.9069145Z             >>>     (torch.randn(1, 10, requires_grad=True), 1.234),
2025-08-14T21:17:31.9069501Z             >>>     (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18),
2025-08-14T21:17:31.9069825Z             >>> ]
2025-08-14T21:17:31.9069977Z             >>>
2025-08-14T21:17:31.9070172Z             >>> for args in sample_inputs:
2025-08-14T21:17:31.9070412Z             >>>     torch.library.opcheck(numpy_mul, args)
2025-08-14T21:17:31.9070560Z     
2025-08-14T21:17:31.9070706Z         
2025-08-14T21:17:31.9071186Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9071331Z     
2025-08-14T21:17:31.9071605Z       warnings.warn(msg)
2025-08-14T21:17:31.9071759Z     
2025-08-14T21:17:31.9072173Z --- Parse Warning: 13 / 146 ---
2025-08-14T21:17:31.9073830Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285.
2025-08-14T21:17:31.9074344Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9074974Z     load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args)
2025-08-14T21:17:31.9075123Z     
2025-08-14T21:17:31.9075447Z         Loads an object saved with :func:`torch.save` from a file.
2025-08-14T21:17:31.9075590Z     
2025-08-14T21:17:31.9076032Z         :func:`torch.load` uses Python's unpickling facilities but treats storages,
2025-08-14T21:17:31.9076460Z         which underlie tensors, specially. They are first deserialized on the
2025-08-14T21:17:31.9076863Z         CPU and are then moved to the device they were saved from. If this fails
2025-08-14T21:17:31.9077302Z         (e.g. because the run time system doesn't have certain devices), an exception
2025-08-14T21:17:31.9077748Z         is raised. However, storages can be dynamically remapped to an alternative
2025-08-14T21:17:31.9078042Z         set of devices using the :attr:`map_location` argument.
2025-08-14T21:17:31.9078202Z     
2025-08-14T21:17:31.9078649Z         If :attr:`map_location` is a callable, it will be called once for each serialized
2025-08-14T21:17:31.9079071Z         storage with two arguments: storage and location. The storage argument
2025-08-14T21:17:31.9079509Z         will be the initial deserialization of the storage, residing on the CPU.
2025-08-14T21:17:31.9079906Z         Each serialized storage has a location tag associated with it which
2025-08-14T21:17:31.9080310Z         identifies the device it was saved from, and this tag is the second
2025-08-14T21:17:31.9080859Z         argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'``
2025-08-14T21:17:31.9081283Z         for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors.
2025-08-14T21:17:31.9081656Z         :attr:`map_location` should return either ``None`` or a storage. If
2025-08-14T21:17:31.9082132Z         :attr:`map_location` returns a storage, it will be used as the final deserialized
2025-08-14T21:17:31.9082597Z         object, already moved to the right device. Otherwise, :func:`torch.load` will
2025-08-14T21:17:31.9083056Z         fall back to the default behavior, as if :attr:`map_location` wasn't specified.
2025-08-14T21:17:31.9083209Z     
2025-08-14T21:17:31.9083666Z         If :attr:`map_location` is a :class:`torch.device` object or a string containing
2025-08-14T21:17:31.9084104Z         a device tag, it indicates the location where all tensors should be loaded.
2025-08-14T21:17:31.9084256Z     
2025-08-14T21:17:31.9084763Z         Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags
2025-08-14T21:17:31.9085149Z         appearing in the file (keys), to ones that specify where to put the
2025-08-14T21:17:31.9085327Z         storages (values).
2025-08-14T21:17:31.9085493Z     
2025-08-14T21:17:31.9085912Z         User extensions can register their own location tags and tagging and
2025-08-14T21:17:31.9086428Z         deserialization methods using :func:`torch.serialization.register_package`.
2025-08-14T21:17:31.9086614Z     
2025-08-14T21:17:31.9087111Z         See :ref:`layout-control` for more advanced tools to manipulate a checkpoint.
2025-08-14T21:17:31.9087270Z     
2025-08-14T21:17:31.9087426Z         Args:
2025-08-14T21:17:31.9088039Z             f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`),
2025-08-14T21:17:31.9088365Z                 or a string or os.PathLike object containing a file name
2025-08-14T21:17:31.9088988Z             map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage
2025-08-14T21:17:31.9089167Z                 locations
2025-08-14T21:17:31.9089594Z             pickle_module: module used for unpickling metadata and objects (has to
2025-08-14T21:17:31.9089906Z                 match the :attr:`pickle_module` used to serialize file)
2025-08-14T21:17:31.9090315Z             weights_only: Indicates whether unpickler should be restricted to
2025-08-14T21:17:31.9090611Z                 loading only tensors, primitive types, dictionaries
2025-08-14T21:17:31.9091019Z                 and any types added via :func:`torch.serialization.add_safe_globals`.
2025-08-14T21:17:31.9091269Z                 See :ref:`weights-only` for more details.
2025-08-14T21:17:31.9091918Z             mmap: Indicates whether the file should be mapped rather than loading all the storages into memory.
2025-08-14T21:17:31.9092582Z                 Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they
2025-08-14T21:17:31.9093247Z                 are moved to the location that they were tagged with when saving, or specified by ``map_location``. This
2025-08-14T21:17:31.9093875Z                 second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the
2025-08-14T21:17:31.9094528Z                 tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages
2025-08-14T21:17:31.9094805Z                 will be lazily loaded when their data is accessed.
2025-08-14T21:17:31.9095278Z             pickle_load_args: (Python 3 only) optional keyword arguments passed over to
2025-08-14T21:17:31.9095691Z                 :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g.,
2025-08-14T21:17:31.9095872Z                 :attr:`errors=...`.
2025-08-14T21:17:31.9096035Z     
2025-08-14T21:17:31.9096208Z         .. warning::
2025-08-14T21:17:31.9096597Z             :func:`torch.load()` unless `weights_only` parameter is set to `True`,
2025-08-14T21:17:31.9097063Z             uses ``pickle`` module implicitly, which is known to be insecure.
2025-08-14T21:17:31.9097595Z             It is possible to construct malicious pickle data which will execute arbitrary code
2025-08-14T21:17:31.9098062Z             during unpickling. Never load data that could have come from an untrusted
2025-08-14T21:17:31.9098630Z             source in an unsafe mode, or that could have been tampered with. **Only load data you trust**.
2025-08-14T21:17:31.9098789Z     
2025-08-14T21:17:31.9098963Z         .. note::
2025-08-14T21:17:31.9099452Z             When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors
2025-08-14T21:17:31.9099939Z             will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')``
2025-08-14T21:17:31.9100468Z             and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint.
2025-08-14T21:17:31.9100619Z     
2025-08-14T21:17:31.9100795Z         .. note::
2025-08-14T21:17:31.9101263Z             By default, we decode byte strings as ``utf-8``.  This is to avoid a common error
2025-08-14T21:17:31.9101672Z             case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...``
2025-08-14T21:17:31.9102080Z             when loading files saved by Python 2 in Python 3.  If this default
2025-08-14T21:17:31.9102559Z             is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how
2025-08-14T21:17:31.9103078Z             these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them
2025-08-14T21:17:31.9103540Z             to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them
2025-08-14T21:17:31.9103975Z             as byte arrays which can be decoded later with ``byte_array.decode(...)``.
2025-08-14T21:17:31.9104146Z     
2025-08-14T21:17:31.9104304Z         Example:
2025-08-14T21:17:31.9104539Z             >>> # xdoctest: +SKIP("undefined filepaths")
2025-08-14T21:17:31.9104811Z             >>> torch.load("tensors.pt", weights_only=True)
2025-08-14T21:17:31.9105019Z             # Load all tensors onto the CPU
2025-08-14T21:17:31.9105193Z             >>> torch.load(
2025-08-14T21:17:31.9105384Z             ...     "tensors.pt",
2025-08-14T21:17:31.9105614Z             ...     map_location=torch.device("cpu"),
2025-08-14T21:17:31.9105800Z             ...     weights_only=True,
2025-08-14T21:17:31.9105973Z             ... )
2025-08-14T21:17:31.9106238Z             # Load all tensors onto the CPU, using a function
2025-08-14T21:17:31.9106425Z             >>> torch.load(
2025-08-14T21:17:31.9106603Z             ...     "tensors.pt",
2025-08-14T21:17:31.9106855Z             ...     map_location=lambda storage, loc: storage,
2025-08-14T21:17:31.9107055Z             ...     weights_only=True,
2025-08-14T21:17:31.9107217Z             ... )
2025-08-14T21:17:31.9107416Z             # Load all tensors onto GPU 1
2025-08-14T21:17:31.9107598Z             >>> torch.load(
2025-08-14T21:17:31.9107779Z             ...     "tensors.pt",
2025-08-14T21:17:31.9108073Z             ...     map_location=lambda storage, loc: storage.cuda(1),
2025-08-14T21:17:31.9108275Z             ...     weights_only=True,
2025-08-14T21:17:31.9108486Z             ... )  # type: ignore[attr-defined]
2025-08-14T21:17:31.9108707Z             # Map tensors from GPU 1 to GPU 0
2025-08-14T21:17:31.9108876Z             >>> torch.load(
2025-08-14T21:17:31.9109253Z             ...     "tensors.pt",
2025-08-14T21:17:31.9109498Z             ...     map_location={"cuda:1": "cuda:0"},
2025-08-14T21:17:31.9109684Z             ...     weights_only=True,
2025-08-14T21:17:31.9109840Z             ... )
2025-08-14T21:17:31.9110073Z             # Load tensor from io.BytesIO object
2025-08-14T21:17:31.9110551Z             # Loading from a buffer setting weights_only=False, warning this can be unsafe
2025-08-14T21:17:31.9110768Z             >>> with open("tensor.pt", "rb") as f:
2025-08-14T21:17:31.9110985Z             ...     buffer = io.BytesIO(f.read())
2025-08-14T21:17:31.9111354Z             >>> torch.load(buffer, weights_only=False)
2025-08-14T21:17:31.9111711Z             # Load a module with 'ascii' encoding for unpickling
2025-08-14T21:17:31.9112183Z             # Loading from a module setting weights_only=False, warning this can be unsafe
2025-08-14T21:17:31.9112545Z             >>> torch.load("module.pt", encoding="ascii", weights_only=False)
2025-08-14T21:17:31.9112724Z         
2025-08-14T21:17:31.9113210Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9113364Z     
2025-08-14T21:17:31.9113560Z       warnings.warn(msg)
2025-08-14T21:17:31.9113713Z     
2025-08-14T21:17:31.9114094Z --- Parse Warning: 14 / 146 ---
2025-08-14T21:17:31.9116095Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1851.
2025-08-14T21:17:31.9116606Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9117043Z     Computes the minimum storage size to hold the given tensor geometry.
2025-08-14T21:17:31.9117195Z     
2025-08-14T21:17:31.9117358Z         Example
2025-08-14T21:17:31.9117528Z         =======
2025-08-14T21:17:31.9117678Z     
2025-08-14T21:17:31.9118105Z         This is the size of a newly allocated tensor's storage, in units of elements
2025-08-14T21:17:31.9118369Z     
2025-08-14T21:17:31.9118559Z         >>> t = torch.empty((10, 20))
2025-08-14T21:17:31.9119020Z         >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset())
2025-08-14T21:17:31.9119193Z         200
2025-08-14T21:17:31.9119344Z     
2025-08-14T21:17:31.9119556Z         >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:31.9119794Z         >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11))
2025-08-14T21:17:31.9120020Z         >>> size = compute_required_storage_length(
2025-08-14T21:17:31.9120279Z         ...     t2.shape, t2.stride(), t2.storage_offset()
2025-08-14T21:17:31.9120434Z         ... )
2025-08-14T21:17:31.9120625Z         >>> size == t.storage().size()
2025-08-14T21:17:31.9120793Z         True
2025-08-14T21:17:31.9120945Z     
2025-08-14T21:17:31.9121313Z         A valid tensor may have a larger storage size, but never smaller
2025-08-14T21:17:31.9121479Z     
2025-08-14T21:17:31.9121680Z         >>> slice = torch.empty(100)[20:40]
2025-08-14T21:17:31.9121879Z         >>> slice.storage().size()
2025-08-14T21:17:31.9122041Z         100
2025-08-14T21:17:31.9122192Z     
2025-08-14T21:17:31.9122416Z         >>> compute_required_storage_length(
2025-08-14T21:17:31.9122715Z         ...     slice.shape, slice.stride(), slice.storage_offset()
2025-08-14T21:17:31.9122869Z         ... )
2025-08-14T21:17:31.9123039Z         40
2025-08-14T21:17:31.9123191Z     
2025-08-14T21:17:31.9123344Z         
2025-08-14T21:17:31.9123845Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9123998Z     
2025-08-14T21:17:31.9124178Z       warnings.warn(msg)
2025-08-14T21:17:31.9124343Z     
2025-08-14T21:17:31.9124680Z --- Parse Warning: 15 / 146 ---
2025-08-14T21:17:31.9126480Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66.
2025-08-14T21:17:31.9126957Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.9127436Z     Check if the current accelerator is available at runtime: it was build, all the
2025-08-14T21:17:31.9127857Z         required drivers are available and at least one device is visible.
2025-08-14T21:17:31.9128123Z         See :ref:`accelerator<accelerators>` for details.
2025-08-14T21:17:31.9128275Z     
2025-08-14T21:17:31.9128447Z         Returns:
2025-08-14T21:17:31.9129048Z             bool: A boolean indicating if there is an available :ref:`accelerator<accelerators>`.
2025-08-14T21:17:31.9129213Z     
2025-08-14T21:17:31.9129675Z         .. note:: This API delegates to the device-specific version of `is_available`.
2025-08-14T21:17:31.9130170Z             On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set,
2025-08-14T21:17:31.9130653Z             this function will NOT poison fork. Otherwise, it will. For more details, see
2025-08-14T21:17:31.9130915Z             :ref:`multiprocessing-poison-fork-note`.
2025-08-14T21:17:31.9131068Z     
2025-08-14T21:17:31.9131250Z         Example::
2025-08-14T21:17:31.9131404Z     
2025-08-14T21:17:31.9131912Z             >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:31.9132083Z         
2025-08-14T21:17:31.9133186Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78))
2025-08-14T21:17:31.9133362Z     
2025-08-14T21:17:31.9133865Z     assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:31.9134041Z                                             ^
2025-08-14T21:17:31.9134232Z       warnings.warn(msg)
2025-08-14T21:17:31.9134385Z     
2025-08-14T21:17:31.9134714Z --- Parse Warning: 16 / 146 ---
2025-08-14T21:17:31.9136555Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212.
2025-08-14T21:17:31.9137064Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.9137465Z     Wait for all kernels in all streams on the given device to complete.
2025-08-14T21:17:31.9137621Z     
2025-08-14T21:17:31.9137778Z         Args:
2025-08-14T21:17:31.9138401Z             device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match
2025-08-14T21:17:31.9138827Z                 the current :ref:`accelerator<accelerators>` device type. If not given,
2025-08-14T21:17:31.9139188Z                 use :func:`torch.accelerator.current_device_index` by default.
2025-08-14T21:17:31.9139349Z     
2025-08-14T21:17:31.9139945Z         .. note:: This function is a no-op if the current :ref:`accelerator<accelerators>` is not initialized.
2025-08-14T21:17:31.9140116Z     
2025-08-14T21:17:31.9140285Z         Example::
2025-08-14T21:17:31.9140431Z     
2025-08-14T21:17:31.9140699Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:31.9141212Z             >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:31.9141471Z             >>> start_event = torch.Event(enable_timing=True)
2025-08-14T21:17:31.9141733Z             >>> end_event = torch.Event(enable_timing=True)
2025-08-14T21:17:31.9141921Z             >>> start_event.record()
2025-08-14T21:17:31.9142385Z             >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator())
2025-08-14T21:17:31.9142574Z             >>> sum = torch.sum(tensor)
2025-08-14T21:17:31.9142755Z             >>> end_event.record()
2025-08-14T21:17:31.9142996Z             >>> torch.accelerator.synchronize()
2025-08-14T21:17:31.9143305Z             >>> elapsed_time_ms = start_event.elapsed_time(end_event)
2025-08-14T21:17:31.9143463Z         
2025-08-14T21:17:31.9144575Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78))
2025-08-14T21:17:31.9144727Z     
2025-08-14T21:17:31.9145228Z     assert torch.accelerator.is_available() "No available accelerators detected."
2025-08-14T21:17:31.9145418Z                                             ^
2025-08-14T21:17:31.9145595Z       warnings.warn(msg)
2025-08-14T21:17:31.9145758Z     
2025-08-14T21:17:31.9146154Z --- Parse Warning: 17 / 146 ---
2025-08-14T21:17:31.9147818Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434.
2025-08-14T21:17:31.9148302Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.9148521Z     Retrieves the CUDA runtime API module.
2025-08-14T21:17:31.9148675Z     
2025-08-14T21:17:31.9148842Z     
2025-08-14T21:17:31.9149322Z         This function initializes the CUDA runtime environment if it is not already
2025-08-14T21:17:31.9149771Z         initialized and returns the CUDA runtime API module (_cudart). The CUDA
2025-08-14T21:17:31.9150200Z         runtime API module provides access to various CUDA runtime functions.
2025-08-14T21:17:31.9150351Z     
2025-08-14T21:17:31.9150516Z         Args:
2025-08-14T21:17:31.9150673Z             ``None``
2025-08-14T21:17:31.9150823Z     
2025-08-14T21:17:31.9150996Z         Returns:
2025-08-14T21:17:31.9151252Z             module: The CUDA runtime API module (_cudart).
2025-08-14T21:17:31.9151498Z     
2025-08-14T21:17:31.9151669Z         Raises:
2025-08-14T21:17:31.9152107Z             RuntimeError: If CUDA cannot be re-initialized in a forked subprocess.
2025-08-14T21:17:31.9152804Z             AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable.
2025-08-14T21:17:31.9153039Z     
2025-08-14T21:17:31.9153276Z         Example of CUDA operations with profiling:
2025-08-14T21:17:31.9153465Z             >>> import torch
2025-08-14T21:17:31.9153708Z             >>> from torch.cuda import cudart, check_error
2025-08-14T21:17:31.9153876Z             >>> import os
2025-08-14T21:17:31.9154041Z             >>>
2025-08-14T21:17:31.9154250Z             >>> os.environ["CUDA_PROFILE"] = "1"
2025-08-14T21:17:31.9154405Z             >>>
2025-08-14T21:17:31.9154672Z             >>> def perform_cuda_operations_with_streams():
2025-08-14T21:17:31.9154882Z             >>>     stream = torch.cuda.Stream()
2025-08-14T21:17:31.9155099Z             >>>     with torch.cuda.stream(stream):
2025-08-14T21:17:31.9155340Z             >>>         x = torch.randn(100, 100, device='cuda')
2025-08-14T21:17:31.9155565Z             >>>         y = torch.randn(100, 100, device='cuda')
2025-08-14T21:17:31.9155765Z             >>>         z = torch.mul(x, y)
2025-08-14T21:17:31.9155935Z             >>>     return z
2025-08-14T21:17:31.9156091Z             >>>
2025-08-14T21:17:31.9156313Z             >>> torch.cuda.synchronize()
2025-08-14T21:17:31.9156553Z             >>> print("====== Start nsys profiling ======")
2025-08-14T21:17:31.9156797Z             >>> check_error(cudart().cudaProfilerStart())
2025-08-14T21:17:31.9157065Z             >>> with torch.autograd.profiler.emit_nvtx():
2025-08-14T21:17:31.9157339Z             >>>     result = perform_cuda_operations_with_streams()
2025-08-14T21:17:31.9157575Z             >>>     print("CUDA operations completed.")
2025-08-14T21:17:31.9157885Z             >>> check_error(torch.cuda.cudart().cudaProfilerStop())
2025-08-14T21:17:31.9158112Z             >>> print("====== End nsys profiling ======")
2025-08-14T21:17:31.9158276Z     
2025-08-14T21:17:31.9158646Z         To run this example and save the profiling information, execute:
2025-08-14T21:17:31.9159333Z             >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-08-14T21:17:31.9159508Z     
2025-08-14T21:17:31.9159973Z         This command profiles the CUDA operations in the provided script and saves
2025-08-14T21:17:31.9160338Z         the profiling information to a file named `trace_name.prof`.
2025-08-14T21:17:31.9160790Z         The `--profile-from-start off` option ensures that profiling starts only
2025-08-14T21:17:31.9161058Z         after the `cudaProfilerStart` call in the script.
2025-08-14T21:17:31.9161570Z         The `--csv` and `--print-summary` options format the profiling output as a
2025-08-14T21:17:31.9161811Z         CSV file and print a summary, respectively.
2025-08-14T21:17:31.9162277Z         The `-o` option specifies the output file name, and the `-f` option forces the
2025-08-14T21:17:31.9162575Z         overwrite of the output file if it already exists.
2025-08-14T21:17:31.9162734Z         
2025-08-14T21:17:31.9164006Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2))
2025-08-14T21:17:31.9164184Z     
2025-08-14T21:17:31.9164859Z     $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-08-14T21:17:31.9165032Z     ^
2025-08-14T21:17:31.9165211Z       warnings.warn(msg)
2025-08-14T21:17:31.9165360Z     
2025-08-14T21:17:31.9165725Z --- Parse Warning: 18 / 146 ---
2025-08-14T21:17:31.9167466Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101.
2025-08-14T21:17:31.9167964Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9168135Z     
2025-08-14T21:17:31.9168575Z     Append the given callback function to this ``Future``, which will be run
2025-08-14T21:17:31.9169018Z     when the ``Future`` is completed.  Multiple callbacks can be added to
2025-08-14T21:17:31.9169438Z     the same ``Future``, but the order in which they will be executed cannot
2025-08-14T21:17:31.9169782Z     be guaranteed (to enforce a certain order consider chaining:
2025-08-14T21:17:31.9170172Z     ``fut.then(cb1).then(cb2)``). The callback must take one argument, which
2025-08-14T21:17:31.9170563Z     is the reference to this ``Future``. The callback function can use the
2025-08-14T21:17:31.9170955Z     :meth:`value` method to get the value. Note that if this ``Future`` is
2025-08-14T21:17:31.9171400Z     already completed, the given callback will be run immediately inline.
2025-08-14T21:17:31.9171552Z     
2025-08-14T21:17:31.9171922Z     If the ``Future``'s value contains tensors that reside on GPUs, the
2025-08-14T21:17:31.9172339Z     callback might be invoked while the async kernels that are populating
2025-08-14T21:17:31.9172771Z     those tensors haven't yet finished executing on the device. However, the
2025-08-14T21:17:31.9173180Z     callback will be invoked with some dedicated streams set as current
2025-08-14T21:17:31.9173565Z     (fetched from a global pool) which will be synchronized with those
2025-08-14T21:17:31.9173991Z     kernels. Hence any operation performed by the callback on these tensors
2025-08-14T21:17:31.9174400Z     will be scheduled on the device after the kernels complete. In other
2025-08-14T21:17:31.9174770Z     words, as long as the callback doesn't switch streams, it can safely
2025-08-14T21:17:31.9175222Z     manipulate the result without any additional synchronization. This is
2025-08-14T21:17:31.9175515Z     similar to the non-blocking behavior of :meth:`wait`.
2025-08-14T21:17:31.9175667Z     
2025-08-14T21:17:31.9176081Z     Similarly, if the callback returns a value that contains tensors that
2025-08-14T21:17:31.9176442Z     reside on a GPU, it can do so even if the kernels that are producing
2025-08-14T21:17:31.9176861Z     these tensors are still running on the device, as long as the callback
2025-08-14T21:17:31.9177261Z     didn't change streams during its execution. If one wants to change
2025-08-14T21:17:31.9177665Z     streams, one must be careful to re-synchronize them with the original
2025-08-14T21:17:31.9178090Z     streams, that is, those that were current when the callback was invoked.
2025-08-14T21:17:31.9178243Z     
2025-08-14T21:17:31.9178399Z     Args:
2025-08-14T21:17:31.9178802Z         callback(``Callable``): a ``Callable`` that takes this ``Future`` as
2025-08-14T21:17:31.9179110Z                                 the only argument.
2025-08-14T21:17:31.9179264Z     
2025-08-14T21:17:31.9179439Z     Returns:
2025-08-14T21:17:31.9179748Z         A new ``Future`` object that holds the return value of the
2025-08-14T21:17:31.9180075Z         ``callback`` and will be marked as completed when the given
2025-08-14T21:17:31.9180267Z         ``callback`` finishes.
2025-08-14T21:17:31.9180417Z     
2025-08-14T21:17:31.9180744Z     .. note:: Note that if the callback function throws, either
2025-08-14T21:17:31.9181145Z         through the original future being completed with an exception and
2025-08-14T21:17:31.9181499Z         calling ``fut.wait()``, or through other code in the callback, the
2025-08-14T21:17:31.9181895Z         future returned by ``then`` will be marked appropriately with the
2025-08-14T21:17:31.9182264Z         encountered error. However, if this callback later completes
2025-08-14T21:17:31.9182673Z         additional futures, those futures are not marked as completed with
2025-08-14T21:17:31.9183069Z         an error and the user is responsible for handling completion/waiting
2025-08-14T21:17:31.9183277Z         on those futures independently.
2025-08-14T21:17:31.9183439Z     
2025-08-14T21:17:31.9183606Z     Example::
2025-08-14T21:17:31.9183755Z     
2025-08-14T21:17:31.9184035Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-08-14T21:17:31.9184214Z         >>> def callback(fut):
2025-08-14T21:17:31.9184499Z         ...     print(f"RPC return value is {fut.wait()}.")
2025-08-14T21:17:31.9184753Z         >>> fut = torch.futures.Future()
2025-08-14T21:17:31.9185063Z         >>> # The inserted callback will print the return value when
2025-08-14T21:17:31.9185282Z         >>> # receiving the response from "worker1"
2025-08-14T21:17:31.9185489Z         >>> cb_fut = fut.then(callback)
2025-08-14T21:17:31.9185678Z         >>> chain_cb_fut = cb_fut.then(
2025-08-14T21:17:31.9185946Z         ...     lambda x : print(f"Chained cb done. {x.wait()}")
2025-08-14T21:17:31.9186112Z         ... )
2025-08-14T21:17:31.9186294Z         >>> fut.set_result(5)
2025-08-14T21:17:31.9186493Z         RPC return value is 5.
2025-08-14T21:17:31.9186677Z         Chained cb done. None
2025-08-14T21:17:31.9186832Z     
2025-08-14T21:17:31.9187322Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9187488Z     
2025-08-14T21:17:31.9187667Z       warnings.warn(msg)
2025-08-14T21:17:31.9187819Z     
2025-08-14T21:17:31.9188177Z --- Parse Warning: 19 / 146 ---
2025-08-14T21:17:31.9189964Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211.
2025-08-14T21:17:31.9190477Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9190631Z     
2025-08-14T21:17:31.9191016Z     Set the result for this ``Future``, which will mark this ``Future`` as
2025-08-14T21:17:31.9191525Z     completed and trigger all attached callbacks. Note that a ``Future``
2025-08-14T21:17:31.9191739Z     cannot be marked completed twice.
2025-08-14T21:17:31.9191892Z     
2025-08-14T21:17:31.9192324Z     If the result contains tensors that reside on GPUs, this method can be
2025-08-14T21:17:31.9192710Z     called even if the asynchronous kernels that are populating those
2025-08-14T21:17:31.9193148Z     tensors haven't yet completed running on the device, provided that the
2025-08-14T21:17:31.9193581Z     streams on which those kernels were enqueued are set as the current ones
2025-08-14T21:17:31.9193980Z     when this method is called. Put simply, it's safe to call this method
2025-08-14T21:17:31.9194398Z     immediately after launching those kernels, without any additional
2025-08-14T21:17:31.9194829Z     synchronization, as long as one doesn't change streams in between. This
2025-08-14T21:17:31.9195241Z     method will record events on all the relevant current streams and will
2025-08-14T21:17:31.9195713Z     use them to ensure proper scheduling for all the consumers of this
2025-08-14T21:17:31.9195876Z     ``Future``.
2025-08-14T21:17:31.9196040Z     
2025-08-14T21:17:31.9196196Z     Args:
2025-08-14T21:17:31.9196499Z         result (object): the result object of this ``Future``.
2025-08-14T21:17:31.9196660Z     
2025-08-14T21:17:31.9196830Z     Example::
2025-08-14T21:17:31.9196981Z     
2025-08-14T21:17:31.9197259Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-08-14T21:17:31.9197441Z         >>> import threading
2025-08-14T21:17:31.9197607Z         >>> import time
2025-08-14T21:17:31.9197830Z         >>> def slow_set_future(fut, value):
2025-08-14T21:17:31.9198009Z         ...     time.sleep(0.5)
2025-08-14T21:17:31.9198199Z         ...     fut.set_result(value)
2025-08-14T21:17:31.9198418Z         >>> fut = torch.futures.Future()
2025-08-14T21:17:31.9198604Z         >>> t = threading.Thread(
2025-08-14T21:17:31.9198801Z         ...     target=slow_set_future,
2025-08-14T21:17:31.9199004Z         ...     args=(fut, torch.ones(2) * 3)
2025-08-14T21:17:31.9199159Z         ... )
2025-08-14T21:17:31.9199332Z         >>> t.start()
2025-08-14T21:17:31.9199510Z         >>> print(fut.wait())
2025-08-14T21:17:31.9199681Z         tensor([3., 3.])
2025-08-14T21:17:31.9199855Z         >>> t.join()
2025-08-14T21:17:31.9200006Z     
2025-08-14T21:17:31.9200490Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9200722Z     
2025-08-14T21:17:31.9200902Z       warnings.warn(msg)
2025-08-14T21:17:31.9201052Z     
2025-08-14T21:17:31.9201402Z --- Parse Warning: 20 / 146 ---
2025-08-14T21:17:31.9203130Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145.
2025-08-14T21:17:31.9203651Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9204073Z     Compiles compute shader from source and allows one to invoke kernels
2025-08-14T21:17:31.9204344Z         defined there from the comfort of Python runtime
2025-08-14T21:17:31.9204524Z         Example::
2025-08-14T21:17:31.9204674Z     
2025-08-14T21:17:31.9204920Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS)
2025-08-14T21:17:31.9205146Z             >>> lib = torch.mps.compile_shader(
2025-08-14T21:17:31.9205892Z             ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }"
2025-08-14T21:17:31.9206061Z             ...  )
2025-08-14T21:17:31.9206266Z             >>> x = torch.zeros(16, device="mps")
2025-08-14T21:17:31.9206444Z             >>> lib.full(x, 3.14)
2025-08-14T21:17:31.9206608Z         
2025-08-14T21:17:31.9207090Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9207240Z     
2025-08-14T21:17:31.9207433Z       warnings.warn(msg)
2025-08-14T21:17:31.9207584Z     
2025-08-14T21:17:31.9207906Z --- Parse Warning: 21 / 146 ---
2025-08-14T21:17:31.9209785Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202.
2025-08-14T21:17:31.9210296Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9210616Z     Return the sum of each row of the given sparse tensor.
2025-08-14T21:17:31.9210768Z     
2025-08-14T21:17:31.9211193Z         Returns the sum of each row of the sparse tensor :attr:`input` in the given
2025-08-14T21:17:31.9211568Z         dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions,
2025-08-14T21:17:31.9211963Z         reduce over all of them. When sum over all ``sparse_dim``, this method
2025-08-14T21:17:31.9212251Z         returns a dense tensor instead of a sparse tensor.
2025-08-14T21:17:31.9212530Z     
2025-08-14T21:17:31.9213022Z         All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output
2025-08-14T21:17:31.9213401Z         tensor having :attr:`dim` fewer dimensions than :attr:`input`.
2025-08-14T21:17:31.9213551Z     
2025-08-14T21:17:31.9213969Z         During backward, only gradients at ``nnz`` locations of :attr:`input`
2025-08-14T21:17:31.9214440Z         will propagate back. Note that the gradients of :attr:`input` is coalesced.
2025-08-14T21:17:31.9214591Z     
2025-08-14T21:17:31.9214748Z         Args:
2025-08-14T21:17:31.9214986Z             input (Tensor): the input sparse tensor
2025-08-14T21:17:31.9215500Z             dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce
2025-08-14T21:17:31.9215689Z                 over all dims.
2025-08-14T21:17:31.9216172Z             dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor.
2025-08-14T21:17:31.9216387Z                 Default: dtype of :attr:`input`.
2025-08-14T21:17:31.9216550Z     
2025-08-14T21:17:31.9216718Z         Example::
2025-08-14T21:17:31.9216868Z     
2025-08-14T21:17:31.9217034Z             >>> nnz = 3
2025-08-14T21:17:31.9217208Z             >>> dims = [5, 5, 2, 3]
2025-08-14T21:17:31.9217491Z             >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)),
2025-08-14T21:17:31.9217839Z                                torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz)
2025-08-14T21:17:31.9218183Z             >>> V = torch.randn(nnz, dims[2], dims[3])
2025-08-14T21:17:31.9218390Z             >>> size = torch.Size(dims)
2025-08-14T21:17:31.9218642Z             >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:31.9218872Z             >>> S = torch.sparse_coo_tensor(I, V, size)
2025-08-14T21:17:31.9219046Z             >>> S
2025-08-14T21:17:31.9219253Z             tensor(indices=tensor([[2, 0, 3],
2025-08-14T21:17:31.9219428Z                                    [2, 4, 1]]),
2025-08-14T21:17:31.9219677Z                    values=tensor([[[-0.6438, -1.6467,  1.4004],
2025-08-14T21:17:31.9219873Z                                    [ 0.3411,  0.0918, -0.2312]],
2025-08-14T21:17:31.9220024Z     
2025-08-14T21:17:31.9220233Z                                   [[ 0.5348,  0.0634, -2.0494],
2025-08-14T21:17:31.9220427Z                                    [-0.7125, -1.0646,  2.1844]],
2025-08-14T21:17:31.9220596Z     
2025-08-14T21:17:31.9220788Z                                   [[ 0.1276,  0.1874, -0.6334],
2025-08-14T21:17:31.9220985Z                                    [-1.9682, -0.5340,  0.7483]]]),
2025-08-14T21:17:31.9221252Z                    size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo)
2025-08-14T21:17:31.9221403Z     
2025-08-14T21:17:31.9221758Z             # when sum over only part of sparse_dims, return a sparse tensor
2025-08-14T21:17:31.9221970Z             >>> torch.sparse.sum(S, [1, 3])
2025-08-14T21:17:31.9222178Z             tensor(indices=tensor([[0, 2, 3]]),
2025-08-14T21:17:31.9222384Z                    values=tensor([[-1.4512,  0.4073],
2025-08-14T21:17:31.9222578Z                                   [-0.8901,  0.2017],
2025-08-14T21:17:31.9222761Z                                   [-0.3183, -1.7539]]),
2025-08-14T21:17:31.9223017Z                    size=(5, 2), nnz=3, layout=torch.sparse_coo)
2025-08-14T21:17:31.9223172Z     
2025-08-14T21:17:31.9223454Z             # when sum over all sparse dim, return a dense tensor
2025-08-14T21:17:31.9223666Z             # with summed dims squeezed
2025-08-14T21:17:31.9223870Z             >>> torch.sparse.sum(S, [0, 1, 3])
2025-08-14T21:17:31.9224051Z             tensor([-2.6596, -1.1450])
2025-08-14T21:17:31.9224215Z         
2025-08-14T21:17:31.9224700Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9224853Z     
2025-08-14T21:17:31.9225040Z       warnings.warn(msg)
2025-08-14T21:17:31.9225191Z     
2025-08-14T21:17:31.9225561Z --- Parse Warning: 22 / 146 ---
2025-08-14T21:17:31.9227424Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=550.
2025-08-14T21:17:31.9227930Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9228297Z     Decorate function, to extend gradcheck for sparse tensors.
2025-08-14T21:17:31.9228453Z     
2025-08-14T21:17:31.9228853Z         Decorator for torch.autograd.gradcheck or its functools.partial
2025-08-14T21:17:31.9229281Z         variants that extends the gradcheck function with support to input
2025-08-14T21:17:31.9229601Z         functions that operate on or/and return sparse tensors.
2025-08-14T21:17:31.9229765Z     
2025-08-14T21:17:31.9230160Z         The specified gradcheck function itself is guaranteed to operate
2025-08-14T21:17:31.9230351Z         on strided tensors only.
2025-08-14T21:17:31.9230513Z     
2025-08-14T21:17:31.9230682Z         For example:
2025-08-14T21:17:31.9230832Z     
2025-08-14T21:17:31.9231287Z         >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck)
2025-08-14T21:17:31.9231502Z         >>> x = (
2025-08-14T21:17:31.9231783Z         ...     torch.tensor([[0, 1], [2, 3]], dtype=torch.float64)
2025-08-14T21:17:31.9231974Z         ...     .to_sparse_coo()
2025-08-14T21:17:31.9232203Z         ...     .requires_grad_(True)
2025-08-14T21:17:31.9232407Z         ... )
2025-08-14T21:17:31.9232641Z         >>> gradcheck(lambda x: x.to_sparse_csr(), x)
2025-08-14T21:17:31.9232794Z         True
2025-08-14T21:17:31.9232961Z         
2025-08-14T21:17:31.9233439Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9233758Z     
2025-08-14T21:17:31.9233953Z       warnings.warn(msg)
2025-08-14T21:17:31.9234101Z     
2025-08-14T21:17:31.9234443Z --- Parse Warning: 23 / 146 ---
2025-08-14T21:17:31.9236119Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39.
2025-08-14T21:17:31.9236616Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9236778Z     
2025-08-14T21:17:31.9237189Z     vmap is the vectorizing map; ``vmap(func)`` returns a new function that
2025-08-14T21:17:31.9237565Z     maps ``func`` over some dimension of the inputs. Semantically, vmap
2025-08-14T21:17:31.9237992Z     pushes the map into PyTorch operations called by ``func``, effectively
2025-08-14T21:17:31.9238189Z     vectorizing those operations.
2025-08-14T21:17:31.9238339Z     
2025-08-14T21:17:31.9238755Z     vmap is useful for handling batch dimensions: one can write a function
2025-08-14T21:17:31.9239133Z     ``func`` that runs on examples and then lift it to a function that can
2025-08-14T21:17:31.9239539Z     take batches of examples with ``vmap(func)``. vmap can also be used to
2025-08-14T21:17:31.9239869Z     compute batched gradients when composed with autograd.
2025-08-14T21:17:31.9240018Z     
2025-08-14T21:17:31.9240196Z     .. note::
2025-08-14T21:17:31.9240529Z         :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for
2025-08-14T21:17:31.9240766Z         convenience. Use whichever one you'd like.
2025-08-14T21:17:31.9240932Z     
2025-08-14T21:17:31.9241086Z     Args:
2025-08-14T21:17:31.9241479Z         func (function): A Python function that takes one or more arguments.
2025-08-14T21:17:31.9241696Z             Must return one or more Tensors.
2025-08-14T21:17:31.9242067Z         in_dims (int or nested structure): Specifies which dimension of the
2025-08-14T21:17:31.9242386Z             inputs should be mapped over. ``in_dims`` should have a
2025-08-14T21:17:31.9242757Z             structure like the inputs. If the ``in_dim`` for a particular
2025-08-14T21:17:31.9243180Z             input is None, then that indicates there is no map dimension.
2025-08-14T21:17:31.9243358Z             Default: 0.
2025-08-14T21:17:31.9243719Z         out_dims (int or Tuple[int]): Specifies where the mapped dimension
2025-08-14T21:17:31.9244077Z             should appear in the outputs. If ``out_dims`` is a Tuple, then
2025-08-14T21:17:31.9244368Z             it should have one element per output. Default: 0.
2025-08-14T21:17:31.9244712Z         randomness (str): Specifies whether the randomness in this
2025-08-14T21:17:31.9245106Z             vmap should be the same or different across batches. If 'different',
2025-08-14T21:17:31.9245492Z             the randomness for each batch will be different. If 'same', the
2025-08-14T21:17:31.9245895Z             randomness will be the same across batches. If 'error', any calls to
2025-08-14T21:17:31.9246304Z             random functions will error. Default: 'error'. WARNING: this flag
2025-08-14T21:17:31.9246683Z             only applies to random PyTorch operations and does not apply to
2025-08-14T21:17:31.9246934Z             Python's random module or numpy randomness.
2025-08-14T21:17:31.9247368Z         chunk_size (None or int): If None (default), apply a single vmap over inputs.
2025-08-14T21:17:31.9247779Z             If not None, then compute the vmap :attr:`chunk_size` samples at a time.
2025-08-14T21:17:31.9248283Z             Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop.
2025-08-14T21:17:31.9248826Z             If you run into memory issues computing the vmap, please try a non-None chunk_size.
2025-08-14T21:17:31.9249013Z     
2025-08-14T21:17:31.9249185Z     Returns:
2025-08-14T21:17:31.9249537Z         Returns a new "batched" function. It takes the same inputs as
2025-08-14T21:17:31.9249873Z         ``func``, except each input has an extra dimension at the index
2025-08-14T21:17:31.9250244Z         specified by ``in_dims``. It takes returns the same outputs as
2025-08-14T21:17:31.9250589Z         ``func``, except each output has an extra dimension at the index
2025-08-14T21:17:31.9250782Z         specified by ``out_dims``.
2025-08-14T21:17:31.9250946Z     
2025-08-14T21:17:31.9251100Z     .. warning:
2025-08-14T21:17:31.9251481Z         :func:`vmap` works best with functional-style code. Please do not
2025-08-14T21:17:31.9251827Z         perform any side-effects in ``func``, with the exception of
2025-08-14T21:17:31.9252273Z         in-place PyTorch operations. Examples of side-effects include mutating
2025-08-14T21:17:31.9252718Z         Python data structures and assigning values to variables not captured
2025-08-14T21:17:31.9252880Z         in ``func``.
2025-08-14T21:17:31.9253028Z     
2025-08-14T21:17:31.9253483Z     One example of using :func:`vmap` is to compute batched dot products. PyTorch
2025-08-14T21:17:31.9253891Z     doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully
2025-08-14T21:17:31.9254324Z     rummaging through docs, use :func:`vmap` to construct a new function.
2025-08-14T21:17:31.9254473Z     
2025-08-14T21:17:31.9254671Z         >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:31.9255053Z         >>> batched_dot = torch.func.vmap(torch.dot)  # [N, D], [N, D] -> [N]
2025-08-14T21:17:31.9255280Z         >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-08-14T21:17:31.9255462Z         >>> batched_dot(x, y)
2025-08-14T21:17:31.9255626Z     
2025-08-14T21:17:31.9256050Z     :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler
2025-08-14T21:17:31.9256248Z     model authoring experience.
2025-08-14T21:17:31.9256413Z     
2025-08-14T21:17:31.9256614Z         >>> batch_size, feature_size = 3, 5
2025-08-14T21:17:31.9256931Z         >>> weights = torch.randn(feature_size, requires_grad=True)
2025-08-14T21:17:31.9257101Z         >>>
2025-08-14T21:17:31.9257286Z         >>> def model(feature_vec):
2025-08-14T21:17:31.9257534Z         >>> # Very simple linear model with activation
2025-08-14T21:17:31.9257763Z         >>>     return feature_vec.dot(weights).relu()
2025-08-14T21:17:31.9257920Z         >>>
2025-08-14T21:17:31.9258273Z         >>> examples = torch.randn(batch_size, feature_size)
2025-08-14T21:17:31.9258491Z         >>> result = torch.vmap(model)(examples)
2025-08-14T21:17:31.9258640Z     
2025-08-14T21:17:31.9259125Z     :func:`vmap` can also help vectorize computations that were previously difficult
2025-08-14T21:17:31.9259566Z     or impossible to batch. One example is higher-order gradient computation.
2025-08-14T21:17:31.9259998Z     The PyTorch autograd engine computes vjps (vector-Jacobian products).
2025-08-14T21:17:31.9260445Z     Computing a full Jacobian matrix for some function f: R^N -> R^N usually
2025-08-14T21:17:31.9260917Z     requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`,
2025-08-14T21:17:31.9261379Z     we can vectorize the whole computation, computing the Jacobian in a single
2025-08-14T21:17:31.9261566Z     call to ``autograd.grad``.
2025-08-14T21:17:31.9261720Z     
2025-08-14T21:17:31.9261892Z         >>> # Setup
2025-08-14T21:17:31.9262051Z         >>> N = 5
2025-08-14T21:17:31.9262228Z         >>> f = lambda x: x**2
2025-08-14T21:17:31.9262455Z         >>> x = torch.randn(N, requires_grad=True)
2025-08-14T21:17:31.9262612Z         >>> y = f(x)
2025-08-14T21:17:31.9262784Z         >>> I_N = torch.eye(N)
2025-08-14T21:17:31.9262948Z         >>>
2025-08-14T21:17:31.9263131Z         >>> # Sequential approach
2025-08-14T21:17:31.9263540Z         >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0]
2025-08-14T21:17:31.9263801Z         >>>                  for v in I_N.unbind()]
2025-08-14T21:17:31.9264020Z         >>> jacobian = torch.stack(jacobian_rows)
2025-08-14T21:17:31.9264185Z         >>>
2025-08-14T21:17:31.9264399Z         >>> # vectorized gradient computation
2025-08-14T21:17:31.9264569Z         >>> def get_vjp(v):
2025-08-14T21:17:31.9264800Z         >>>     return torch.autograd.grad(y, x, v)
2025-08-14T21:17:31.9265010Z         >>> jacobian = torch.vmap(get_vjp)(I_N)
2025-08-14T21:17:31.9265158Z     
2025-08-14T21:17:31.9265673Z     :func:`vmap` can also be nested, producing an output with multiple batched dimensions
2025-08-14T21:17:31.9265826Z     
2025-08-14T21:17:31.9266030Z         >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:31.9266223Z         >>> batched_dot = torch.vmap(
2025-08-14T21:17:31.9266411Z         ...     torch.vmap(torch.dot)
2025-08-14T21:17:31.9266627Z         ... )  # [N1, N0, D], [N1, N0, D] -> [N1, N0]
2025-08-14T21:17:31.9266875Z         >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5)
2025-08-14T21:17:31.9267104Z         >>> batched_dot(x, y)  # tensor of size [2, 3]
2025-08-14T21:17:31.9267269Z     
2025-08-14T21:17:31.9267730Z     If the inputs are not batched along the first dimension, ``in_dims`` specifies
2025-08-14T21:17:31.9268014Z     the dimension that each inputs are batched along as
2025-08-14T21:17:31.9268174Z     
2025-08-14T21:17:31.9268359Z         >>> torch.dot  # [N], [N] -> []
2025-08-14T21:17:31.9268787Z         >>> batched_dot = torch.vmap(torch.dot, in_dims=1)  # [N, D], [N, D] -> [D]
2025-08-14T21:17:31.9269013Z         >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-08-14T21:17:31.9269182Z         >>> batched_dot(
2025-08-14T21:17:31.9269346Z         ...     x, y
2025-08-14T21:17:31.9269698Z         ... )  # output is [5] instead of [2] if batched along the 0th dimension
2025-08-14T21:17:31.9269849Z     
2025-08-14T21:17:31.9270357Z     If there are multiple inputs each of which is batched along different dimensions,
2025-08-14T21:17:31.9270728Z     ``in_dims`` must be a tuple with the batch dimension for each input as
2025-08-14T21:17:31.9270879Z     
2025-08-14T21:17:31.9271081Z         >>> torch.dot  # [D], [D] -> []
2025-08-14T21:17:31.9271606Z         >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None))  # [N, D], [D] -> [N]
2025-08-14T21:17:31.9271839Z         >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-08-14T21:17:31.9272006Z         >>> batched_dot(
2025-08-14T21:17:31.9272163Z         ...     x, y
2025-08-14T21:17:31.9272611Z         ... )  # second arg doesn't have a batch dim because in_dim[1] was None
2025-08-14T21:17:31.9272767Z     
2025-08-14T21:17:31.9273216Z     If the input is a Python struct, ``in_dims`` must be a tuple containing a struct
2025-08-14T21:17:31.9273429Z     matching the shape of the input:
2025-08-14T21:17:31.9273580Z     
2025-08-14T21:17:31.9273830Z         >>> f = lambda dict: torch.dot(dict["x"], dict["y"])
2025-08-14T21:17:31.9274067Z         >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-08-14T21:17:31.9274248Z         >>> input = {"x": x, "y": y}
2025-08-14T21:17:31.9274589Z         >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},))
2025-08-14T21:17:31.9274770Z         >>> batched_dot(input)
2025-08-14T21:17:31.9274918Z     
2025-08-14T21:17:31.9275457Z     By default, the output is batched along the first dimension. However, it can be batched
2025-08-14T21:17:31.9275679Z     along any dimension by using ``out_dims``
2025-08-14T21:17:31.9275829Z     
2025-08-14T21:17:31.9276025Z         >>> f = lambda x: x**2
2025-08-14T21:17:31.9276206Z         >>> x = torch.randn(2, 5)
2025-08-14T21:17:31.9276432Z         >>> batched_pow = torch.vmap(f, out_dims=1)
2025-08-14T21:17:31.9276627Z         >>> batched_pow(x)  # [5, 2]
2025-08-14T21:17:31.9276779Z     
2025-08-14T21:17:31.9277353Z     For any function that uses kwargs, the returned function will not batch the kwargs but will
2025-08-14T21:17:31.9277519Z     accept kwargs
2025-08-14T21:17:31.9277722Z     
2025-08-14T21:17:31.9277949Z         >>> x = torch.randn([2, 5])
2025-08-14T21:17:31.9278130Z         >>> def fn(x, scale=4.):
2025-08-14T21:17:31.9278304Z         >>>   return x * scale
2025-08-14T21:17:31.9278475Z         >>>
2025-08-14T21:17:31.9278676Z         >>> batched_pow = torch.vmap(fn)
2025-08-14T21:17:31.9278928Z         >>> assert torch.allclose(batched_pow(x), x * 4)
2025-08-14T21:17:31.9279364Z         >>> batched_pow(x, scale=x)  # scale is not batched, output has shape [2, 2, 5]
2025-08-14T21:17:31.9279517Z     
2025-08-14T21:17:31.9279683Z     .. note::
2025-08-14T21:17:31.9280116Z         vmap does not provide general autobatching or handle variable-length
2025-08-14T21:17:31.9280307Z         sequences out of the box.
2025-08-14T21:17:31.9280473Z     
2025-08-14T21:17:31.9280955Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9281101Z     
2025-08-14T21:17:31.9281294Z       warnings.warn(msg)
2025-08-14T21:17:31.9281449Z     
2025-08-14T21:17:31.9281815Z --- Parse Warning: 24 / 146 ---
2025-08-14T21:17:31.9283496Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306.
2025-08-14T21:17:31.9283931Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9284185Z     ``grad`` operator helps computing gradients of ``func`` with respect to the
2025-08-14T21:17:31.9284387Z         input(s) specified by ``argnums``. This operator can be nested to
2025-08-14T21:17:31.9284499Z         compute higher-order gradients.
2025-08-14T21:17:31.9284592Z     
2025-08-14T21:17:31.9284673Z         Args:
2025-08-14T21:17:31.9284886Z             func (Callable): A Python function that takes one or more arguments.
2025-08-14T21:17:31.9285160Z                 Must return a single-element Tensor. If specified ``has_aux`` equals ``True``,
2025-08-14T21:17:31.9285431Z                 function can return a tuple of single-element Tensor and other auxiliary objects:
2025-08-14T21:17:31.9285528Z                 ``(output, aux)``.
2025-08-14T21:17:31.9285812Z             argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to.
2025-08-14T21:17:31.9286013Z                 ``argnums`` can be single integer or tuple of integers. Default: 0.
2025-08-14T21:17:31.9286241Z             has_aux (bool): Flag indicating that ``func`` returns a tensor and other
2025-08-14T21:17:31.9286467Z                 auxiliary objects: ``(output, aux)``. Default: False.
2025-08-14T21:17:31.9286548Z     
2025-08-14T21:17:31.9286644Z         Returns:
2025-08-14T21:17:31.9286922Z             Function to compute gradients with respect to its inputs. By default, the output of
2025-08-14T21:17:31.9287152Z             the function is the gradient tensor(s) with respect to the first argument.
2025-08-14T21:17:31.9287435Z             If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects
2025-08-14T21:17:31.9287685Z             is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with
2025-08-14T21:17:31.9287841Z             respect to each ``argnums`` value is returned.
2025-08-14T21:17:31.9287921Z     
2025-08-14T21:17:31.9288023Z         Example of using ``grad``:
2025-08-14T21:17:31.9288105Z     
2025-08-14T21:17:31.9288221Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9288331Z             >>> from torch.func import grad
2025-08-14T21:17:31.9288445Z             >>> x = torch.randn([])
2025-08-14T21:17:31.9288573Z             >>> cos_x = grad(lambda x: torch.sin(x))(x)
2025-08-14T21:17:31.9288698Z             >>> assert torch.allclose(cos_x, x.cos())
2025-08-14T21:17:31.9288792Z             >>>
2025-08-14T21:17:31.9288897Z             >>> # Second-order gradients
2025-08-14T21:17:31.9289043Z             >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x)
2025-08-14T21:17:31.9289215Z             >>> assert torch.allclose(neg_sin_x, -x.sin())
2025-08-14T21:17:31.9289320Z     
2025-08-14T21:17:31.9289565Z         When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients:
2025-08-14T21:17:31.9289657Z     
2025-08-14T21:17:31.9289753Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9289883Z             >>> from torch.func import grad, vmap
2025-08-14T21:17:31.9289997Z             >>> batch_size, feature_size = 3, 5
2025-08-14T21:17:31.9290079Z             >>>
2025-08-14T21:17:31.9290211Z             >>> def model(weights, feature_vec):
2025-08-14T21:17:31.9290348Z             >>> # Very simple linear model with activation
2025-08-14T21:17:31.9290476Z             >>>     assert feature_vec.dim() == 1
2025-08-14T21:17:31.9290601Z             >>>     return feature_vec.dot(weights).relu()
2025-08-14T21:17:31.9290691Z             >>>
2025-08-14T21:17:31.9290828Z             >>> def compute_loss(weights, example, target):
2025-08-14T21:17:31.9290952Z             >>>     y = model(weights, example)
2025-08-14T21:17:31.9291089Z             >>>     return ((y - target) ** 2).mean()  # MSELoss
2025-08-14T21:17:31.9291171Z             >>>
2025-08-14T21:17:31.9291356Z             >>> weights = torch.randn(feature_size, requires_grad=True)
2025-08-14T21:17:31.9291505Z             >>> examples = torch.randn(batch_size, feature_size)
2025-08-14T21:17:31.9291620Z             >>> targets = torch.randn(batch_size)
2025-08-14T21:17:31.9291755Z             >>> inputs = (weights, examples, targets)
2025-08-14T21:17:31.9291990Z             >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))(
2025-08-14T21:17:31.9292094Z             ...     *inputs
2025-08-14T21:17:31.9292177Z             ... )
2025-08-14T21:17:31.9292258Z     
2025-08-14T21:17:31.9292445Z         Example of using ``grad`` with ``has_aux`` and ``argnums``:
2025-08-14T21:17:31.9292523Z     
2025-08-14T21:17:31.9292620Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9292743Z             >>> from torch.func import grad
2025-08-14T21:17:31.9292855Z             >>> def my_loss_func(y, y_pred):
2025-08-14T21:17:31.9292984Z             >>>    loss_per_sample = (0.5 * y_pred - y) ** 2
2025-08-14T21:17:31.9293111Z             >>>    loss = loss_per_sample.mean()
2025-08-14T21:17:31.9293238Z             >>>    return loss, (y_pred, loss_per_sample)
2025-08-14T21:17:31.9293320Z             >>>
2025-08-14T21:17:31.9293475Z             >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True)
2025-08-14T21:17:31.9293579Z             >>> y_true = torch.rand(4)
2025-08-14T21:17:31.9293777Z             >>> y_preds = torch.rand(4, requires_grad=True)
2025-08-14T21:17:31.9293885Z             >>> out = fn(y_true, y_preds)
2025-08-14T21:17:31.9294127Z             >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample))
2025-08-14T21:17:31.9294223Z     
2025-08-14T21:17:31.9294312Z         .. note::
2025-08-14T21:17:31.9294479Z             Using PyTorch ``torch.no_grad`` together with ``grad``.
2025-08-14T21:17:31.9294578Z     
2025-08-14T21:17:31.9294722Z             Case 1: Using ``torch.no_grad`` inside a function:
2025-08-14T21:17:31.9294803Z     
2025-08-14T21:17:31.9294919Z                 >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9295009Z                 >>> def f(x):
2025-08-14T21:17:31.9295129Z                 >>>     with torch.no_grad():
2025-08-14T21:17:31.9295218Z                 >>>         c = x ** 2
2025-08-14T21:17:31.9295314Z                 >>>     return x - c
2025-08-14T21:17:31.9295402Z     
2025-08-14T21:17:31.9295602Z             In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``.
2025-08-14T21:17:31.9295679Z     
2025-08-14T21:17:31.9295871Z             Case 2: Using ``grad`` inside ``torch.no_grad`` context manager:
2025-08-14T21:17:31.9295949Z     
2025-08-14T21:17:31.9296054Z                 >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9296164Z                 >>> with torch.no_grad():
2025-08-14T21:17:31.9296280Z                 >>>     grad(f)(x)
2025-08-14T21:17:31.9296380Z     
2025-08-14T21:17:31.9296610Z             In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the
2025-08-14T21:17:31.9296827Z             outer one. This is because ``grad`` is a "function transform": its result
2025-08-14T21:17:31.9297059Z             should not depend on the result of a context manager outside of ``f``.
2025-08-14T21:17:31.9297134Z     
2025-08-14T21:17:31.9297215Z         
2025-08-14T21:17:31.9297476Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9297554Z     
2025-08-14T21:17:31.9297649Z       warnings.warn(msg)
2025-08-14T21:17:31.9297738Z     
2025-08-14T21:17:31.9297945Z --- Parse Warning: 25 / 146 ---
2025-08-14T21:17:31.9298921Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=397.
2025-08-14T21:17:31.9299170Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.9299346Z     Register a FakeTensor implementation for this custom op.
2025-08-14T21:17:31.9299439Z     
2025-08-14T21:17:31.9299681Z             This is necessary to get the operator to work efficiently with torch.compile.
2025-08-14T21:17:31.9299758Z     
2025-08-14T21:17:31.9299991Z             The Fake impl (sometimes also known as a meta kernel or abstract impl)
2025-08-14T21:17:31.9300217Z             specifies the behavior of this operator on Tensors that carry no data.
2025-08-14T21:17:31.9300376Z             Given some input Tensors with certain properties
2025-08-14T21:17:31.9300634Z             (sizes/strides/storage_offset/device), it specifies what the properties of
2025-08-14T21:17:31.9300734Z             the output Tensors are.
2025-08-14T21:17:31.9300827Z     
2025-08-14T21:17:31.9301028Z             Please see :func:`torch.library.register_fake` for more details.
2025-08-14T21:17:31.9301107Z     
2025-08-14T21:17:31.9301198Z             Args:
2025-08-14T21:17:31.9301369Z                 fn (Callable): The function to register as the FakeTensor
2025-08-14T21:17:31.9301468Z                     implementation.
2025-08-14T21:17:31.9301558Z     
2025-08-14T21:17:31.9301642Z             Examples:
2025-08-14T21:17:31.9301734Z                 >>> import torch
2025-08-14T21:17:31.9301847Z                 >>> import numpy as np
2025-08-14T21:17:31.9301954Z                 >>> from torch import Tensor
2025-08-14T21:17:31.9302099Z                 >>>
2025-08-14T21:17:31.9302287Z                 >>> # Example 1: an operator without data-dependent output shape
2025-08-14T21:17:31.9302471Z                 >>> @torch.library.custom_op("mylib::linear", mutates_args=())
2025-08-14T21:17:31.9302673Z                 >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-08-14T21:17:31.9302791Z                 >>>     return (x @ weight.t()) + bias
2025-08-14T21:17:31.9302871Z                 >>>
2025-08-14T21:17:31.9302989Z                 >>> @linear.register_fake
2025-08-14T21:17:31.9303092Z                 >>> def _(x, weight, bias):
2025-08-14T21:17:31.9303204Z                 >>>     assert x.dim() == 2
2025-08-14T21:17:31.9303316Z                 >>>     assert weight.dim() == 2
2025-08-14T21:17:31.9303421Z                 >>>     assert bias.dim() == 1
2025-08-14T21:17:31.9303558Z                 >>>     assert x.shape[1] == weight.shape[1]
2025-08-14T21:17:31.9303693Z                 >>>     assert weight.shape[0] == bias.shape[0]
2025-08-14T21:17:31.9303812Z                 >>>     assert x.device == weight.device
2025-08-14T21:17:31.9303970Z                 >>>     return x.new_empty(x.size(0), weight.size(0))
2025-08-14T21:17:31.9304055Z                 >>>
2025-08-14T21:17:31.9304156Z                 >>> x = torch.randn(2, 2)
2025-08-14T21:17:31.9304277Z                 >>> weight = torch.randn(2, 2)
2025-08-14T21:17:31.9304405Z                 >>> bias = torch.randn(2)
2025-08-14T21:17:31.9304573Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:31.9304763Z                 >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias)
2025-08-14T21:17:31.9304892Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:31.9305146Z                 >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias))
2025-08-14T21:17:31.9305231Z                 >>>
2025-08-14T21:17:31.9305406Z                 >>> # Example 2: an operator with data-dependent output shape
2025-08-14T21:17:31.9305613Z                 >>> @torch.library.custom_op("mylib::nonzero", mutates_args=())
2025-08-14T21:17:31.9305732Z                 >>> def nonzero(x: Tensor) -> Tensor:
2025-08-14T21:17:31.9305847Z                 >>>     x_np = x.cpu().numpy()
2025-08-14T21:17:31.9305976Z                 >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-08-14T21:17:31.9306112Z                 >>>     return torch.tensor(res, device=x.device)
2025-08-14T21:17:31.9306205Z                 >>>
2025-08-14T21:17:31.9306311Z                 >>> @nonzero.register_fake
2025-08-14T21:17:31.9306396Z                 >>> def _(x):
2025-08-14T21:17:31.9306558Z                 >>> # Number of nonzero-elements is data-dependent.
2025-08-14T21:17:31.9306720Z                 >>> # Since we cannot peek at the data in an abstract impl,
2025-08-14T21:17:31.9306873Z                 >>> # we use the ctx object to construct a new symint that
2025-08-14T21:17:31.9307013Z                 >>> # represents the data-dependent size.
2025-08-14T21:17:31.9307132Z                 >>>     ctx = torch.library.get_ctx()
2025-08-14T21:17:31.9307260Z                 >>>     nnz = ctx.new_dynamic_size()
2025-08-14T21:17:31.9307366Z                 >>>     shape = [nnz, x.dim()]
2025-08-14T21:17:31.9307512Z                 >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-08-14T21:17:31.9307618Z                 >>>     return result
2025-08-14T21:17:31.9307700Z                 >>>
2025-08-14T21:17:31.9307817Z                 >>> x = torch.tensor([0, 1, 2, 0, 0, 1])
2025-08-14T21:17:31.9307961Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:31.9308105Z                 >>> out = torch.compile(nonzero, fullgraph=True)(x)
2025-08-14T21:17:31.9308246Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-08-14T21:17:31.9308375Z                 >>> assert torch.allclose(out, x.nonzero())
2025-08-14T21:17:31.9308453Z     
2025-08-14T21:17:31.9308545Z             
2025-08-14T21:17:31.9309390Z     Original Error: IndentationError('expected an indented block after function definition on line 36', ('<source_block>', 37, 1, '_._ = None\n', 37, 2))
2025-08-14T21:17:31.9309472Z     
2025-08-14T21:17:31.9309566Z     _._ = None
2025-08-14T21:17:31.9309645Z     ^
2025-08-14T21:17:31.9309742Z       warnings.warn(msg)
2025-08-14T21:17:31.9309830Z     
2025-08-14T21:17:31.9310035Z --- Parse Warning: 26 / 146 ---
2025-08-14T21:17:31.9311017Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94.
2025-08-14T21:17:31.9311277Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9311353Z     
2025-08-14T21:17:31.9311664Z     Registers a fake kernel based on the given operator profiles. This fake
2025-08-14T21:17:31.9311913Z     kernel registration will override any existing fake kernel registrations.
2025-08-14T21:17:31.9311992Z     
2025-08-14T21:17:31.9312215Z     The input is a dictionary mapping operator names to a set of operator
2025-08-14T21:17:31.9312443Z     profiles, which we will use to generate fake kernels. The operator profiles
2025-08-14T21:17:31.9312652Z     are a record of the input and output tensor metadata. Based on this
2025-08-14T21:17:31.9312939Z     information we will match a given input to the recorded profile, and return
2025-08-14T21:17:31.9313193Z     an output with the same metadata as in the recorded profile. If a profile
2025-08-14T21:17:31.9313344Z     doesn't exist then an exception will be thrown.
2025-08-14T21:17:31.9313422Z     
2025-08-14T21:17:31.9313649Z     The fake kernel generation is considered unsafe because it relies on the
2025-08-14T21:17:31.9313885Z     rigid, pre-defined operator profiles that do not account for potential
2025-08-14T21:17:31.9314136Z     variations in output behavior. Specifically, the generated kernels assume a
2025-08-14T21:17:31.9314399Z     fixed relationship between input and output ranks. However, in reality, it's
2025-08-14T21:17:31.9314636Z     possible that data-dependent operations may produce outputs of different
2025-08-14T21:17:31.9314854Z     ranks even when given inputs of the same rank. The generated fake kernels
2025-08-14T21:17:31.9315078Z     are inflexible and unable to accommodate these nuances, making them
2025-08-14T21:17:31.9315181Z     potentially unsafe.
2025-08-14T21:17:31.9315258Z     
2025-08-14T21:17:31.9315358Z     Args:
2025-08-14T21:17:31.9315573Z         op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator
2025-08-14T21:17:31.9315768Z             name to a set of operator profiles from which we will generate fake
2025-08-14T21:17:31.9315864Z             kernels.
2025-08-14T21:17:31.9315940Z     
2025-08-14T21:17:31.9316038Z     Examples:
2025-08-14T21:17:31.9316118Z     
2025-08-14T21:17:31.9316287Z         >>> # Example: Registering an op-profile from draft-export
2025-08-14T21:17:31.9316390Z         >>> import torch
2025-08-14T21:17:31.9316552Z         >>> from torch.export._draft_export import draft_export
2025-08-14T21:17:31.9316633Z         >>>
2025-08-14T21:17:31.9316823Z         >>> @torch.library.custom_op("mylib::foo", mutates_args=())
2025-08-14T21:17:31.9316950Z         >>> def foo(x: Tensor, y: Tensor) -> Tensor:
2025-08-14T21:17:31.9317043Z         >>>     return x + y
2025-08-14T21:17:31.9317136Z         >>>
2025-08-14T21:17:31.9317243Z         >>> class M(torch.nn.Module):
2025-08-14T21:17:31.9317359Z         >>>     def forward(self, a, b):
2025-08-14T21:17:31.9317502Z         >>>         res = torch.ops.mylib.foo(a, b)  # no fake impl
2025-08-14T21:17:31.9317597Z         >>>         return res
2025-08-14T21:17:31.9317689Z         >>>
2025-08-14T21:17:31.9317858Z         >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4))
2025-08-14T21:17:31.9317940Z         >>>
2025-08-14T21:17:31.9318353Z         >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles):
2025-08-14T21:17:31.9318475Z         >>>     decomp = ep.run_decompositions()
2025-08-14T21:17:31.9318555Z     
2025-08-14T21:17:31.9318651Z     
2025-08-14T21:17:31.9318908Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9318988Z     
2025-08-14T21:17:31.9319100Z       warnings.warn(msg)
2025-08-14T21:17:31.9319182Z     
2025-08-14T21:17:31.9319402Z --- Parse Warning: 27 / 146 ---
2025-08-14T21:17:31.9320254Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=96.
2025-08-14T21:17:31.9320518Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9320785Z     Create a custom operator whose implementation is backed by 1+ triton kernels.
2025-08-14T21:17:31.9320871Z     
2025-08-14T21:17:31.9321078Z         This is a more structured way of using triton kernels with PyTorch.
2025-08-14T21:17:31.9321347Z         Prefer using triton kernels with no ``torch.library`` custom operator wrappers
2025-08-14T21:17:31.9321598Z         (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because
2025-08-14T21:17:31.9321709Z         that is simpler;
2025-08-14T21:17:31.9321986Z         only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you
2025-08-14T21:17:31.9322240Z         want to create an operator that behaves like PyTorch built-in operators.
2025-08-14T21:17:31.9322470Z         For example, you may use a ``torch.library`` wrapper API to define the
2025-08-14T21:17:31.9322684Z         behavior of the triton kernel when passed a tensor subclass or under
2025-08-14T21:17:31.9322790Z         a TorchDispatchMode.
2025-08-14T21:17:31.9322887Z     
2025-08-14T21:17:31.9323142Z         Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op`
2025-08-14T21:17:31.9323260Z         when the implementation
2025-08-14T21:17:31.9323477Z         consists of 1+ triton kernels. :func:`torch.library.custom_op` treats
2025-08-14T21:17:31.9323647Z         custom operators as opaque (:func:`torch.compile` and
2025-08-14T21:17:31.9323895Z         :func:`torch.export.export` will never trace into them), but ``triton_op``
2025-08-14T21:17:31.9324117Z         makes the implementation visible to these subsystems, allowing them
2025-08-14T21:17:31.9324234Z         to optimize the triton kernel(s).
2025-08-14T21:17:31.9324335Z     
2025-08-14T21:17:31.9324525Z         Note that ``fn`` must only consist of calls to PyTorch-understood
2025-08-14T21:17:31.9324764Z         operators and triton kernels. Any triton kernels called inside ``fn``
2025-08-14T21:17:31.9324961Z         must be wrapped in a call to :func:`torch.library.wrap_triton`.
2025-08-14T21:17:31.9325042Z     
2025-08-14T21:17:31.9325141Z         Args:
2025-08-14T21:17:31.9325370Z             name (str): A name for the custom op that looks like "{namespace}::{name}",
2025-08-14T21:17:31.9325583Z                 e.g. "mylib::my_linear". The name is used as the op's stable identifier
2025-08-14T21:17:31.9325760Z                 in PyTorch subsystems (e.g. torch.export, FX graphs).
2025-08-14T21:17:31.9325995Z                 To avoid name collisions, please use your project name as the namespace;
2025-08-14T21:17:31.9326217Z                 e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace.
2025-08-14T21:17:31.9326493Z             mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates.
2025-08-14T21:17:31.9326730Z                 This MUST be accurate, otherwise, the behavior is undefined. If "unknown",
2025-08-14T21:17:31.9327008Z                 it pessimistically assumes that all inputs to the operator are being mutated.
2025-08-14T21:17:31.9327251Z             schema (None | str): A schema string for the operator. If None
2025-08-14T21:17:31.9327455Z                 (recommended) we'll infer a schema for the operator from its type
2025-08-14T21:17:31.9327672Z                 annotations. We recommend letting us infer a schema unless you
2025-08-14T21:17:31.9327788Z                 have a specific reason not to.
2025-08-14T21:17:31.9327947Z                 Example: "(Tensor x, int y) -> (Tensor, Tensor)".
2025-08-14T21:17:31.9328029Z     
2025-08-14T21:17:31.9328118Z         Example::
2025-08-14T21:17:31.9328215Z     
2025-08-14T21:17:31.9328355Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:31.9328449Z             >>> import torch
2025-08-14T21:17:31.9328614Z             >>> from torch.library import triton_op, wrap_triton
2025-08-14T21:17:31.9328696Z             >>>
2025-08-14T21:17:31.9328789Z             >>> import triton
2025-08-14T21:17:31.9328920Z             >>> from triton import language as tl
2025-08-14T21:17:31.9329002Z             >>>
2025-08-14T21:17:31.9329108Z             >>> @triton.jit
2025-08-14T21:17:31.9329201Z             >>> def add_kernel(
2025-08-14T21:17:31.9329290Z             >>>     in_ptr0,
2025-08-14T21:17:31.9329391Z             >>>     in_ptr1,
2025-08-14T21:17:31.9329483Z             >>>     out_ptr,
2025-08-14T21:17:31.9329574Z             >>>     n_elements,
2025-08-14T21:17:31.9329701Z             >>>     BLOCK_SIZE: "tl.constexpr",
2025-08-14T21:17:31.9329810Z             >>> ):
2025-08-14T21:17:31.9329922Z             >>>     pid = tl.program_id(axis=0)
2025-08-14T21:17:31.9330076Z             >>>     block_start = pid * BLOCK_SIZE
2025-08-14T21:17:31.9330227Z             >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-08-14T21:17:31.9330335Z             >>>     mask = offsets < n_elements
2025-08-14T21:17:31.9330478Z             >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-08-14T21:17:31.9330611Z             >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-08-14T21:17:31.9330721Z             >>>     output = x + y
2025-08-14T21:17:31.9330869Z             >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-08-14T21:17:31.9330952Z             >>>
2025-08-14T21:17:31.9331095Z             >>> @triton_op("mylib::add", mutates_args={})
2025-08-14T21:17:31.9331279Z             >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
2025-08-14T21:17:31.9331396Z             >>>     output = torch.empty_like(x)
2025-08-14T21:17:31.9331526Z             >>>     n_elements = output.numel()
2025-08-14T21:17:31.9331609Z             >>>
2025-08-14T21:17:31.9331723Z             >>>     def grid(meta):
2025-08-14T21:17:31.9331893Z             >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-08-14T21:17:31.9331976Z             >>>
2025-08-14T21:17:31.9332166Z             >>>     # NB: we need to wrap the triton kernel in a call to wrap_triton
2025-08-14T21:17:31.9332349Z             >>>     wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16)
2025-08-14T21:17:31.9332450Z             >>>     return output
2025-08-14T21:17:31.9332543Z             >>>
2025-08-14T21:17:31.9332640Z             >>> @torch.compile
2025-08-14T21:17:31.9332731Z             >>> def f(x, y):
2025-08-14T21:17:31.9332839Z             >>>     return add(x, y)
2025-08-14T21:17:31.9332919Z             >>>
2025-08-14T21:17:31.9333049Z             >>> x = torch.randn(3, device="cuda")
2025-08-14T21:17:31.9333163Z             >>> y = torch.randn(3, device="cuda")
2025-08-14T21:17:31.9333245Z             >>>
2025-08-14T21:17:31.9333345Z             >>> z = f(x, y)
2025-08-14T21:17:31.9333461Z             >>> assert torch.allclose(z, x + y)
2025-08-14T21:17:31.9333539Z     
2025-08-14T21:17:31.9333633Z         
2025-08-14T21:17:31.9333883Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9333964Z     
2025-08-14T21:17:31.9334073Z       warnings.warn(msg)
2025-08-14T21:17:31.9334153Z     
2025-08-14T21:17:31.9334348Z --- Parse Warning: 28 / 146 ---
2025-08-14T21:17:31.9335281Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=296.
2025-08-14T21:17:31.9335547Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9335754Z     Allows capture of a triton kernel into a graph via make_fx or
2025-08-14T21:17:31.9335867Z         non-strict ``torch.export``.
2025-08-14T21:17:31.9335950Z     
2025-08-14T21:17:31.9336149Z         These technologies perform Dispatcher-based tracing (via
2025-08-14T21:17:31.9336347Z         ``__torch_dispatch__``) and cannot see calls to raw triton kernels.
2025-08-14T21:17:31.9336542Z         The ``wrap_triton`` API wraps a triton kernel into a callable that
2025-08-14T21:17:31.9336671Z         can actually be traced into a graph.
2025-08-14T21:17:31.9336750Z     
2025-08-14T21:17:31.9336975Z         Please use this API together with :func:`torch.library.triton_op`.
2025-08-14T21:17:31.9337056Z     
2025-08-14T21:17:31.9337145Z         Examples:
2025-08-14T21:17:31.9337238Z     
2025-08-14T21:17:31.9337337Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9337431Z             >>> import torch
2025-08-14T21:17:31.9337538Z             >>> import triton
2025-08-14T21:17:31.9340137Z             >>> from triton import language as tl
2025-08-14T21:17:31.9340392Z             >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-08-14T21:17:31.9340584Z             >>> from torch.library import wrap_triton
2025-08-14T21:17:31.9340669Z             >>>
2025-08-14T21:17:31.9340760Z             >>> @triton.jit
2025-08-14T21:17:31.9340868Z             >>> def add_kernel(
2025-08-14T21:17:31.9340960Z             >>>     in_ptr0,
2025-08-14T21:17:31.9341049Z             >>>     in_ptr1,
2025-08-14T21:17:31.9341151Z             >>>     out_ptr,
2025-08-14T21:17:31.9341243Z             >>>     n_elements,
2025-08-14T21:17:31.9341362Z             >>>     BLOCK_SIZE: "tl.constexpr",
2025-08-14T21:17:31.9341456Z             >>> ):
2025-08-14T21:17:31.9341567Z             >>>     pid = tl.program_id(axis=0)
2025-08-14T21:17:31.9341680Z             >>>     block_start = pid * BLOCK_SIZE
2025-08-14T21:17:31.9341842Z             >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-08-14T21:17:31.9341988Z             >>>     mask = offsets < n_elements
2025-08-14T21:17:31.9342121Z             >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-08-14T21:17:31.9342261Z             >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-08-14T21:17:31.9342359Z             >>>     output = x + y
2025-08-14T21:17:31.9342504Z             >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-08-14T21:17:31.9342596Z             >>>
2025-08-14T21:17:31.9342690Z             >>> def add(x, y):
2025-08-14T21:17:31.9342805Z             >>>     output = torch.empty_like(x)
2025-08-14T21:17:31.9342930Z             >>>     n_elements = output.numel()
2025-08-14T21:17:31.9343015Z             >>>
2025-08-14T21:17:31.9343127Z             >>>     def grid_fn(meta):
2025-08-14T21:17:31.9343299Z             >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-08-14T21:17:31.9343381Z             >>>
2025-08-14T21:17:31.9343591Z             >>>     wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16)
2025-08-14T21:17:31.9343688Z             >>>     return output
2025-08-14T21:17:31.9343772Z             >>>
2025-08-14T21:17:31.9343905Z             >>> x = torch.randn(3, device="cuda")
2025-08-14T21:17:31.9344019Z             >>> y = torch.randn(3, device="cuda")
2025-08-14T21:17:31.9344121Z             >>> gm = make_fx(add)(x, y)
2025-08-14T21:17:31.9344233Z             >>> print(gm.code)
2025-08-14T21:17:31.9344342Z             >>> # def forward(self, x_1, y_1):
2025-08-14T21:17:31.9344595Z             >>> #     empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False)
2025-08-14T21:17:31.9344865Z             >>> #     triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation(
2025-08-14T21:17:31.9344995Z             >>> #         kernel_idx = 0, constant_args_idx = 0,
2025-08-14T21:17:31.9345119Z             >>> #         grid = [(1, 1, 1)], kwargs = {
2025-08-14T21:17:31.9345271Z             >>> #             'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like,
2025-08-14T21:17:31.9345398Z             >>> #             'n_elements': 3, 'BLOCK_SIZE': 16
2025-08-14T21:17:31.9345501Z             >>> #         })
2025-08-14T21:17:31.9345604Z             >>> #     return empty_like
2025-08-14T21:17:31.9345683Z     
2025-08-14T21:17:31.9345776Z         
2025-08-14T21:17:31.9346028Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9346120Z     
2025-08-14T21:17:31.9346216Z       warnings.warn(msg)
2025-08-14T21:17:31.9346293Z     
2025-08-14T21:17:31.9346534Z --- Parse Warning: 29 / 146 ---
2025-08-14T21:17:31.9347456Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286.
2025-08-14T21:17:31.9347719Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9347814Z     
2025-08-14T21:17:31.9348104Z     Test if two objects are equal, and print an error message if test fails.
2025-08-14T21:17:31.9348250Z     
2025-08-14T21:17:31.9348397Z     The test is performed with ``actual == desired``.
2025-08-14T21:17:31.9348475Z     
2025-08-14T21:17:31.9348576Z     Parameters
2025-08-14T21:17:31.9348661Z     ----------
2025-08-14T21:17:31.9348752Z     test_string : str
2025-08-14T21:17:31.9348893Z         The message supplied to AssertionError.
2025-08-14T21:17:31.9348983Z     actual : object
2025-08-14T21:17:31.9349135Z         The object to test for equality against `desired`.
2025-08-14T21:17:31.9349239Z     desired : object
2025-08-14T21:17:31.9349342Z         The expected result.
2025-08-14T21:17:31.9349420Z     
2025-08-14T21:17:31.9349515Z     Examples
2025-08-14T21:17:31.9349596Z     --------
2025-08-14T21:17:31.9349732Z     >>> np.testing.print_assert_equal(
2025-08-14T21:17:31.9349849Z     ...     "Test XYZ of func xyz", [0, 1], [0, 1]
2025-08-14T21:17:31.9349948Z     ... )  # doctest: +SKIP
2025-08-14T21:17:31.9350075Z     >>> np.testing.print_assert_equal(
2025-08-14T21:17:31.9350191Z     ...     "Test XYZ of func xyz", [0, 1], [0, 2]
2025-08-14T21:17:31.9350300Z     ... )  # doctest: +SKIP
2025-08-14T21:17:31.9350411Z     Traceback (most recent call last):
2025-08-14T21:17:31.9350493Z     ...
2025-08-14T21:17:31.9350637Z     AssertionError: Test XYZ of func xyz failed
2025-08-14T21:17:31.9350720Z     ACTUAL:
2025-08-14T21:17:31.9350802Z     [0, 1]
2025-08-14T21:17:31.9350902Z     DESIRED:
2025-08-14T21:17:31.9350983Z     [0, 2]
2025-08-14T21:17:31.9351063Z     
2025-08-14T21:17:31.9351162Z     
2025-08-14T21:17:31.9351514Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9351598Z     
2025-08-14T21:17:31.9351709Z       warnings.warn(msg)
2025-08-14T21:17:31.9351790Z     
2025-08-14T21:17:31.9351990Z --- Parse Warning: 30 / 146 ---
2025-08-14T21:17:31.9352931Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331.
2025-08-14T21:17:31.9353198Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9353292Z     
2025-08-14T21:17:31.9353501Z     Raises an AssertionError if two items are not equal up to desired
2025-08-14T21:17:31.9353589Z     precision.
2025-08-14T21:17:31.9353684Z     
2025-08-14T21:17:31.9353863Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:31.9354082Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:31.9354288Z               instead of this function for more consistent floating point
2025-08-14T21:17:31.9354385Z               comparisons.
2025-08-14T21:17:31.9354479Z     
2025-08-14T21:17:31.9354696Z     The test verifies that the elements of `actual` and `desired` satisfy.
2025-08-14T21:17:31.9354775Z     
2025-08-14T21:17:31.9354952Z         ``abs(desired-actual) < float64(1.5 * 10**(-decimal))``
2025-08-14T21:17:31.9355034Z     
2025-08-14T21:17:31.9355262Z     That is a looser test than originally documented, but agrees with what the
2025-08-14T21:17:31.9355508Z     actual implementation in `assert_array_almost_equal` did up to rounding
2025-08-14T21:17:31.9355741Z     vagaries. An exception is raised at conflicting values. For ndarrays this
2025-08-14T21:17:31.9355861Z     delegates to assert_array_almost_equal
2025-08-14T21:17:31.9355955Z     
2025-08-14T21:17:31.9356042Z     Parameters
2025-08-14T21:17:31.9356139Z     ----------
2025-08-14T21:17:31.9356231Z     actual : array_like
2025-08-14T21:17:31.9356330Z         The object to check.
2025-08-14T21:17:31.9356433Z     desired : array_like
2025-08-14T21:17:31.9356529Z         The expected object.
2025-08-14T21:17:31.9356625Z     decimal : int, optional
2025-08-14T21:17:31.9356752Z         Desired precision, default is 7.
2025-08-14T21:17:31.9356846Z     err_msg : str, optional
2025-08-14T21:17:31.9357108Z         The error message to be printed in case of failure.
2025-08-14T21:17:31.9357246Z     verbose : bool, optional
2025-08-14T21:17:31.9357447Z         If True, the conflicting values are appended to the error message.
2025-08-14T21:17:31.9357527Z     
2025-08-14T21:17:31.9357622Z     Raises
2025-08-14T21:17:31.9357703Z     ------
2025-08-14T21:17:31.9357806Z     AssertionError
2025-08-14T21:17:31.9357999Z       If actual and desired are not equal up to specified precision.
2025-08-14T21:17:31.9358076Z     
2025-08-14T21:17:31.9358170Z     See Also
2025-08-14T21:17:31.9358254Z     --------
2025-08-14T21:17:31.9358489Z     assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:31.9358630Z                      relative and/or absolute precision.
2025-08-14T21:17:31.9358837Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:31.9358916Z     
2025-08-14T21:17:31.9359017Z     Examples
2025-08-14T21:17:31.9359102Z     --------
2025-08-14T21:17:31.9359267Z     >>> from torch._numpy.testing import assert_almost_equal
2025-08-14T21:17:31.9359411Z     >>> assert_almost_equal(2.3333333333333, 2.33333334)
2025-08-14T21:17:31.9359581Z     >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
2025-08-14T21:17:31.9359707Z     Traceback (most recent call last):
2025-08-14T21:17:31.9359789Z         ...
2025-08-14T21:17:31.9359881Z     AssertionError:
2025-08-14T21:17:31.9360016Z     Arrays are not almost equal to 10 decimals
2025-08-14T21:17:31.9360108Z      ACTUAL: 2.3333333333333
2025-08-14T21:17:31.9360199Z      DESIRED: 2.33333334
2025-08-14T21:17:31.9360291Z     
2025-08-14T21:17:31.9360386Z     >>> assert_almost_equal(
2025-08-14T21:17:31.9360586Z     ...     np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9
2025-08-14T21:17:31.9360676Z     ... )
2025-08-14T21:17:31.9360787Z     Traceback (most recent call last):
2025-08-14T21:17:31.9360868Z         ...
2025-08-14T21:17:31.9360973Z     AssertionError:
2025-08-14T21:17:31.9361098Z     Arrays are not almost equal to 9 decimals
2025-08-14T21:17:31.9361195Z     <BLANKLINE>
2025-08-14T21:17:31.9361301Z     Mismatched elements: 1 / 2 (50%)
2025-08-14T21:17:31.9361430Z     Max absolute difference: 6.666699636781459e-09
2025-08-14T21:17:31.9361568Z     Max relative difference: 2.8571569790287484e-09
2025-08-14T21:17:31.9361708Z      x: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-08-14T21:17:31.9361841Z      y: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-08-14T21:17:31.9361931Z     
2025-08-14T21:17:31.9362009Z     
2025-08-14T21:17:31.9362287Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9362381Z     
2025-08-14T21:17:31.9362479Z       warnings.warn(msg)
2025-08-14T21:17:31.9362557Z     
2025-08-14T21:17:31.9362765Z --- Parse Warning: 31 / 146 ---
2025-08-14T21:17:31.9363693Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457.
2025-08-14T21:17:31.9363972Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9364051Z     
2025-08-14T21:17:31.9364273Z     Raises an AssertionError if two items are not equal up to significant
2025-08-14T21:17:31.9364369Z     digits.
2025-08-14T21:17:31.9364451Z     
2025-08-14T21:17:31.9364628Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:31.9364824Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:31.9365015Z               instead of this function for more consistent floating point
2025-08-14T21:17:31.9365124Z               comparisons.
2025-08-14T21:17:31.9365203Z     
2025-08-14T21:17:31.9365388Z     Given two numbers, check that they are approximately equal.
2025-08-14T21:17:31.9365648Z     Approximately equal is defined as the number of significant digits
2025-08-14T21:17:31.9365758Z     that agree.
2025-08-14T21:17:31.9365861Z     
2025-08-14T21:17:31.9365962Z     Parameters
2025-08-14T21:17:31.9366046Z     ----------
2025-08-14T21:17:31.9366133Z     actual : scalar
2025-08-14T21:17:31.9366241Z         The object to check.
2025-08-14T21:17:31.9366328Z     desired : scalar
2025-08-14T21:17:31.9366423Z         The expected object.
2025-08-14T21:17:31.9366536Z     significant : int, optional
2025-08-14T21:17:31.9366647Z         Desired precision, default is 7.
2025-08-14T21:17:31.9366755Z     err_msg : str, optional
2025-08-14T21:17:31.9366911Z         The error message to be printed in case of failure.
2025-08-14T21:17:31.9367008Z     verbose : bool, optional
2025-08-14T21:17:31.9367225Z         If True, the conflicting values are appended to the error message.
2025-08-14T21:17:31.9367308Z     
2025-08-14T21:17:31.9367387Z     Raises
2025-08-14T21:17:31.9367480Z     ------
2025-08-14T21:17:31.9367570Z     AssertionError
2025-08-14T21:17:31.9367763Z       If actual and desired are not equal up to specified precision.
2025-08-14T21:17:31.9367861Z     
2025-08-14T21:17:31.9367942Z     See Also
2025-08-14T21:17:31.9368025Z     --------
2025-08-14T21:17:31.9368273Z     assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:31.9368398Z                      relative and/or absolute precision.
2025-08-14T21:17:31.9368617Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:31.9368694Z     
2025-08-14T21:17:31.9368779Z     Examples
2025-08-14T21:17:31.9368870Z     --------
2025-08-14T21:17:31.9368985Z     >>> np.testing.assert_approx_equal(
2025-08-14T21:17:31.9369089Z     ...     0.12345677777777e-20, 0.1234567e-20
2025-08-14T21:17:31.9369194Z     ... )  # doctest: +SKIP
2025-08-14T21:17:31.9369306Z     >>> np.testing.assert_approx_equal(
2025-08-14T21:17:31.9369393Z     ...     0.12345670e-20,
2025-08-14T21:17:31.9369513Z     ...     0.12345671e-20,  # doctest: +SKIP
2025-08-14T21:17:31.9369606Z     ...     significant=8,
2025-08-14T21:17:31.9369688Z     ... )
2025-08-14T21:17:31.9369813Z     >>> np.testing.assert_approx_equal(
2025-08-14T21:17:31.9369902Z     ...     0.12345670e-20,
2025-08-14T21:17:31.9370019Z     ...     0.12345672e-20,  # doctest: +SKIP
2025-08-14T21:17:31.9370111Z     ...     significant=8,
2025-08-14T21:17:31.9370188Z     ... )
2025-08-14T21:17:31.9370309Z     Traceback (most recent call last):
2025-08-14T21:17:31.9370389Z         ...
2025-08-14T21:17:31.9370478Z     AssertionError:
2025-08-14T21:17:31.9370619Z     Items are not equal to 8 significant digits:
2025-08-14T21:17:31.9370738Z      ACTUAL: 1.234567e-21
2025-08-14T21:17:31.9370832Z      DESIRED: 1.2345672e-21
2025-08-14T21:17:31.9370923Z     
2025-08-14T21:17:31.9371083Z     the evaluated condition that raises the exception is
2025-08-14T21:17:31.9371161Z     
2025-08-14T21:17:31.9371363Z     >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1)
2025-08-14T21:17:31.9371445Z     True
2025-08-14T21:17:31.9371542Z     
2025-08-14T21:17:31.9371621Z     
2025-08-14T21:17:31.9371873Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9371964Z     
2025-08-14T21:17:31.9372064Z       warnings.warn(msg)
2025-08-14T21:17:31.9372142Z     
2025-08-14T21:17:31.9372349Z --- Parse Warning: 32 / 146 ---
2025-08-14T21:17:31.9373272Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744.
2025-08-14T21:17:31.9373534Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9373627Z     
2025-08-14T21:17:31.9373833Z     Raises an AssertionError if two array_like objects are not equal.
2025-08-14T21:17:31.9373925Z     
2025-08-14T21:17:31.9374127Z     Given two array_like objects, check that the shape is equal and all
2025-08-14T21:17:31.9374416Z     elements of these objects are equal (but see the Notes for the special
2025-08-14T21:17:31.9374652Z     handling of a scalar). An exception is raised at shape mismatch or
2025-08-14T21:17:31.9374872Z     conflicting values. In contrast to the standard usage in numpy, NaNs
2025-08-14T21:17:31.9375088Z     are compared like numbers, no assertion is raised if both objects have
2025-08-14T21:17:31.9375210Z     NaNs in the same positions.
2025-08-14T21:17:31.9375289Z     
2025-08-14T21:17:31.9375524Z     The usual caution for verifying equality with floating point numbers is
2025-08-14T21:17:31.9375610Z     advised.
2025-08-14T21:17:31.9375689Z     
2025-08-14T21:17:31.9375787Z     Parameters
2025-08-14T21:17:31.9375872Z     ----------
2025-08-14T21:17:31.9375961Z     x : array_like
2025-08-14T21:17:31.9376083Z         The actual object to check.
2025-08-14T21:17:31.9376171Z     y : array_like
2025-08-14T21:17:31.9376281Z         The desired, expected object.
2025-08-14T21:17:31.9376391Z     err_msg : str, optional
2025-08-14T21:17:31.9376550Z         The error message to be printed in case of failure.
2025-08-14T21:17:31.9376653Z     verbose : bool, optional
2025-08-14T21:17:31.9376868Z         If True, the conflicting values are appended to the error message.
2025-08-14T21:17:31.9376966Z     strict : bool, optional
2025-08-14T21:17:31.9377178Z         If True, raise an AssertionError when either the shape or the data
2025-08-14T21:17:31.9377354Z         type of the array_like objects does not match. The special
2025-08-14T21:17:31.9377557Z         handling for scalars mentioned in the Notes section is disabled.
2025-08-14T21:17:31.9377650Z     
2025-08-14T21:17:31.9377733Z     Raises
2025-08-14T21:17:31.9377816Z     ------
2025-08-14T21:17:31.9377919Z     AssertionError
2025-08-14T21:17:31.9378056Z         If actual and desired objects are not equal.
2025-08-14T21:17:31.9378135Z     
2025-08-14T21:17:31.9378233Z     See Also
2025-08-14T21:17:31.9378319Z     --------
2025-08-14T21:17:31.9378556Z     assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:31.9378702Z                      relative and/or absolute precision.
2025-08-14T21:17:31.9378912Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:31.9379006Z     
2025-08-14T21:17:31.9379089Z     Notes
2025-08-14T21:17:31.9379172Z     -----
2025-08-14T21:17:31.9379371Z     When one of `x` and `y` is a scalar and the other is array_like, the
2025-08-14T21:17:31.9379597Z     function checks that each element of the array_like object is equal to
2025-08-14T21:17:31.9379848Z     the scalar. This behaviour can be disabled with the `strict` parameter.
2025-08-14T21:17:31.9379942Z     
2025-08-14T21:17:31.9380027Z     Examples
2025-08-14T21:17:31.9380110Z     --------
2025-08-14T21:17:31.9380260Z     The first assert does not raise an exception:
2025-08-14T21:17:31.9380341Z     
2025-08-14T21:17:31.9380456Z     >>> np.testing.assert_array_equal(
2025-08-14T21:17:31.9380609Z     ...     [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan]
2025-08-14T21:17:31.9380695Z     ... )
2025-08-14T21:17:31.9380788Z     
2025-08-14T21:17:31.9381015Z     Use `assert_allclose` or one of the nulp (number of floating point values)
2025-08-14T21:17:31.9381128Z     functions for these cases instead:
2025-08-14T21:17:31.9381219Z     
2025-08-14T21:17:31.9381325Z     >>> np.testing.assert_allclose(
2025-08-14T21:17:31.9381519Z     ...     [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0
2025-08-14T21:17:31.9381616Z     ... )
2025-08-14T21:17:31.9381696Z     
2025-08-14T21:17:31.9381907Z     As mentioned in the Notes section, `assert_array_equal` has special
2025-08-14T21:17:31.9382144Z     handling for scalars. Here the test checks that each value in `x` is 3:
2025-08-14T21:17:31.9382221Z     
2025-08-14T21:17:31.9382336Z     >>> x = np.full((2, 5), fill_value=3)
2025-08-14T21:17:31.9382452Z     >>> np.testing.assert_array_equal(x, 3)
2025-08-14T21:17:31.9382529Z     
2025-08-14T21:17:31.9382807Z     Use `strict` to raise an AssertionError when comparing a scalar with an
2025-08-14T21:17:31.9382914Z     array:
2025-08-14T21:17:31.9382992Z     
2025-08-14T21:17:31.9383152Z     >>> np.testing.assert_array_equal(x, 3, strict=True)
2025-08-14T21:17:31.9383260Z     Traceback (most recent call last):
2025-08-14T21:17:31.9383343Z         ...
2025-08-14T21:17:31.9383443Z     AssertionError:
2025-08-14T21:17:31.9383536Z     Arrays are not equal
2025-08-14T21:17:31.9383619Z     <BLANKLINE>
2025-08-14T21:17:31.9383725Z     (shapes (2, 5), () mismatch)
2025-08-14T21:17:31.9383827Z      x: torch.ndarray([[3, 3, 3, 3, 3],
2025-08-14T21:17:31.9383927Z             [3, 3, 3, 3, 3]])
2025-08-14T21:17:31.9384019Z      y: torch.ndarray(3)
2025-08-14T21:17:31.9384100Z     
2025-08-14T21:17:31.9384325Z     The `strict` parameter also ensures that the array data types match:
2025-08-14T21:17:31.9384404Z     
2025-08-14T21:17:31.9384500Z     >>> x = np.array([2, 2, 2])
2025-08-14T21:17:31.9384645Z     >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32)
2025-08-14T21:17:31.9384796Z     >>> np.testing.assert_array_equal(x, y, strict=True)
2025-08-14T21:17:31.9384906Z     Traceback (most recent call last):
2025-08-14T21:17:31.9384998Z         ...
2025-08-14T21:17:31.9385089Z     AssertionError:
2025-08-14T21:17:31.9385184Z     Arrays are not equal
2025-08-14T21:17:31.9385284Z     <BLANKLINE>
2025-08-14T21:17:31.9385429Z     (dtypes dtype("int64"), dtype("float32") mismatch)
2025-08-14T21:17:31.9385542Z      x: torch.ndarray([2, 2, 2])
2025-08-14T21:17:31.9385645Z      y: torch.ndarray([2., 2., 2.])
2025-08-14T21:17:31.9385724Z     
2025-08-14T21:17:31.9385992Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9386069Z     
2025-08-14T21:17:31.9386166Z       warnings.warn(msg)
2025-08-14T21:17:31.9386258Z     
2025-08-14T21:17:31.9386452Z --- Parse Warning: 33 / 146 ---
2025-08-14T21:17:31.9387406Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851.
2025-08-14T21:17:31.9387683Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9387762Z     
2025-08-14T21:17:31.9387986Z     Raises an AssertionError if two objects are not equal up to desired
2025-08-14T21:17:31.9388074Z     precision.
2025-08-14T21:17:31.9388152Z     
2025-08-14T21:17:31.9388338Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-08-14T21:17:31.9388545Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-08-14T21:17:31.9388732Z               instead of this function for more consistent floating point
2025-08-14T21:17:31.9388838Z               comparisons.
2025-08-14T21:17:31.9388917Z     
2025-08-14T21:17:31.9389153Z     The test verifies identical shapes and that the elements of ``actual`` and
2025-08-14T21:17:31.9389263Z     ``desired`` satisfy.
2025-08-14T21:17:31.9389344Z     
2025-08-14T21:17:31.9389487Z         ``abs(desired-actual) < 1.5 * 10**(-decimal)``
2025-08-14T21:17:31.9389566Z     
2025-08-14T21:17:31.9389792Z     That is a looser test than originally documented, but agrees with what the
2025-08-14T21:17:31.9390044Z     actual implementation did up to rounding vagaries. An exception is raised
2025-08-14T21:17:31.9390274Z     at shape mismatch or conflicting values. In contrast to the standard usage
2025-08-14T21:17:31.9390492Z     in numpy, NaNs are compared like numbers, no assertion is raised if both
2025-08-14T21:17:31.9390626Z     objects have NaNs in the same positions.
2025-08-14T21:17:31.9390705Z     
2025-08-14T21:17:31.9390789Z     Parameters
2025-08-14T21:17:31.9390885Z     ----------
2025-08-14T21:17:31.9390975Z     x : array_like
2025-08-14T21:17:31.9391090Z         The actual object to check.
2025-08-14T21:17:31.9391175Z     y : array_like
2025-08-14T21:17:31.9391312Z         The desired, expected object.
2025-08-14T21:17:31.9391528Z     decimal : int, optional
2025-08-14T21:17:31.9391681Z         Desired precision, default is 6.
2025-08-14T21:17:31.9391776Z     err_msg : str, optional
2025-08-14T21:17:31.9391944Z       The error message to be printed in case of failure.
2025-08-14T21:17:31.9392046Z     verbose : bool, optional
2025-08-14T21:17:31.9392251Z         If True, the conflicting values are appended to the error message.
2025-08-14T21:17:31.9392344Z     
2025-08-14T21:17:31.9392427Z     Raises
2025-08-14T21:17:31.9392509Z     ------
2025-08-14T21:17:31.9392615Z     AssertionError
2025-08-14T21:17:31.9392809Z         If actual and desired are not equal up to specified precision.
2025-08-14T21:17:31.9392901Z     
2025-08-14T21:17:31.9392984Z     See Also
2025-08-14T21:17:31.9393067Z     --------
2025-08-14T21:17:31.9393312Z     assert_allclose: Compare two array_like objects for equality with desired
2025-08-14T21:17:31.9393440Z                      relative and/or absolute precision.
2025-08-14T21:17:31.9393646Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-08-14T21:17:31.9393738Z     
2025-08-14T21:17:31.9393821Z     Examples
2025-08-14T21:17:31.9393902Z     --------
2025-08-14T21:17:31.9394041Z     the first assert does not raise an exception
2025-08-14T21:17:31.9394119Z     
2025-08-14T21:17:31.9394370Z     >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan])
2025-08-14T21:17:31.9394460Z     
2025-08-14T21:17:31.9394581Z     >>> np.testing.assert_array_almost_equal(
2025-08-14T21:17:31.9394742Z     ...     [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5
2025-08-14T21:17:31.9394822Z     ... )
2025-08-14T21:17:31.9394931Z     Traceback (most recent call last):
2025-08-14T21:17:31.9395020Z         ...
2025-08-14T21:17:31.9395111Z     AssertionError:
2025-08-14T21:17:31.9395231Z     Arrays are not almost equal to 5 decimals
2025-08-14T21:17:31.9395324Z     <BLANKLINE>
2025-08-14T21:17:31.9395431Z     Mismatched elements: 1 / 3 (33.3%)
2025-08-14T21:17:31.9395559Z     Max absolute difference: 5.999999999994898e-05
2025-08-14T21:17:31.9395699Z     Max relative difference: 2.5713661239633743e-05
2025-08-14T21:17:31.9395860Z      x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-08-14T21:17:31.9396028Z      y: torch.ndarray([1.0000, 2.3334,    nan], dtype=float64)
2025-08-14T21:17:31.9396107Z     
2025-08-14T21:17:31.9396227Z     >>> np.testing.assert_array_almost_equal(
2025-08-14T21:17:31.9396371Z     ...     [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5
2025-08-14T21:17:31.9396451Z     ... )
2025-08-14T21:17:31.9396591Z     Traceback (most recent call last):
2025-08-14T21:17:31.9396684Z         ...
2025-08-14T21:17:31.9396775Z     AssertionError:
2025-08-14T21:17:31.9396893Z     Arrays are not almost equal to 5 decimals
2025-08-14T21:17:31.9396987Z     <BLANKLINE>
2025-08-14T21:17:31.9397092Z     x and y nan location mismatch:
2025-08-14T21:17:31.9397252Z      x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-08-14T21:17:31.9397419Z      y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64)
2025-08-14T21:17:31.9397499Z     
2025-08-14T21:17:31.9397587Z     
2025-08-14T21:17:31.9397840Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9397920Z     
2025-08-14T21:17:31.9398030Z       warnings.warn(msg)
2025-08-14T21:17:31.9398107Z     
2025-08-14T21:17:31.9398315Z --- Parse Warning: 34 / 146 ---
2025-08-14T21:17:31.9399285Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848.
2025-08-14T21:17:31.9399550Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9399775Z     Context manager that resets warning registry for catching warnings
2025-08-14T21:17:31.9399853Z     
2025-08-14T21:17:31.9400158Z         Warnings can be slippery, because, whenever a warning is triggered, Python
2025-08-14T21:17:31.9400427Z         adds a ``__warningregistry__`` member to the *calling* module.  This makes
2025-08-14T21:17:31.9400665Z         it impossible to retrigger the warning in this module, whatever you put in
2025-08-14T21:17:31.9400904Z         the warnings filters.  This context manager accepts a sequence of `modules`
2025-08-14T21:17:31.9401050Z         as a keyword argument to its constructor and:
2025-08-14T21:17:31.9401130Z     
2025-08-14T21:17:31.9401356Z         * stores and removes any ``__warningregistry__`` entries in given `modules`
2025-08-14T21:17:31.9401454Z           on entry;
2025-08-14T21:17:31.9401640Z         * resets ``__warningregistry__`` to its previous state on exit.
2025-08-14T21:17:31.9401735Z     
2025-08-14T21:17:31.9401957Z         This makes it possible to trigger any warning afresh inside the context
2025-08-14T21:17:31.9402140Z         manager without disturbing the state of warnings outside.
2025-08-14T21:17:31.9402235Z     
2025-08-14T21:17:31.9402465Z         For compatibility with Python 3.0, please consider all arguments to be
2025-08-14T21:17:31.9402558Z         keyword-only.
2025-08-14T21:17:31.9402646Z     
2025-08-14T21:17:31.9402734Z         Parameters
2025-08-14T21:17:31.9402819Z         ----------
2025-08-14T21:17:31.9402937Z         record : bool, optional
2025-08-14T21:17:31.9403123Z             Specifies whether warnings should be captured by a custom
2025-08-14T21:17:31.9403376Z             implementation of ``warnings.showwarning()`` and be appended to a list
2025-08-14T21:17:31.9403585Z             returned by the context manager. Otherwise None is returned by the
2025-08-14T21:17:31.9403811Z             context manager. The objects appended to the list are arguments whose
2025-08-14T21:17:31.9403993Z             attributes mirror the arguments to ``showwarning()``.
2025-08-14T21:17:31.9404104Z         modules : sequence, optional
2025-08-14T21:17:31.9404330Z             Sequence of modules for which to reset warnings registry on entry and
2025-08-14T21:17:31.9404536Z             restore on exit. To work correctly, all 'ignore' filters should
2025-08-14T21:17:31.9404650Z             filter by one of these modules.
2025-08-14T21:17:31.9404747Z     
2025-08-14T21:17:31.9404833Z         Examples
2025-08-14T21:17:31.9404919Z         --------
2025-08-14T21:17:31.9405029Z         >>> import warnings
2025-08-14T21:17:31.9405215Z         >>> with np.testing.clear_and_catch_warnings(  # doctest: +SKIP
2025-08-14T21:17:31.9405359Z         ...     modules=[np.core.fromnumeric]
2025-08-14T21:17:31.9405458Z         ... ):
2025-08-14T21:17:31.9405581Z         ...     warnings.simplefilter("always")
2025-08-14T21:17:31.9405804Z         ...     warnings.filterwarnings("ignore", module="np.core.fromnumeric")
2025-08-14T21:17:31.9405991Z         ...     # do something that raises a warning but ignore those in
2025-08-14T21:17:31.9406100Z         ...     # np.core.fromnumeric
2025-08-14T21:17:31.9406200Z         
2025-08-14T21:17:31.9406456Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9406538Z     
2025-08-14T21:17:31.9406650Z       warnings.warn(msg)
2025-08-14T21:17:31.9406732Z     
2025-08-14T21:17:31.9406922Z --- Parse Warning: 35 / 146 ---
2025-08-14T21:17:31.9407853Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354.
2025-08-14T21:17:31.9408118Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9408330Z     Applies a 1D convolution over a quantized input signal composed of
2025-08-14T21:17:31.9408458Z         several quantized input planes.
2025-08-14T21:17:31.9408541Z     
2025-08-14T21:17:31.9408810Z         For details on input arguments, parameters, and implementation see
2025-08-14T21:17:31.9408943Z         :class:`~torch.nn.Conv1d`.
2025-08-14T21:17:31.9409230Z     
2025-08-14T21:17:31.9409338Z         .. note::
2025-08-14T21:17:31.9409539Z             Only `zeros` is supported for the :attr:`padding_mode` argument.
2025-08-14T21:17:31.9409619Z     
2025-08-14T21:17:31.9409719Z         .. note::
2025-08-14T21:17:31.9409896Z             Only `torch.quint8` is supported for the input data type.
2025-08-14T21:17:31.9409976Z     
2025-08-14T21:17:31.9410067Z     
2025-08-14T21:17:31.9410157Z         Attributes:
2025-08-14T21:17:31.9410371Z             weight (Tensor):     packed tensor derived from the learnable weight
2025-08-14T21:17:31.9410485Z                                  parameter.
2025-08-14T21:17:31.9410628Z             scale (Tensor):      scalar for the output scale
2025-08-14T21:17:31.9410804Z             zero_point (Tensor): scalar for the output zero point
2025-08-14T21:17:31.9410883Z     
2025-08-14T21:17:31.9411037Z         See :class:`~torch.nn.Conv1d` for other attributes.
2025-08-14T21:17:31.9411127Z     
2025-08-14T21:17:31.9411218Z         Examples::
2025-08-14T21:17:31.9411296Z     
2025-08-14T21:17:31.9411456Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE)
2025-08-14T21:17:31.9411587Z             >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
2025-08-14T21:17:31.9411700Z             >>> input = torch.randn(20, 16, 100)
2025-08-14T21:17:31.9411821Z             >>> # quantize input to quint8
2025-08-14T21:17:31.9411917Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9412139Z             >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0,
2025-08-14T21:17:31.9412266Z             ...                                     dtype=torch.quint8)
2025-08-14T21:17:31.9412366Z             >>> output = m(q_input)
2025-08-14T21:17:31.9412456Z     
2025-08-14T21:17:31.9412538Z         
2025-08-14T21:17:31.9412788Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9412885Z     
2025-08-14T21:17:31.9412983Z       warnings.warn(msg)
2025-08-14T21:17:31.9413066Z     
2025-08-14T21:17:31.9413270Z --- Parse Warning: 36 / 146 ---
2025-08-14T21:17:31.9414160Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12.
2025-08-14T21:17:31.9414437Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9414633Z     A quantized long short-term memory (LSTM).
2025-08-14T21:17:31.9414715Z     
2025-08-14T21:17:31.9415007Z         For the description and the argument types, please, refer to :class:`~torch.nn.LSTM`
2025-08-14T21:17:31.9415085Z     
2025-08-14T21:17:31.9415172Z         Attributes:
2025-08-14T21:17:31.9415309Z             layers : instances of the `_LSTMLayer`
2025-08-14T21:17:31.9415389Z     
2025-08-14T21:17:31.9415476Z         .. note::
2025-08-14T21:17:31.9415704Z             To access the weights and biases, you need to access them per layer.
2025-08-14T21:17:31.9415879Z             See examples in :class:`~torch.ao.nn.quantizable.LSTM`
2025-08-14T21:17:31.9415971Z     
2025-08-14T21:17:31.9416061Z         Examples::
2025-08-14T21:17:31.9416159Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9416279Z             >>> custom_module_config = {
2025-08-14T21:17:31.9416417Z             ...     'float_to_observed_custom_module_class': {
2025-08-14T21:17:31.9416544Z             ...         nn.LSTM: nn.quantizable.LSTM,
2025-08-14T21:17:31.9416641Z             ...     },
2025-08-14T21:17:31.9416789Z             ...     'observed_to_quantized_custom_module_class': {
2025-08-14T21:17:31.9416941Z             ...         nn.quantizable.LSTM: nn.quantized.LSTM,
2025-08-14T21:17:31.9417024Z             ...     }
2025-08-14T21:17:31.9417105Z             ... }
2025-08-14T21:17:31.9417377Z             >>> tq.prepare(model, prepare_custom_module_class=custom_module_config)
2025-08-14T21:17:31.9417624Z             >>> tq.convert(model, convert_custom_module_class=custom_module_config)
2025-08-14T21:17:31.9417742Z         
2025-08-14T21:17:31.9418011Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9418092Z     
2025-08-14T21:17:31.9418191Z       warnings.warn(msg)
2025-08-14T21:17:31.9418286Z     
2025-08-14T21:17:31.9418478Z --- Parse Warning: 37 / 146 ---
2025-08-14T21:17:31.9419679Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16.
2025-08-14T21:17:31.9419945Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9420026Z     
2025-08-14T21:17:31.9420307Z     The Activation sparsifier class aims to sparsify/prune activations in a neural
2025-08-14T21:17:31.9420538Z     network. The idea is to attach the sparsifier to a layer (or layers) and it
2025-08-14T21:17:31.9420787Z     zeroes out the activations based on the mask_fn (or sparsification function)
2025-08-14T21:17:31.9420893Z     input by the user.
2025-08-14T21:17:31.9421115Z     The mask_fn is applied once all the inputs are aggregated and reduced i.e.
2025-08-14T21:17:31.9421283Z     mask = mask_fn(reduce_fn(aggregate_fn(activations)))
2025-08-14T21:17:31.9421366Z     
2025-08-14T21:17:31.9421451Z     Note::
2025-08-14T21:17:31.9421788Z         The sparsification mask is computed on the input **before it goes through the attached layer**.
2025-08-14T21:17:31.9421867Z     
2025-08-14T21:17:31.9421949Z     Args:
2025-08-14T21:17:31.9422057Z         model (nn.Module):
2025-08-14T21:17:31.9422281Z             The model whose layers will be sparsified. The layers that needs to be
2025-08-14T21:17:31.9422523Z             sparsified should be added separately using the register_layer() function
2025-08-14T21:17:31.9422653Z         aggregate_fn (Optional, Callable):
2025-08-14T21:17:31.9422910Z             default aggregate_fn that is used if not specified while registering the layer.
2025-08-14T21:17:31.9423087Z             specifies how inputs should be aggregated over time.
2025-08-14T21:17:31.9423372Z             The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor.
2025-08-14T21:17:31.9423459Z             Example
2025-08-14T21:17:31.9423645Z                 def add_agg_fn(tensor1, tensor2):  return tensor1 + tensor2
2025-08-14T21:17:31.9423789Z                 reduce_fn (Optional, Callable):
2025-08-14T21:17:31.9424033Z                     default reduce_fn that is used if not specified while registering the layer.
2025-08-14T21:17:31.9424298Z                     reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after
2025-08-14T21:17:31.9424416Z                     calling agg_fn() on all inputs.
2025-08-14T21:17:31.9424519Z                     Example
2025-08-14T21:17:31.9424717Z                 def mean_reduce_fn(agg_tensor):    return agg_tensor.mean(dim=0)
2025-08-14T21:17:31.9424829Z                 mask_fn (Optional, Callable):
2025-08-14T21:17:31.9425149Z                     default mask_fn that is used to create the sparsification mask using the tensor obtained after
2025-08-14T21:17:31.9425399Z                     calling the reduce_fn(). This is used by default if a custom one is passed in the
2025-08-14T21:17:31.9425498Z                     register_layer().
2025-08-14T21:17:31.9425856Z                     Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config
2025-08-14T21:17:31.9425949Z                     arguments.
2025-08-14T21:17:31.9426071Z                 features (Optional, list):
2025-08-14T21:17:31.9426201Z                     default selected features to sparsify.
2025-08-14T21:17:31.9426491Z                     If this is non-empty, then the mask_fn will be applied for each feature of the input.
2025-08-14T21:17:31.9426655Z                     For example,
2025-08-14T21:17:31.9426905Z                 mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features]
2025-08-14T21:17:31.9427019Z                 feature_dim (Optional, int):
2025-08-14T21:17:31.9427305Z                     default dimension of input features. Again, features along this dim will be chosen
2025-08-14T21:17:31.9427407Z                     for sparsification.
2025-08-14T21:17:31.9427524Z                 sparse_config (Dict):
2025-08-14T21:17:31.9427745Z                     Default configuration for the mask_fn. This config will be passed
2025-08-14T21:17:31.9427844Z                     with the mask_fn()
2025-08-14T21:17:31.9427936Z     
2025-08-14T21:17:31.9428020Z     Example:
2025-08-14T21:17:31.9428117Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9428225Z         >>> model = SomeModel()
2025-08-14T21:17:31.9428469Z         >>> act_sparsifier = ActivationSparsifier(...)  # init activation sparsifier
2025-08-14T21:17:31.9428576Z         >>> # Initialize aggregate_fn
2025-08-14T21:17:31.9428682Z         >>> def agg_fn(x, y):
2025-08-14T21:17:31.9428775Z         >>>     return x + y
2025-08-14T21:17:31.9428869Z         >>>
2025-08-14T21:17:31.9428968Z         >>> # Initialize reduce_fn
2025-08-14T21:17:31.9429063Z         >>> def reduce_fn(x):
2025-08-14T21:17:31.9429184Z         >>>     return torch.mean(x, dim=0)
2025-08-14T21:17:31.9429263Z         >>>
2025-08-14T21:17:31.9429363Z         >>> # Initialize mask_fn
2025-08-14T21:17:31.9429471Z         >>> def mask_fn(data):
2025-08-14T21:17:31.9429614Z         >>>     return torch.eye(data.shape).to(data.device)
2025-08-14T21:17:31.9429697Z         >>>
2025-08-14T21:17:31.9429787Z         >>>
2025-08-14T21:17:31.9429902Z         >>> act_sparsifier.register_layer(
2025-08-14T21:17:31.9430001Z         ...     model.some_layer,
2025-08-14T21:17:31.9430117Z         ...     aggregate_fn=agg_fn,
2025-08-14T21:17:31.9430217Z         ...     reduce_fn=reduce_fn,
2025-08-14T21:17:31.9430328Z         ...     mask_fn=mask_fn,
2025-08-14T21:17:31.9430408Z         ... )
2025-08-14T21:17:31.9430488Z         >>>
2025-08-14T21:17:31.9430600Z         >>> # start training process
2025-08-14T21:17:31.9430691Z         >>> for _ in [...]:
2025-08-14T21:17:31.9430785Z         >>> # epoch starts
2025-08-14T21:17:31.9430968Z         >>> # model.forward(), compute_loss() and model.backwards()
2025-08-14T21:17:31.9431059Z         >>> # epoch ends
2025-08-14T21:17:31.9431165Z         >>>     act_sparsifier.step()
2025-08-14T21:17:31.9431302Z         >>> # end training process
2025-08-14T21:17:31.9431505Z         >>> sparsifier.squash_mask()
2025-08-14T21:17:31.9431588Z     
2025-08-14T21:17:31.9431857Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9431938Z     
2025-08-14T21:17:31.9432048Z       warnings.warn(msg)
2025-08-14T21:17:31.9432126Z     
2025-08-14T21:17:31.9432333Z --- Parse Warning: 38 / 146 ---
2025-08-14T21:17:31.9433552Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91.
2025-08-14T21:17:31.9433815Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9433896Z     
2025-08-14T21:17:31.9434118Z     Abstract method that needs to be implemented by the child class.
2025-08-14T21:17:31.9434374Z     The expected return type should is a dictionary of name to schedule_param value
2025-08-14T21:17:31.9434657Z     The returned values will be updated in sparsifier when the scheduler step() function
2025-08-14T21:17:31.9434743Z     is called.
2025-08-14T21:17:31.9434823Z     
2025-08-14T21:17:31.9434924Z     Example:
2025-08-14T21:17:31.9435075Z         >>> def get_schedule_param(self):
2025-08-14T21:17:31.9435203Z         ...     new_param = {}
2025-08-14T21:17:31.9435400Z         ...     for name in self.sparsifier.data_groups.keys():
2025-08-14T21:17:31.9435503Z         ...         new_param[name] = (
2025-08-14T21:17:31.9435711Z         ...             self.sparsifier.data_groups[name][self.schedule_param] * 0.5
2025-08-14T21:17:31.9435811Z         ...         )
2025-08-14T21:17:31.9435910Z         ...     return new_param
2025-08-14T21:17:31.9435998Z     
2025-08-14T21:17:31.9444103Z     When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param]
2025-08-14T21:17:31.9444283Z     would be halved
2025-08-14T21:17:31.9444367Z     
2025-08-14T21:17:31.9444651Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9444732Z     
2025-08-14T21:17:31.9444833Z       warnings.warn(msg)
2025-08-14T21:17:31.9444925Z     
2025-08-14T21:17:31.9445178Z --- Parse Warning: 39 / 146 ---
2025-08-14T21:17:31.9446258Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229.
2025-08-14T21:17:31.9446539Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9446714Z     Squashes the sparse masks into the appropriate tensors.
2025-08-14T21:17:31.9446811Z     
2025-08-14T21:17:31.9447019Z             If either the `params_to_keep` or `params_to_keep_per_layer` is set,
2025-08-14T21:17:31.9447203Z             the module will have a `sparse_params` dict attached to it.
2025-08-14T21:17:31.9447299Z     
2025-08-14T21:17:31.9447383Z             Args:
2025-08-14T21:17:31.9447566Z                 params_to_keep: List of keys to save in the module or a dict
2025-08-14T21:17:31.9447739Z                                 representing the modules and keys that will have
2025-08-14T21:17:31.9447865Z                                 sparsity parameters saved
2025-08-14T21:17:31.9448083Z                 params_to_keep_per_layer: Dict to specify the params that should be
2025-08-14T21:17:31.9448245Z                                 saved for specific layers. The keys in the dict
2025-08-14T21:17:31.9448400Z                                 should be the module fqn, while the values should
2025-08-14T21:17:31.9448569Z                                 be a list of strings with the names of the variables
2025-08-14T21:17:31.9448776Z                                 to save in the `sparse_params`
2025-08-14T21:17:31.9448860Z     
2025-08-14T21:17:31.9448958Z             Examples:
2025-08-14T21:17:31.9449089Z                 >>> # xdoctest: +SKIP("locals are undefined")
2025-08-14T21:17:31.9449206Z                 >>> # Don't save any sparse params
2025-08-14T21:17:31.9449333Z                 >>> sparsifier.squash_mask()
2025-08-14T21:17:31.9449473Z                 >>> hasattr(model.submodule1, "sparse_params")
2025-08-14T21:17:31.9449579Z                 False
2025-08-14T21:17:31.9449658Z     
2025-08-14T21:17:31.9449775Z                 >>> # Keep sparse params per layer
2025-08-14T21:17:31.9449900Z                 >>> sparsifier.squash_mask(
2025-08-14T21:17:31.9450015Z                 ...     params_to_keep_per_layer={
2025-08-14T21:17:31.9450146Z                 ...         "submodule1.linear1": ("foo", "bar"),
2025-08-14T21:17:31.9450282Z                 ...         "submodule2.linear42": ("baz",),
2025-08-14T21:17:31.9450370Z                 ...     }
2025-08-14T21:17:31.9450455Z                 ... )
2025-08-14T21:17:31.9450624Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:31.9450728Z                 {'foo': 42, 'bar': 24}
2025-08-14T21:17:31.9450895Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:31.9450987Z                 {'baz': 0.1}
2025-08-14T21:17:31.9451068Z     
2025-08-14T21:17:31.9451270Z                 >>> # Keep sparse params for all layers
2025-08-14T21:17:31.9451471Z                 >>> sparsifier.squash_mask(params_to_keep=("foo", "bar"))
2025-08-14T21:17:31.9451623Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:31.9451732Z                 {'foo': 42, 'bar': 24}
2025-08-14T21:17:31.9451885Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:31.9451982Z                 {'foo': 42, 'bar': 24}
2025-08-14T21:17:31.9452071Z     
2025-08-14T21:17:31.9452266Z                 >>> # Keep some sparse params for all layers, and specific ones for
2025-08-14T21:17:31.9452378Z                 >>> # some other layers
2025-08-14T21:17:31.9452487Z                 >>> sparsifier.squash_mask(
2025-08-14T21:17:31.9452607Z                 ...     params_to_keep=("foo", "bar"),
2025-08-14T21:17:31.9452810Z                 ...     params_to_keep_per_layer={"submodule2.linear42": ("baz",)},
2025-08-14T21:17:31.9452896Z                 ... )
2025-08-14T21:17:31.9453051Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-08-14T21:17:31.9453162Z                 {'foo': 42, 'bar': 24}
2025-08-14T21:17:31.9453316Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-08-14T21:17:31.9453424Z                 {'foo': 42, 'bar': 24, 'baz': 0.1}
2025-08-14T21:17:31.9453519Z             
2025-08-14T21:17:31.9453772Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9453866Z     
2025-08-14T21:17:31.9453963Z       warnings.warn(msg)
2025-08-14T21:17:31.9454043Z     
2025-08-14T21:17:31.9454254Z --- Parse Warning: 40 / 146 ---
2025-08-14T21:17:31.9455288Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181.
2025-08-14T21:17:31.9455552Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9455648Z     
2025-08-14T21:17:31.9455897Z     Config object that specifies the supported data types passed as arguments to
2025-08-14T21:17:31.9456147Z     quantize ops in the reference model spec, for input and output activations,
2025-08-14T21:17:31.9456243Z     weights, and biases.
2025-08-14T21:17:31.9456323Z     
2025-08-14T21:17:31.9456494Z     For example, consider the following reference model:
2025-08-14T21:17:31.9456575Z     
2025-08-14T21:17:31.9456734Z       quant1 - [dequant1 - fp32_linear - quant2] - dequant2
2025-08-14T21:17:31.9456849Z     
2025-08-14T21:17:31.9457067Z     The pattern in the square brackets refers to the reference pattern of
2025-08-14T21:17:31.9457302Z     statically quantized linear. Setting the input dtype as `torch.quint8`
2025-08-14T21:17:31.9457539Z     in the DTypeConfig means we pass in `torch.quint8` as the dtype argument
2025-08-14T21:17:31.9457763Z     to the first quantize op (quant1). Similarly, setting the output dtype as
2025-08-14T21:17:31.9457998Z     `torch.quint8` means we pass in `torch.quint8` as the dtype argument to
2025-08-14T21:17:31.9458108Z     the second quantize op (quant2).
2025-08-14T21:17:31.9458189Z     
2025-08-14T21:17:31.9458411Z     Note that the dtype here does not refer to the interface dtypes of the
2025-08-14T21:17:31.9458617Z     op. For example, the "input dtype" here is not the dtype of the input
2025-08-14T21:17:31.9458830Z     tensor passed to the quantized linear op. Though it can still be the
2025-08-14T21:17:31.9459037Z     same as the interface dtype, this is not always the case, e.g. the
2025-08-14T21:17:31.9459255Z     interface dtype is fp32 in dynamic quantization but the "input dtype"
2025-08-14T21:17:31.9459476Z     specified in the DTypeConfig would still be quint8. The semantics of
2025-08-14T21:17:31.9459685Z     dtypes here are the same as the semantics of the dtypes specified in
2025-08-14T21:17:31.9459775Z     the observers.
2025-08-14T21:17:31.9459921Z     
2025-08-14T21:17:31.9460128Z     These dtypes are matched against the ones specified in the user's
2025-08-14T21:17:31.9460369Z     QConfig. If there is a match, and the QConfig satisfies the constraints
2025-08-14T21:17:31.9460598Z     specified in the DTypeConfig (if any), then we will quantize the given
2025-08-14T21:17:31.9460823Z     pattern using this DTypeConfig. Otherwise, the QConfig is ignored and
2025-08-14T21:17:31.9460944Z     the pattern will not be quantized.
2025-08-14T21:17:31.9461023Z     
2025-08-14T21:17:31.9461126Z     Example usage::
2025-08-14T21:17:31.9461224Z     
2025-08-14T21:17:31.9461330Z         >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:31.9461441Z         >>> dtype_config1 = DTypeConfig(
2025-08-14T21:17:31.9461557Z         ...     input_dtype=torch.quint8,
2025-08-14T21:17:31.9461663Z         ...     output_dtype=torch.quint8,
2025-08-14T21:17:31.9461770Z         ...     weight_dtype=torch.qint8,
2025-08-14T21:17:31.9461886Z         ...     bias_dtype=torch.float)
2025-08-14T21:17:31.9461965Z     
2025-08-14T21:17:31.9462075Z         >>> dtype_config2 = DTypeConfig(
2025-08-14T21:17:31.9462217Z         ...     input_dtype=DTypeWithConstraints(
2025-08-14T21:17:31.9462317Z         ...         dtype=torch.quint8,
2025-08-14T21:17:31.9462433Z         ...         quant_min_lower_bound=0,
2025-08-14T21:17:31.9462547Z         ...         quant_max_upper_bound=255,
2025-08-14T21:17:31.9462628Z         ...     ),
2025-08-14T21:17:31.9462768Z         ...     output_dtype=DTypeWithConstraints(
2025-08-14T21:17:31.9462869Z         ...         dtype=torch.quint8,
2025-08-14T21:17:31.9462975Z         ...         quant_min_lower_bound=0,
2025-08-14T21:17:31.9463096Z         ...         quant_max_upper_bound=255,
2025-08-14T21:17:31.9463178Z         ...     ),
2025-08-14T21:17:31.9463302Z         ...     weight_dtype=DTypeWithConstraints(
2025-08-14T21:17:31.9463417Z         ...         dtype=torch.qint8,
2025-08-14T21:17:31.9463533Z         ...         quant_min_lower_bound=-128,
2025-08-14T21:17:31.9463643Z         ...         quant_max_upper_bound=127,
2025-08-14T21:17:31.9463738Z         ...     ),
2025-08-14T21:17:31.9463846Z         ...     bias_dtype=torch.float)
2025-08-14T21:17:31.9463937Z     
2025-08-14T21:17:31.9464046Z         >>> dtype_config1.input_dtype
2025-08-14T21:17:31.9464137Z         torch.quint8
2025-08-14T21:17:31.9464228Z     
2025-08-14T21:17:31.9464335Z         >>> dtype_config2.input_dtype
2025-08-14T21:17:31.9464425Z         torch.quint8
2025-08-14T21:17:31.9464515Z     
2025-08-14T21:17:31.9464676Z         >>> dtype_config2.input_dtype_with_constraints
2025-08-14T21:17:31.9465222Z         DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None)
2025-08-14T21:17:31.9465312Z     
2025-08-14T21:17:31.9465566Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9465658Z     
2025-08-14T21:17:31.9465758Z       warnings.warn(msg)
2025-08-14T21:17:31.9465838Z     
2025-08-14T21:17:31.9466044Z --- Parse Warning: 41 / 146 ---
2025-08-14T21:17:31.9467068Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24.
2025-08-14T21:17:31.9467328Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9467421Z     
2025-08-14T21:17:31.9467730Z     The ModelReport class aims to provide users an easy way to diagnose issues that they run into
2025-08-14T21:17:31.9468037Z     with their models. The class works with all traceable GraphModules to help diagnose issues,
2025-08-14T21:17:31.9468336Z     though the requirements on the type of model more-so depends on the specific report the user
2025-08-14T21:17:31.9468667Z     is trying to generate. With respect to the reports, the ModelReport class is initialized with
2025-08-14T21:17:31.9469004Z     a set of Detector classes, each of which generate reports on quantization configuration
2025-08-14T21:17:31.9469106Z     issues a use might have.
2025-08-14T21:17:31.9469187Z     
2025-08-14T21:17:31.9469328Z     Currently supports generating reports on:
2025-08-14T21:17:31.9469557Z     - Suggestions for per-channel vs. per-tensor quantization (nn.Module)
2025-08-14T21:17:31.9469838Z     - Suggestions for dynamic vs static quantization for linear layers (Graph Modules)
2025-08-14T21:17:31.9470133Z     - Suggestions for input-weight equalization for linear and conv layers (Graph Modules)
2025-08-14T21:17:31.9470345Z     - Suggestions for outlier detection for all layers (Graph Modules)
2025-08-14T21:17:31.9470438Z     
2025-08-14T21:17:31.9470838Z     The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver)
2025-08-14T21:17:31.9471214Z     where needed for each detector to gather the information it needs, and then after calibration, the ModelReport
2025-08-14T21:17:31.9471718Z     class compiles the report generated by each Detector class into a single report to return to the user. It also
2025-08-14T21:17:31.9471932Z     has the capability to remove all the observers it inserted as well.
2025-08-14T21:17:31.9472026Z     
2025-08-14T21:17:31.9472307Z     * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule
2025-08-14T21:17:31.9472388Z     
2025-08-14T21:17:31.9472778Z     * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class
2025-08-14T21:17:31.9473095Z         Make sure that these are all unique types of detectors [do not have more than 1 of the same class]
2025-08-14T21:17:31.9473178Z     
2025-08-14T21:17:31.9473475Z     * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors.
2025-08-14T21:17:31.9473705Z         This set is generated by calling the get_detector_name() of each detector
2025-08-14T21:17:31.9473801Z     
2025-08-14T21:17:31.9474134Z     * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest
2025-08-14T21:17:31.9474453Z         The purpose of this is to keep track of what observers were inserted for each detector, so that they
2025-08-14T21:17:31.9474581Z         can be removed at the end if desired
2025-08-14T21:17:31.9474660Z     
2025-08-14T21:17:31.9474977Z     * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not
2025-08-14T21:17:31.9475262Z         This is to ensure we only insert observers once with the ModelReport instance
2025-08-14T21:17:31.9475342Z     
2025-08-14T21:17:31.9475614Z     * :attr:`_removed_observers` A boolean to track if we have removed observers already
2025-08-14T21:17:31.9475906Z         The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport
2025-08-14T21:17:31.9476226Z         instance. This also allows the functionality where we can generate the report multiple times
2025-08-14T21:17:31.9476388Z         as long as we haven't removed the observers yet.
2025-08-14T21:17:31.9476469Z     
2025-08-14T21:17:31.9476553Z     Note:
2025-08-14T21:17:31.9476860Z         This class was initially designed to work with the Fx Graph Mode workflow in mind. However,
2025-08-14T21:17:31.9477171Z         full functionality is available as long as there is a traceable GraphModule that is being used.
2025-08-14T21:17:31.9477481Z         One method to get a traceable GraphModule without going through the Fx workflow is to use
2025-08-14T21:17:31.9477595Z         the QuantizationTracer class.
2025-08-14T21:17:31.9477677Z     
2025-08-14T21:17:31.9477791Z     General Flow for Fx workflow:
2025-08-14T21:17:31.9478183Z     1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model
2025-08-14T21:17:31.9478332Z     2.) Prepare your model with prepare_fx
2025-08-14T21:17:31.9478627Z     3.) Call model_report.prepare_detailed_calibration to add relevant observers
2025-08-14T21:17:31.9478762Z     4.) Calibrate your model with data
2025-08-14T21:17:31.9479129Z     5.) Call model_report.generate_report on your model to generate report and optionally remove added observers
2025-08-14T21:17:31.9479213Z     Optional
2025-08-14T21:17:31.9479484Z         6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance
2025-08-14T21:17:31.9479737Z         7.) To help in parsing report information and debugging, view report info as a:
2025-08-14T21:17:31.9479828Z             - Table
2025-08-14T21:17:31.9479918Z             - Histogram
2025-08-14T21:17:31.9480025Z             - Line plot
2025-08-14T21:17:31.9480341Z     8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions
2025-08-14T21:17:31.9480423Z     
2025-08-14T21:17:31.9480555Z     Example (with QuantizationTracer):
2025-08-14T21:17:31.9480656Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9480779Z         >>> # get the necessary qconfig
2025-08-14T21:17:31.9480897Z         >>> config = PrepareCustomConfig()
2025-08-14T21:17:31.9481050Z         >>> skipped_module_names, skipped_module_classes = (
2025-08-14T21:17:31.9481224Z         ...     get_skipped_module_name_and_classes(config, False)
2025-08-14T21:17:31.9481304Z         ... )
2025-08-14T21:17:31.9481385Z     
2025-08-14T21:17:31.9481528Z         >>> # initialize our model and get GraphModule
2025-08-14T21:17:31.9481627Z         >>> model = SomeModel()
2025-08-14T21:17:31.9481881Z         >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes)
2025-08-14T21:17:31.9482063Z         >>> graph_module = GraphModule(model, tracer.trace(model))
2025-08-14T21:17:31.9482142Z     
2025-08-14T21:17:31.9482307Z         >>> # get our set of detectors and ModelReport instance
2025-08-14T21:17:31.9482404Z         >>> detector_set = set(
2025-08-14T21:17:31.9482488Z         ...     [
2025-08-14T21:17:31.9482643Z         ...         DynamicStaticDetector(tolerance=0.5),
2025-08-14T21:17:31.9482838Z         ...         InputWeightEqualizationDetector(ratio_threshold=0.7),
2025-08-14T21:17:31.9482919Z         ...     ]
2025-08-14T21:17:31.9483013Z         ... )
2025-08-14T21:17:31.9483219Z         >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set)
2025-08-14T21:17:31.9483299Z     
2025-08-14T21:17:31.9483468Z         >>> # now we insert the observers and calibrate the model
2025-08-14T21:17:31.9483751Z         >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration()
2025-08-14T21:17:31.9483898Z         >>> for i in range(num_callibration_batches):
2025-08-14T21:17:31.9484033Z         >>>     example_input = get_callibration_input()
2025-08-14T21:17:31.9484169Z         >>>     tracer_model_with_observers(example_input)
2025-08-14T21:17:31.9484260Z     
2025-08-14T21:17:31.9484522Z         >>> # finally we generate the reports and optionally remove the observers we inserted
2025-08-14T21:17:31.9484674Z         >>> reports = tracer_reporter.generate_model_report(
2025-08-14T21:17:31.9484804Z         ...     remove_inserted_observers=True
2025-08-14T21:17:31.9484884Z         ... )
2025-08-14T21:17:31.9484962Z     
2025-08-14T21:17:31.9485194Z         >>> # Optional: we can generate the qconfig mapping based on the suggestions
2025-08-14T21:17:31.9485351Z         >>> qconfigs = model_report.generate_qconfig_mapping()
2025-08-14T21:17:31.9485443Z     
2025-08-14T21:17:31.9485687Z         >>> # Optional: we can generate the equalization mapping based on the suggestions
2025-08-14T21:17:31.9485862Z         >>> qconfigs = model_report.generate_equalization_mapping()
2025-08-14T21:17:31.9485955Z     
2025-08-14T21:17:31.9486232Z         >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired
2025-08-14T21:17:31.9486439Z         >>> model_report_visualizer = tracer_reporter.generate_visualizer()
2025-08-14T21:17:31.9486527Z     
2025-08-14T21:17:31.9486661Z     
2025-08-14T21:17:31.9486916Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9487030Z     
2025-08-14T21:17:31.9487126Z       warnings.warn(msg)
2025-08-14T21:17:31.9487215Z     
2025-08-14T21:17:31.9487428Z --- Parse Warning: 42 / 146 ---
2025-08-14T21:17:31.9488693Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301.
2025-08-14T21:17:31.9488970Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9489048Z     
2025-08-14T21:17:31.9489319Z     Takes in optional filter values and generates two tables with desired information.
2025-08-14T21:17:31.9489410Z     
2025-08-14T21:17:31.9489620Z     The generated tables are presented in both a list-of-lists format
2025-08-14T21:17:31.9489712Z     
2025-08-14T21:17:31.9489921Z     The reason for the two tables are that they handle different things:
2025-08-14T21:17:31.9490082Z     1.) the first table handles all tensor level information
2025-08-14T21:17:31.9490310Z     2.) the second table handles and displays all channel based information
2025-08-14T21:17:31.9490390Z     
2025-08-14T21:17:31.9490710Z     The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-08-14T21:17:31.9491051Z         statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-08-14T21:17:31.9491400Z         tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-08-14T21:17:31.9491491Z     
2025-08-14T21:17:31.9491589Z     Tensor table columns:
2025-08-14T21:17:31.9491780Z         idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:31.9491949Z         ----  ---------  ---------   ---------   ---------        ---------
2025-08-14T21:17:31.9492030Z     
2025-08-14T21:17:31.9492139Z     Per-Channel table columns:
2025-08-14T21:17:31.9492369Z         idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:31.9492532Z         ----  ---------  -------  ---------   ---------   ---------        ---------
2025-08-14T21:17:31.9492612Z     
2025-08-14T21:17:31.9492705Z     Args:
2025-08-14T21:17:31.9492964Z         feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:31.9493117Z             contain this filter substring
2025-08-14T21:17:31.9493281Z             Default = "", results in all the features being printed
2025-08-14T21:17:31.9493539Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:31.9493796Z             Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:31.9493876Z     
2025-08-14T21:17:31.9493988Z     Returns a dictionary with two keys:
2025-08-14T21:17:31.9494173Z         (Dict[str, Tuple[List, List]]) A dict containing two keys:
2025-08-14T21:17:31.9494300Z         "tensor_level_info", "channel_level_info"
2025-08-14T21:17:31.9494423Z             Each key maps to a tuple with:
2025-08-14T21:17:31.9494544Z                 A list of the headers of each table
2025-08-14T21:17:31.9494725Z                 A list of lists containing the table information row by row
2025-08-14T21:17:31.9494910Z                 The 0th index row will contain the headers of the columns
2025-08-14T21:17:31.9495035Z                 The rest of the rows will contain data
2025-08-14T21:17:31.9495116Z     
2025-08-14T21:17:31.9495217Z     Example Use:
2025-08-14T21:17:31.9495345Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9495494Z         >>> mod_report_visualizer.generate_filtered_tables(
2025-08-14T21:17:31.9495741Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:31.9496067Z         ... )  # generates table with per_channel_min info for all modules in block 1 of the model
2025-08-14T21:17:31.9496161Z     
2025-08-14T21:17:31.9496412Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9496492Z     
2025-08-14T21:17:31.9496599Z       warnings.warn(msg)
2025-08-14T21:17:31.9496676Z     
2025-08-14T21:17:31.9496871Z --- Parse Warning: 43 / 146 ---
2025-08-14T21:17:31.9498163Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399.
2025-08-14T21:17:31.9498422Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9498512Z     
2025-08-14T21:17:31.9498784Z     Takes in optional filter values and prints out formatted tables of the information.
2025-08-14T21:17:31.9498866Z     
2025-08-14T21:17:31.9499223Z     The reason for the two tables printed out instead of one large one are that they handle different things:
2025-08-14T21:17:31.9499387Z     1.) the first table handles all tensor level information
2025-08-14T21:17:31.9499603Z     2.) the second table handles and displays all channel based information
2025-08-14T21:17:31.9499696Z     
2025-08-14T21:17:31.9500018Z     The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-08-14T21:17:31.9500358Z         statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-08-14T21:17:31.9500715Z         tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-08-14T21:17:31.9500798Z     
2025-08-14T21:17:31.9500909Z     Tensor table columns:
2025-08-14T21:17:31.9501100Z      idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:31.9501257Z     ----  ---------  ---------   ---------   ---------        ---------
2025-08-14T21:17:31.9501351Z     
2025-08-14T21:17:31.9501456Z     Per-Channel table columns:
2025-08-14T21:17:31.9501538Z     
2025-08-14T21:17:31.9501767Z      idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-08-14T21:17:31.9501925Z     ----  ---------  -------  ---------   ---------   ---------        ---------
2025-08-14T21:17:31.9502018Z     
2025-08-14T21:17:31.9502100Z     Args:
2025-08-14T21:17:31.9502388Z         feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:31.9502514Z             contain this filter substring
2025-08-14T21:17:31.9502676Z             Default = "", results in all the features being printed
2025-08-14T21:17:31.9502932Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:31.9503189Z             Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:31.9503271Z     
2025-08-14T21:17:31.9503361Z     Example Use:
2025-08-14T21:17:31.9503503Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9503667Z         >>> mod_report_visualizer.generate_table_visualization(
2025-08-14T21:17:31.9503872Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:31.9503953Z         ... )
2025-08-14T21:17:31.9504144Z         >>> # prints out neatly formatted table with per_channel_min info
2025-08-14T21:17:31.9504281Z         >>> # for all modules in block 1 of the model
2025-08-14T21:17:31.9504362Z     
2025-08-14T21:17:31.9504611Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9504699Z     
2025-08-14T21:17:31.9504794Z       warnings.warn(msg)
2025-08-14T21:17:31.9504871Z     
2025-08-14T21:17:31.9505127Z --- Parse Warning: 44 / 146 ---
2025-08-14T21:17:31.9506420Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564.
2025-08-14T21:17:31.9506722Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9506802Z     
2025-08-14T21:17:31.9507039Z     Takes in a feature and optional module_filter and plots of the desired data.
2025-08-14T21:17:31.9507131Z     
2025-08-14T21:17:31.9507405Z     For per channel features, it averages the value across the channels and plots a point
2025-08-14T21:17:31.9507672Z     per module. The reason for this is that for models with hundreds of channels, it can
2025-08-14T21:17:31.9507947Z     be hard to differentiate one channel line from another, and so the point of generating
2025-08-14T21:17:31.9508216Z     a single average point per module is to give a sense of general trends that encourage
2025-08-14T21:17:31.9508327Z     further deep dives.
2025-08-14T21:17:31.9508406Z     
2025-08-14T21:17:31.9508485Z     Note:
2025-08-14T21:17:31.9508771Z         Only features in the report that have tensor value data are plottable by this class
2025-08-14T21:17:31.9508938Z         When the tensor information is plotted, it will plot:
2025-08-14T21:17:31.9509270Z             idx as the x val, feature value as the y_val
2025-08-14T21:17:31.9509449Z         When the channel information is plotted, it will plot:
2025-08-14T21:17:31.9509718Z             the first idx of each module as the x val, feature value as the y_val [for each channel]
2025-08-14T21:17:31.9509946Z             The reason for this is that we want to be able to compare values across the
2025-08-14T21:17:31.9510189Z             channels for same layer, and it will be hard if values are staggered by idx
2025-08-14T21:17:31.9510358Z             This means each module is represented by only 1 x value
2025-08-14T21:17:31.9510455Z     Args:
2025-08-14T21:17:31.9510678Z         feature_filter (str): Filters the features presented to only those that
2025-08-14T21:17:31.9510787Z             contain this filter substring
2025-08-14T21:17:31.9511055Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:31.9511301Z             Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:31.9511441Z     
2025-08-14T21:17:31.9511553Z     Example Use:
2025-08-14T21:17:31.9511752Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9511914Z         >>> mod_report_visualizer.generate_plot_visualization(
2025-08-14T21:17:31.9512119Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:31.9512201Z         ... )
2025-08-14T21:17:31.9512390Z         >>> # outputs line plot of per_channel_min information for all
2025-08-14T21:17:31.9512575Z         >>> # modules in block1 of model each channel gets it's own line,
2025-08-14T21:17:31.9512749Z         >>> # and it's plotted across the in-order modules on the x-axis
2025-08-14T21:17:31.9512837Z     
2025-08-14T21:17:31.9513088Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9513167Z     
2025-08-14T21:17:31.9513275Z       warnings.warn(msg)
2025-08-14T21:17:31.9513354Z     
2025-08-14T21:17:31.9513557Z --- Parse Warning: 45 / 146 ---
2025-08-14T21:17:31.9514862Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643.
2025-08-14T21:17:31.9515124Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9515211Z     
2025-08-14T21:17:31.9515593Z     Takes in a feature and optional module_filter and plots the histogram of desired data.
2025-08-14T21:17:31.9515705Z     
2025-08-14T21:17:31.9515801Z     Note:
2025-08-14T21:17:31.9516067Z         Only features in the report that have tensor value data can be viewed as a histogram
2025-08-14T21:17:31.9516339Z         If you want to plot a histogram from all the channel values of a specific feature for
2025-08-14T21:17:31.9516583Z             a specific model, make sure to specify both the model and the feature properly
2025-08-14T21:17:31.9516828Z             in the filters and you should be able to see a distribution of the channel data
2025-08-14T21:17:31.9516914Z     
2025-08-14T21:17:31.9516994Z     Args:
2025-08-14T21:17:31.9517256Z         feature_filter (str, optional): Filters the features presented to only those that
2025-08-14T21:17:31.9517378Z             contain this filter substring
2025-08-14T21:17:31.9517543Z             Default = "", results in all the features being printed
2025-08-14T21:17:31.9517802Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-08-14T21:17:31.9518058Z             Default = "", results in all the modules in the reports to be visible in the table
2025-08-14T21:17:31.9518279Z         num_bins (int, optional): The number of bins to create the histogram with
2025-08-14T21:17:31.9518479Z             Default = 10, the values will be split into 10 equal sized bins
2025-08-14T21:17:31.9518554Z     
2025-08-14T21:17:31.9518640Z     Example Use:
2025-08-14T21:17:31.9518747Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9519048Z         >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization(
2025-08-14T21:17:31.9519240Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-08-14T21:17:31.9519335Z         ... )
2025-08-14T21:17:31.9519609Z         # outputs histogram of per_channel_min information for all modules in block1 of model
2025-08-14T21:17:31.9519880Z             information is gathered across all channels for all modules in block 1 for the
2025-08-14T21:17:31.9520102Z             per_channel_min and is displayed in a histogram of equally sized bins
2025-08-14T21:17:31.9520181Z     
2025-08-14T21:17:31.9520443Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9520525Z     
2025-08-14T21:17:31.9520620Z       warnings.warn(msg)
2025-08-14T21:17:31.9520711Z     
2025-08-14T21:17:31.9520896Z --- Parse Warning: 46 / 146 ---
2025-08-14T21:17:31.9521835Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734.
2025-08-14T21:17:31.9522094Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9522478Z     Context manager/function decorator that adds a label to a code block/function when running autograd profiler.
2025-08-14T21:17:31.9522672Z         Label will only appear if CPU activity tracing is enabled.
2025-08-14T21:17:31.9522751Z     
2025-08-14T21:17:31.9522881Z         It is useful when tracing the code profile.
2025-08-14T21:17:31.9522968Z     
2025-08-14T21:17:31.9523049Z         Args:
2025-08-14T21:17:31.9523191Z             name (str): Label assigned to the block of code.
2025-08-14T21:17:31.9523383Z             node_id (int): ID of node, for distributed profiling. Unset in
2025-08-14T21:17:31.9523485Z             non-distributed cases.
2025-08-14T21:17:31.9523576Z     
2025-08-14T21:17:31.9523659Z         Example:
2025-08-14T21:17:31.9523838Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER)
2025-08-14T21:17:31.9523978Z             >>> x = torch.randn((1, 1), requires_grad=True)
2025-08-14T21:17:31.9524136Z             >>> with torch.autograd.profiler.profile() as prof:
2025-08-14T21:17:31.9524225Z             ...     y = x**2
2025-08-14T21:17:31.9524448Z             ...     with torch.autograd.profiler.record_function(
2025-08-14T21:17:31.9524562Z             ...         "label-z"
2025-08-14T21:17:31.9524664Z             ...     ):  # label the block
2025-08-14T21:17:31.9524763Z             ...         z = y**3
2025-08-14T21:17:31.9524852Z             ...     y.backward()
2025-08-14T21:17:31.9524967Z             >>> # xdoctest: +IGNORE_WANT
2025-08-14T21:17:31.9525099Z             >>> # NOTE: some columns were removed for brevity
2025-08-14T21:17:31.9525300Z             >>> print(prof.key_averages().table(sort_by="self_cpu_time_total"))
2025-08-14T21:17:31.9525507Z             -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:31.9525687Z             Name                                 Self CPU total %  CPU time avg     Number of Calls
2025-08-14T21:17:31.9525878Z             -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:31.9526022Z             pow                                  60.77%           47.470us         3
2025-08-14T21:17:31.9526153Z             mul                                  21.73%           25.465us         2
2025-08-14T21:17:31.9526333Z             PowBackward0                         12.03%           121.891us        1
2025-08-14T21:17:31.9526557Z             torch::autograd::AccumulateGrad      2.70%            6.324us          1
2025-08-14T21:17:31.9526696Z             label-z                              2.13%            12.421us         1
2025-08-14T21:17:31.9526909Z             torch::autograd::GraphRoot           0.64%            1.503us          1
2025-08-14T21:17:31.9527095Z             -----------------------------------  ---------------  ---------------  ---------------
2025-08-14T21:17:31.9527214Z             Self CPU time total: 234.344us
2025-08-14T21:17:31.9527313Z             CUDA time total: 0.000us
2025-08-14T21:17:31.9527392Z     
2025-08-14T21:17:31.9527483Z         
2025-08-14T21:17:31.9527736Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9527818Z     
2025-08-14T21:17:31.9527922Z       warnings.warn(msg)
2025-08-14T21:17:31.9527998Z     
2025-08-14T21:17:31.9528184Z --- Parse Warning: 47 / 146 ---
2025-08-14T21:17:31.9529145Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=722.
2025-08-14T21:17:31.9529420Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:31.9529510Z     
2025-08-14T21:17:31.9529774Z     Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh.
2025-08-14T21:17:31.9530042Z     The submesh created consists of the dimensions and the communicators indicated by
2025-08-14T21:17:31.9530144Z     ``mesh_dim_names``
2025-08-14T21:17:31.9530222Z     
2025-08-14T21:17:31.9530311Z     Args:
2025-08-14T21:17:31.9530554Z         mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the
2025-08-14T21:17:31.9530740Z         mesh dimension of the DeviceMesh to create the submesh for.
2025-08-14T21:17:31.9530837Z     Returns:
2025-08-14T21:17:31.9530940Z         A :class:`DeviceMesh` object
2025-08-14T21:17:31.9531018Z     
2025-08-14T21:17:31.9531313Z     The following program runs on each process/rank in an SPMD manner in a world size of 8.
2025-08-14T21:17:31.9531411Z     In the first example:
2025-08-14T21:17:31.9531666Z         Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]).
2025-08-14T21:17:31.9531929Z         Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of  DeviceMesh:([4, 5, 6, 7]).
2025-08-14T21:17:31.9532150Z         Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of  DeviceMesh:([0, 4]).
2025-08-14T21:17:31.9532408Z         Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of  DeviceMesh:([1, 5]).
2025-08-14T21:17:31.9532649Z         Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of  DeviceMesh:([2, 6]).
2025-08-14T21:17:31.9532890Z         Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of  DeviceMesh:([3, 7]).
2025-08-14T21:17:31.9532980Z     
2025-08-14T21:17:31.9533078Z     In the second example:
2025-08-14T21:17:31.9533340Z         Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]).
2025-08-14T21:17:31.9533611Z         Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]).
2025-08-14T21:17:31.9533866Z         Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]).
2025-08-14T21:17:31.9534129Z         Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]).
2025-08-14T21:17:31.9534204Z     
2025-08-14T21:17:31.9534291Z     Example::
2025-08-14T21:17:31.9534382Z     
2025-08-14T21:17:31.9534492Z         >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:31.9534662Z         >>> from torch.distributed.device_mesh import DeviceMesh
2025-08-14T21:17:31.9534754Z         >>>
2025-08-14T21:17:31.9534951Z         >>> # Initialize a 2D device mesh as (2, 4) to represent the topology
2025-08-14T21:17:31.9535088Z         >>> # of cross-host(dim 0), and within-host (dim 1).
2025-08-14T21:17:31.9535346Z         >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-08-14T21:17:31.9535445Z         >>> tp_mesh = mesh_2d["tp"]
2025-08-14T21:17:31.9535556Z         >>> dp_mesh = mesh_2d["dp"]
2025-08-14T21:17:31.9535636Z         >>>
2025-08-14T21:17:31.9535734Z         >>> # Initialize a 3D mesh.
2025-08-14T21:17:31.9536019Z         >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp"))
2025-08-14T21:17:31.9536323Z         >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh.
2025-08-14T21:17:31.9536439Z         >>> dp_cp_mesh = mesh_3d["dp", "cp"]
2025-08-14T21:17:31.9536563Z         >>> cp_dp_mesh = mesh_3d["cp", "dp"]
2025-08-14T21:17:31.9536641Z     
2025-08-14T21:17:31.9537329Z     Original Error: SyntaxError('positional argument follows keyword argument', ('<source_block>', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83))
2025-08-14T21:17:31.9537407Z     
2025-08-14T21:17:31.9537652Z     mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-08-14T21:17:31.9537806Z                                                                                      ^
2025-08-14T21:17:31.9537903Z       warnings.warn(msg)
2025-08-14T21:17:31.9537979Z     
2025-08-14T21:17:31.9538180Z --- Parse Warning: 48 / 146 ---
2025-08-14T21:17:31.9539141Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2706.
2025-08-14T21:17:31.9539418Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9539495Z     
2025-08-14T21:17:31.9539742Z     Send or Receive a batch of tensors asynchronously and return a list of requests.
2025-08-14T21:17:31.9539830Z     
2025-08-14T21:17:31.9540075Z     Process each of the operations in ``p2p_op_list`` and return the corresponding
2025-08-14T21:17:31.9540270Z     requests. NCCL, Gloo, and UCC backend are currently supported.
2025-08-14T21:17:31.9540367Z     
2025-08-14T21:17:31.9540449Z     Args:
2025-08-14T21:17:31.9540675Z         p2p_op_list: A list of point-to-point operations(type of each operator is
2025-08-14T21:17:31.9540916Z             ``torch.distributed.P2POp``). The order of the isend/irecv in the list
2025-08-14T21:17:31.9541126Z             matters and it needs to match with corresponding isend/irecv on the
2025-08-14T21:17:31.9541281Z             remote end.
2025-08-14T21:17:31.9541363Z     
2025-08-14T21:17:31.9541475Z     Returns:
2025-08-14T21:17:31.9541731Z         A list of distributed request objects returned by calling the corresponding
2025-08-14T21:17:31.9541830Z         op in the op_list.
2025-08-14T21:17:31.9541910Z     
2025-08-14T21:17:31.9542011Z     Examples:
2025-08-14T21:17:31.9542117Z         >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:31.9542306Z         >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank
2025-08-14T21:17:31.9542475Z         >>> recv_tensor = torch.randn(2, dtype=torch.float32)
2025-08-14T21:17:31.9542684Z         >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size)
2025-08-14T21:17:31.9542801Z         >>> recv_op = dist.P2POp(
2025-08-14T21:17:31.9542990Z         ...     dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size
2025-08-14T21:17:31.9543073Z         ... )
2025-08-14T21:17:31.9543224Z         >>> reqs = batch_isend_irecv([send_op, recv_op])
2025-08-14T21:17:31.9543323Z         >>> for req in reqs:
2025-08-14T21:17:31.9543418Z         >>>     req.wait()
2025-08-14T21:17:31.9543521Z         >>> recv_tensor
2025-08-14T21:17:31.9543618Z         tensor([2, 3])     # Rank 0
2025-08-14T21:17:31.9543716Z         tensor([0, 1])     # Rank 1
2025-08-14T21:17:31.9543810Z     
2025-08-14T21:17:31.9544052Z     .. note:: Note that when this API is used with the NCCL PG backend, users must set
2025-08-14T21:17:31.9544292Z         the current GPU device with `torch.cuda.set_device`, otherwise it will
2025-08-14T21:17:31.9544403Z         lead to unexpected hang issues.
2025-08-14T21:17:31.9544481Z     
2025-08-14T21:17:31.9544701Z         In addition, if this API is the first collective call in the ``group``
2025-08-14T21:17:31.9544918Z         passed to ``dist.P2POp``, all ranks of the ``group`` must participate in
2025-08-14T21:17:31.9545137Z         this API call; otherwise, the behavior is undefined. If this API call is
2025-08-14T21:17:31.9545370Z         not the first collective call in the ``group``, batched P2P operations
2025-08-14T21:17:31.9545565Z         involving only a subset of ranks of the ``group`` are allowed.
2025-08-14T21:17:31.9545655Z     
2025-08-14T21:17:31.9545903Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9545981Z     
2025-08-14T21:17:31.9546087Z       warnings.warn(msg)
2025-08-14T21:17:31.9546163Z     
2025-08-14T21:17:31.9546349Z --- Parse Warning: 49 / 146 ---
2025-08-14T21:17:31.9547333Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2838.
2025-08-14T21:17:31.9547593Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9547675Z     
2025-08-14T21:17:31.9547955Z     Reduces the tensor data across all machines in a way that all get the final result.
2025-08-14T21:17:31.9548034Z     
2025-08-14T21:17:31.9548274Z     After the call ``tensor`` is going to be bitwise identical in all processes.
2025-08-14T21:17:31.9548348Z     
2025-08-14T21:17:31.9548457Z     Complex tensors are supported.
2025-08-14T21:17:31.9548552Z     
2025-08-14T21:17:31.9548633Z     Args:
2025-08-14T21:17:31.9548833Z         tensor (Tensor): Input and output of the collective. The function
2025-08-14T21:17:31.9548948Z             operates in-place.
2025-08-14T21:17:31.9549063Z         op (optional): One of the values from
2025-08-14T21:17:31.9549183Z             ``torch.distributed.ReduceOp``
2025-08-14T21:17:31.9549393Z             enum.  Specifies an operation used for element-wise reductions.
2025-08-14T21:17:31.9549621Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9549757Z             the default process group will be used.
2025-08-14T21:17:31.9549975Z         async_op (bool, optional): Whether this op should be an async op
2025-08-14T21:17:31.9550080Z     
2025-08-14T21:17:31.9550199Z     Returns:
2025-08-14T21:17:31.9550336Z         Async work handle, if async_op is set to True.
2025-08-14T21:17:31.9550480Z         None, if not async_op or if not part of the group
2025-08-14T21:17:31.9550569Z     
2025-08-14T21:17:31.9550652Z     Examples:
2025-08-14T21:17:31.9550759Z         >>> # xdoctest: +SKIP("no rank")
2025-08-14T21:17:31.9550900Z         >>> # All tensors below are of torch.int64 type.
2025-08-14T21:17:31.9551015Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9551145Z         >>> device = torch.device(f"cuda:{rank}")
2025-08-14T21:17:31.9551371Z         >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-08-14T21:17:31.9551549Z         >>> tensor
2025-08-14T21:17:31.9551678Z         tensor([1, 2], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9551790Z         tensor([3, 4], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9551926Z         >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-08-14T21:17:31.9552025Z         >>> tensor
2025-08-14T21:17:31.9552138Z         tensor([4, 6], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9552250Z         tensor([4, 6], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9552345Z     
2025-08-14T21:17:31.9552480Z         >>> # All tensors below are of torch.cfloat type.
2025-08-14T21:17:31.9552607Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9552708Z         >>> tensor = torch.tensor(
2025-08-14T21:17:31.9552854Z         ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-08-14T21:17:31.9552967Z         ... ) + 2 * rank * (1 + 1j)
2025-08-14T21:17:31.9553046Z         >>> tensor
2025-08-14T21:17:31.9553185Z         tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9553332Z         tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9553461Z         >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-08-14T21:17:31.9553546Z         >>> tensor
2025-08-14T21:17:31.9553694Z         tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9553826Z         tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9553914Z     
2025-08-14T21:17:31.9553991Z     
2025-08-14T21:17:31.9554243Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9554335Z     
2025-08-14T21:17:31.9554428Z       warnings.warn(msg)
2025-08-14T21:17:31.9554505Z     
2025-08-14T21:17:31.9554707Z --- Parse Warning: 50 / 146 ---
2025-08-14T21:17:31.9555689Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3198.
2025-08-14T21:17:31.9555949Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9556040Z     
2025-08-14T21:17:31.9556263Z     Gathers picklable objects from the whole group in a single process.
2025-08-14T21:17:31.9556356Z     
2025-08-14T21:17:31.9556584Z     Similar to :func:`gather`, but Python objects can be passed in. Note that the
2025-08-14T21:17:31.9556730Z     object must be picklable in order to be gathered.
2025-08-14T21:17:31.9556820Z     
2025-08-14T21:17:31.9556900Z     Args:
2025-08-14T21:17:31.9557026Z         obj (Any): Input object. Must be picklable.
2025-08-14T21:17:31.9557245Z         object_gather_list (list[Any]): Output list. On the ``dst`` rank, it
2025-08-14T21:17:31.9557432Z             should be correctly sized as the size of the group for this
2025-08-14T21:17:31.9557645Z             collective and will contain the output. Must be ``None`` on non-dst
2025-08-14T21:17:31.9557762Z             ranks. (default is ``None``)
2025-08-14T21:17:31.9558083Z         dst (int, optional): Destination rank on global process group (regardless of ``group`` argument).
2025-08-14T21:17:31.9558314Z             (If both ``dst`` and ``group_dst`` are None, default is global rank 0)
2025-08-14T21:17:31.9558569Z         group: (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9558781Z             the default process group will be used. Default is ``None``.
2025-08-14T21:17:31.9559134Z         group_dst (int, optional): Destination rank on ``group``.  Invalid to specify both ``dst`` and ``group_dst``
2025-08-14T21:17:31.9559216Z     
2025-08-14T21:17:31.9559295Z     Returns:
2025-08-14T21:17:31.9559484Z         None. On the ``dst`` rank, ``object_gather_list`` will contain the
2025-08-14T21:17:31.9559590Z         output of the collective.
2025-08-14T21:17:31.9559677Z     
2025-08-14T21:17:31.9559886Z     .. note:: Note that this API differs slightly from the gather collective
2025-08-14T21:17:31.9560099Z         since it does not provide an async_op handle and thus will be a blocking
2025-08-14T21:17:31.9560190Z         call.
2025-08-14T21:17:31.9560270Z     
2025-08-14T21:17:31.9560499Z     .. note:: For NCCL-based processed groups, internal tensor representations
2025-08-14T21:17:31.9560725Z         of objects must be moved to the GPU device before communication takes
2025-08-14T21:17:31.9560868Z         place. In this case, the device used is given by
2025-08-14T21:17:31.9561099Z         ``torch.cuda.current_device()`` and it is the user's responsibility to
2025-08-14T21:17:31.9561301Z         ensure that this is set so that each rank has an individual GPU, via
2025-08-14T21:17:31.9561405Z         ``torch.cuda.set_device()``.
2025-08-14T21:17:31.9561496Z     
2025-08-14T21:17:31.9561582Z     .. warning::
2025-08-14T21:17:31.9561822Z         Object collectives have a number of serious performance and scalability
2025-08-14T21:17:31.9562007Z         limitations.  See :ref:`object_collectives` for details.
2025-08-14T21:17:31.9562084Z     
2025-08-14T21:17:31.9562170Z     .. warning::
2025-08-14T21:17:31.9562377Z         :func:`gather_object` uses ``pickle`` module implicitly, which is
2025-08-14T21:17:31.9562594Z         known to be insecure. It is possible to construct malicious pickle data
2025-08-14T21:17:31.9562826Z         which will execute arbitrary code during unpickling. Only call this
2025-08-14T21:17:31.9562930Z         function with data you trust.
2025-08-14T21:17:31.9563008Z     
2025-08-14T21:17:31.9563105Z     .. warning::
2025-08-14T21:17:31.9563317Z         Calling :func:`gather_object` with GPU tensors is not well supported
2025-08-14T21:17:31.9563536Z         and inefficient as it incurs GPU -> CPU transfer since tensors would be
2025-08-14T21:17:31.9563739Z         pickled. Please consider using :func:`gather` instead.
2025-08-14T21:17:31.9563819Z     
2025-08-14T21:17:31.9563905Z     Example::
2025-08-14T21:17:31.9564055Z         >>> # xdoctest: +SKIP("need process group init")
2025-08-14T21:17:31.9564232Z         >>> # Note: Process group initialization omitted on each rank.
2025-08-14T21:17:31.9564360Z         >>> import torch.distributed as dist
2025-08-14T21:17:31.9564466Z         >>> # Assumes world_size of 3.
2025-08-14T21:17:31.9564639Z         >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object
2025-08-14T21:17:31.9564772Z         >>> output = [None for _ in gather_objects]
2025-08-14T21:17:31.9564868Z         >>> dist.gather_object(
2025-08-14T21:17:31.9564986Z         ...     gather_objects[dist.get_rank()],
2025-08-14T21:17:31.9565126Z         ...     output if dist.get_rank() == 0 else None,
2025-08-14T21:17:31.9565211Z         ...     dst=0
2025-08-14T21:17:31.9565290Z         ... )
2025-08-14T21:17:31.9565387Z         >>> # On rank 0
2025-08-14T21:17:31.9565468Z         >>> output
2025-08-14T21:17:31.9565569Z         ['foo', 12, {1: 2}]
2025-08-14T21:17:31.9565648Z     
2025-08-14T21:17:31.9565902Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9565990Z     
2025-08-14T21:17:31.9566084Z       warnings.warn(msg)
2025-08-14T21:17:31.9566163Z     
2025-08-14T21:17:31.9566362Z --- Parse Warning: 51 / 146 ---
2025-08-14T21:17:31.9567347Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3794.
2025-08-14T21:17:31.9567649Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9567733Z     
2025-08-14T21:17:31.9567873Z     Gathers tensors from the whole group in a list.
2025-08-14T21:17:31.9567965Z     
2025-08-14T21:17:31.9568107Z     Complex and uneven sized tensors are supported.
2025-08-14T21:17:31.9568188Z     
2025-08-14T21:17:31.9568285Z     Args:
2025-08-14T21:17:31.9568465Z         tensor_list (list[Tensor]): Output list. It should contain
2025-08-14T21:17:31.9568681Z             correctly-sized tensors to be used for output of the collective.
2025-08-14T21:17:31.9568812Z             Uneven sized tensors are supported.
2025-08-14T21:17:31.9569001Z         tensor (Tensor): Tensor to be broadcast from current process.
2025-08-14T21:17:31.9569232Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9569367Z             the default process group will be used.
2025-08-14T21:17:31.9569562Z         async_op (bool, optional): Whether this op should be an async op
2025-08-14T21:17:31.9569650Z     
2025-08-14T21:17:31.9569734Z     Returns:
2025-08-14T21:17:31.9569872Z         Async work handle, if async_op is set to True.
2025-08-14T21:17:31.9570028Z         None, if not async_op or if not part of the group
2025-08-14T21:17:31.9570109Z     
2025-08-14T21:17:31.9570193Z     Examples:
2025-08-14T21:17:31.9570339Z         >>> # xdoctest: +SKIP("need process group init")
2025-08-14T21:17:31.9570470Z         >>> # All tensors below are of torch.int64 dtype.
2025-08-14T21:17:31.9570599Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9570717Z         >>> device = torch.device(f"cuda:{rank}")
2025-08-14T21:17:31.9570811Z         >>> tensor_list = [
2025-08-14T21:17:31.9571032Z         ...     torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2)
2025-08-14T21:17:31.9571115Z         ... ]
2025-08-14T21:17:31.9571203Z         >>> tensor_list
2025-08-14T21:17:31.9571415Z         [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0
2025-08-14T21:17:31.9571607Z         [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1
2025-08-14T21:17:31.9571842Z         >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-08-14T21:17:31.9571938Z         >>> tensor
2025-08-14T21:17:31.9572079Z         tensor([1, 2], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9572192Z         tensor([3, 4], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9572318Z         >>> dist.all_gather(tensor_list, tensor)
2025-08-14T21:17:31.9572407Z         >>> tensor_list
2025-08-14T21:17:31.9572600Z         [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0
2025-08-14T21:17:31.9572806Z         [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1
2025-08-14T21:17:31.9572885Z     
2025-08-14T21:17:31.9573035Z         >>> # All tensors below are of torch.cfloat dtype.
2025-08-14T21:17:31.9573150Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9573245Z         >>> tensor_list = [
2025-08-14T21:17:31.9573467Z         ...     torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2)
2025-08-14T21:17:31.9573548Z         ... ]
2025-08-14T21:17:31.9573638Z         >>> tensor_list
2025-08-14T21:17:31.9573896Z         [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0
2025-08-14T21:17:31.9574131Z         [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1
2025-08-14T21:17:31.9574234Z         >>> tensor = torch.tensor(
2025-08-14T21:17:31.9574390Z         ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-08-14T21:17:31.9574512Z         ... ) + 2 * rank * (1 + 1j)
2025-08-14T21:17:31.9574630Z         >>> tensor
2025-08-14T21:17:31.9574807Z         tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-08-14T21:17:31.9574941Z         tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-08-14T21:17:31.9575067Z         >>> dist.all_gather(tensor_list, tensor)
2025-08-14T21:17:31.9575156Z         >>> tensor_list
2025-08-14T21:17:31.9575393Z         [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0
2025-08-14T21:17:31.9575647Z         [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1
2025-08-14T21:17:31.9575724Z     
2025-08-14T21:17:31.9575801Z     
2025-08-14T21:17:31.9576065Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9576144Z     
2025-08-14T21:17:31.9576251Z       warnings.warn(msg)
2025-08-14T21:17:31.9576331Z     
2025-08-14T21:17:31.9576521Z --- Parse Warning: 52 / 146 ---
2025-08-14T21:17:31.9577617Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4500.
2025-08-14T21:17:31.9577882Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9577962Z     
2025-08-14T21:17:31.9578225Z     Split input tensor and then scatter the split list to all processes in a group.
2025-08-14T21:17:31.9578304Z     
2025-08-14T21:17:31.9578579Z     Later the received tensors are concatenated from all the processes in the group
2025-08-14T21:17:31.9578695Z     and returned as a single output tensor.
2025-08-14T21:17:31.9578774Z     
2025-08-14T21:17:31.9578893Z     Complex tensors are supported.
2025-08-14T21:17:31.9578970Z     
2025-08-14T21:17:31.9579051Z     Args:
2025-08-14T21:17:31.9579225Z         output (Tensor): Gathered concatenated output tensor.
2025-08-14T21:17:31.9579353Z         input (Tensor): Input tensor to scatter.
2025-08-14T21:17:31.9579575Z         output_split_sizes: (list[Int], optional): Output split sizes for dim 0
2025-08-14T21:17:31.9579791Z             if specified None or empty, dim 0 of ``output`` tensor must divide
2025-08-14T21:17:31.9579897Z             equally by ``world_size``.
2025-08-14T21:17:31.9580120Z         input_split_sizes: (list[Int], optional): Input split sizes for dim 0
2025-08-14T21:17:31.9580314Z             if specified None or empty, dim 0 of ``input`` tensor must divide
2025-08-14T21:17:31.9580451Z             equally by ``world_size``.
2025-08-14T21:17:31.9580689Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9580812Z             the default process group will be used.
2025-08-14T21:17:31.9581007Z         async_op (bool, optional): Whether this op should be an async op.
2025-08-14T21:17:31.9581096Z     
2025-08-14T21:17:31.9581178Z     Returns:
2025-08-14T21:17:31.9581319Z         Async work handle, if async_op is set to True.
2025-08-14T21:17:31.9581470Z         None, if not async_op or if not part of the group.
2025-08-14T21:17:31.9581546Z     
2025-08-14T21:17:31.9581655Z     .. warning::
2025-08-14T21:17:31.9581821Z         `all_to_all_single` is experimental and subject to change.
2025-08-14T21:17:31.9581897Z     
2025-08-14T21:17:31.9581990Z     Examples:
2025-08-14T21:17:31.9582104Z         >>> # xdoctest: +SKIP("Undefined rank")
2025-08-14T21:17:31.9582216Z         >>> input = torch.arange(4) + rank * 4
2025-08-14T21:17:31.9582308Z         >>> input
2025-08-14T21:17:31.9582411Z         tensor([0, 1, 2, 3])     # Rank 0
2025-08-14T21:17:31.9582509Z         tensor([4, 5, 6, 7])     # Rank 1
2025-08-14T21:17:31.9582613Z         tensor([8, 9, 10, 11])   # Rank 2
2025-08-14T21:17:31.9582704Z         tensor([12, 13, 14, 15]) # Rank 3
2025-08-14T21:17:31.9582853Z         >>> output = torch.empty([4], dtype=torch.int64)
2025-08-14T21:17:31.9583000Z         >>> dist.all_to_all_single(output, input)
2025-08-14T21:17:31.9583109Z         >>> output
2025-08-14T21:17:31.9583238Z         tensor([0, 4, 8, 12])    # Rank 0
2025-08-14T21:17:31.9583329Z         tensor([1, 5, 9, 13])    # Rank 1
2025-08-14T21:17:31.9583422Z         tensor([2, 6, 10, 14])   # Rank 2
2025-08-14T21:17:31.9583520Z         tensor([3, 7, 11, 15])   # Rank 3
2025-08-14T21:17:31.9583596Z     
2025-08-14T21:17:31.9583753Z         >>> # Essentially, it is similar to following operation:
2025-08-14T21:17:31.9583898Z         >>> scatter_list = list(input.chunk(world_size))
2025-08-14T21:17:31.9584035Z         >>> gather_list = list(output.chunk(world_size))
2025-08-14T21:17:31.9584138Z         >>> for i in range(world_size):
2025-08-14T21:17:31.9584373Z         >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i)
2025-08-14T21:17:31.9584449Z     
2025-08-14T21:17:31.9584580Z         >>> # Another example with uneven split
2025-08-14T21:17:31.9584660Z         >>> input
2025-08-14T21:17:31.9584815Z         tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-08-14T21:17:31.9584986Z         tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-08-14T21:17:31.9585135Z         tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-08-14T21:17:31.9585286Z         tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-08-14T21:17:31.9585388Z         >>> input_splits
2025-08-14T21:17:31.9585504Z         [2, 2, 1, 1]                                                     # Rank 0
2025-08-14T21:17:31.9585635Z         [3, 2, 2, 2]                                                     # Rank 1
2025-08-14T21:17:31.9585749Z         [2, 1, 1, 1]                                                     # Rank 2
2025-08-14T21:17:31.9585864Z         [2, 2, 2, 1]                                                     # Rank 3
2025-08-14T21:17:31.9585969Z         >>> output_splits
2025-08-14T21:17:31.9586084Z         [2, 3, 2, 2]                                                     # Rank 0
2025-08-14T21:17:31.9586202Z         [2, 2, 1, 2]                                                     # Rank 1
2025-08-14T21:17:31.9586328Z         [1, 2, 1, 2]                                                     # Rank 2
2025-08-14T21:17:31.9586443Z         [1, 2, 1, 1]                                                     # Rank 3
2025-08-14T21:17:31.9586546Z         >>> output = ...
2025-08-14T21:17:31.9586748Z         >>> dist.all_to_all_single(output, input, output_splits, input_splits)
2025-08-14T21:17:31.9586832Z         >>> output
2025-08-14T21:17:31.9587022Z         tensor([ 0,  1, 10, 11, 12, 20, 21, 30, 31])                     # Rank 0
2025-08-14T21:17:31.9587173Z         tensor([ 2,  3, 13, 14, 22, 32, 33])                             # Rank 1
2025-08-14T21:17:31.9587324Z         tensor([ 4, 15, 16, 23, 34, 35])                                 # Rank 2
2025-08-14T21:17:31.9587484Z         tensor([ 5, 17, 18, 24, 36])                                     # Rank 3
2025-08-14T21:17:31.9587565Z     
2025-08-14T21:17:31.9587656Z     
2025-08-14T21:17:31.9587814Z         >>> # Another example with tensors of torch.cfloat type.
2025-08-14T21:17:31.9587914Z         >>> input = torch.tensor(
2025-08-14T21:17:31.9588061Z         ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-08-14T21:17:31.9588153Z         ... ) + 4 * rank * (1 + 1j)
2025-08-14T21:17:31.9588234Z         >>> input
2025-08-14T21:17:31.9588415Z         tensor([1+1j, 2+2j, 3+3j, 4+4j])                                # Rank 0
2025-08-14T21:17:31.9588581Z         tensor([5+5j, 6+6j, 7+7j, 8+8j])                                # Rank 1
2025-08-14T21:17:31.9588757Z         tensor([9+9j, 10+10j, 11+11j, 12+12j])                          # Rank 2
2025-08-14T21:17:31.9588944Z         tensor([13+13j, 14+14j, 15+15j, 16+16j])                        # Rank 3
2025-08-14T21:17:31.9589081Z         >>> output = torch.empty([4], dtype=torch.int64)
2025-08-14T21:17:31.9589242Z         >>> dist.all_to_all_single(output, input)
2025-08-14T21:17:31.9589408Z         >>> output
2025-08-14T21:17:31.9589575Z         tensor([1+1j, 5+5j, 9+9j, 13+13j])                              # Rank 0
2025-08-14T21:17:31.9589754Z         tensor([2+2j, 6+6j, 10+10j, 14+14j])                            # Rank 1
2025-08-14T21:17:31.9589922Z         tensor([3+3j, 7+7j, 11+11j, 15+15j])                            # Rank 2
2025-08-14T21:17:31.9590093Z         tensor([4+4j, 8+8j, 12+12j, 16+16j])                            # Rank 3
2025-08-14T21:17:31.9590184Z     
2025-08-14T21:17:31.9590435Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9590527Z     
2025-08-14T21:17:31.9590620Z       warnings.warn(msg)
2025-08-14T21:17:31.9590697Z     
2025-08-14T21:17:31.9590909Z --- Parse Warning: 53 / 146 ---
2025-08-14T21:17:31.9591919Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4642.
2025-08-14T21:17:31.9593338Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9593426Z     
2025-08-14T21:17:31.9593787Z     Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list.
2025-08-14T21:17:31.9593874Z     
2025-08-14T21:17:31.9593981Z     Complex tensors are supported.
2025-08-14T21:17:31.9594057Z     
2025-08-14T21:17:31.9594145Z     Args:
2025-08-14T21:17:31.9594364Z         output_tensor_list (list[Tensor]): List of tensors to be gathered one
2025-08-14T21:17:31.9594450Z             per rank.
2025-08-14T21:17:31.9594684Z         input_tensor_list (list[Tensor]): List of tensors to scatter one per rank.
2025-08-14T21:17:31.9594913Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9595048Z             the default process group will be used.
2025-08-14T21:17:31.9595248Z         async_op (bool, optional): Whether this op should be an async op.
2025-08-14T21:17:31.9595326Z     
2025-08-14T21:17:31.9595419Z     Returns:
2025-08-14T21:17:31.9595559Z         Async work handle, if async_op is set to True.
2025-08-14T21:17:31.9595702Z         None, if not async_op or if not part of the group.
2025-08-14T21:17:31.9595787Z     
2025-08-14T21:17:31.9595878Z     .. warning::
2025-08-14T21:17:31.9596024Z         `all_to_all` is experimental and subject to change.
2025-08-14T21:17:31.9596110Z     
2025-08-14T21:17:31.9596195Z     Examples:
2025-08-14T21:17:31.9596358Z         >>> # xdoctest: +SKIP("Undefined rank")
2025-08-14T21:17:31.9596479Z         >>> input = torch.arange(4) + rank * 4
2025-08-14T21:17:31.9596588Z         >>> input = list(input.chunk(4))
2025-08-14T21:17:31.9596684Z         >>> input
2025-08-14T21:17:31.9596851Z         [tensor([0]), tensor([1]), tensor([2]), tensor([3])]     # Rank 0
2025-08-14T21:17:31.9597020Z         [tensor([4]), tensor([5]), tensor([6]), tensor([7])]     # Rank 1
2025-08-14T21:17:31.9597194Z         [tensor([8]), tensor([9]), tensor([10]), tensor([11])]   # Rank 2
2025-08-14T21:17:31.9597357Z         [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3
2025-08-14T21:17:31.9597537Z         >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-08-14T21:17:31.9597656Z         >>> dist.all_to_all(output, input)
2025-08-14T21:17:31.9597736Z         >>> output
2025-08-14T21:17:31.9597898Z         [tensor([0]), tensor([4]), tensor([8]), tensor([12])]    # Rank 0
2025-08-14T21:17:31.9598070Z         [tensor([1]), tensor([5]), tensor([9]), tensor([13])]    # Rank 1
2025-08-14T21:17:31.9598227Z         [tensor([2]), tensor([6]), tensor([10]), tensor([14])]   # Rank 2
2025-08-14T21:17:31.9598392Z         [tensor([3]), tensor([7]), tensor([11]), tensor([15])]   # Rank 3
2025-08-14T21:17:31.9598470Z     
2025-08-14T21:17:31.9598663Z         >>> # Essentially, it is similar to following operation:
2025-08-14T21:17:31.9598796Z         >>> scatter_list = input
2025-08-14T21:17:31.9598918Z         >>> gather_list = output
2025-08-14T21:17:31.9599024Z         >>> for i in range(world_size):
2025-08-14T21:17:31.9599253Z         >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i)
2025-08-14T21:17:31.9599333Z     
2025-08-14T21:17:31.9599426Z         >>> input
2025-08-14T21:17:31.9599573Z         tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-08-14T21:17:31.9599731Z         tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-08-14T21:17:31.9599891Z         tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-08-14T21:17:31.9600042Z         tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-08-14T21:17:31.9600134Z         >>> input_splits
2025-08-14T21:17:31.9600261Z         [2, 2, 1, 1]                                                     # Rank 0
2025-08-14T21:17:31.9600381Z         [3, 2, 2, 2]                                                     # Rank 1
2025-08-14T21:17:31.9600509Z         [2, 1, 1, 1]                                                     # Rank 2
2025-08-14T21:17:31.9600623Z         [2, 2, 2, 1]                                                     # Rank 3
2025-08-14T21:17:31.9600719Z         >>> output_splits
2025-08-14T21:17:31.9600850Z         [2, 3, 2, 2]                                                     # Rank 0
2025-08-14T21:17:31.9600967Z         [2, 2, 1, 2]                                                     # Rank 1
2025-08-14T21:17:31.9601086Z         [1, 2, 1, 2]                                                     # Rank 2
2025-08-14T21:17:31.9601218Z         [1, 2, 1, 1]                                                     # Rank 3
2025-08-14T21:17:31.9601346Z         >>> input = list(input.split(input_splits))
2025-08-14T21:17:31.9601444Z         >>> input
2025-08-14T21:17:31.9601652Z         [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])]                   # Rank 0
2025-08-14T21:17:31.9601857Z         [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1
2025-08-14T21:17:31.9602072Z         [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])]                 # Rank 2
2025-08-14T21:17:31.9602271Z         [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])]         # Rank 3
2025-08-14T21:17:31.9602366Z         >>> output = ...
2025-08-14T21:17:31.9602494Z         >>> dist.all_to_all(output, input)
2025-08-14T21:17:31.9602579Z         >>> output
2025-08-14T21:17:31.9602819Z         [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])]   # Rank 0
2025-08-14T21:17:31.9603020Z         [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])]           # Rank 1
2025-08-14T21:17:31.9603218Z         [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])]              # Rank 2
2025-08-14T21:17:31.9603438Z         [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])]                  # Rank 3
2025-08-14T21:17:31.9603523Z     
2025-08-14T21:17:31.9603685Z         >>> # Another example with tensors of torch.cfloat type.
2025-08-14T21:17:31.9603804Z         >>> input = torch.tensor(
2025-08-14T21:17:31.9603942Z         ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-08-14T21:17:31.9604049Z         ... ) + 4 * rank * (1 + 1j)
2025-08-14T21:17:31.9604155Z         >>> input = list(input.chunk(4))
2025-08-14T21:17:31.9604239Z         >>> input
2025-08-14T21:17:31.9604466Z         [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])]            # Rank 0
2025-08-14T21:17:31.9604675Z         [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])]            # Rank 1
2025-08-14T21:17:31.9604891Z         [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])]      # Rank 2
2025-08-14T21:17:31.9605120Z         [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])]    # Rank 3
2025-08-14T21:17:31.9605366Z         >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-08-14T21:17:31.9605516Z         >>> dist.all_to_all(output, input)
2025-08-14T21:17:31.9605599Z         >>> output
2025-08-14T21:17:31.9605806Z         [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])]          # Rank 0
2025-08-14T21:17:31.9606024Z         [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])]        # Rank 1
2025-08-14T21:17:31.9606228Z         [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])]        # Rank 2
2025-08-14T21:17:31.9606433Z         [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])]        # Rank 3
2025-08-14T21:17:31.9606525Z     
2025-08-14T21:17:31.9606602Z     
2025-08-14T21:17:31.9606856Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9606945Z     
2025-08-14T21:17:31.9607040Z       warnings.warn(msg)
2025-08-14T21:17:31.9607128Z     
2025-08-14T21:17:31.9607342Z --- Parse Warning: 54 / 146 ---
2025-08-14T21:17:31.9608196Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2.
2025-08-14T21:17:31.9608470Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9608549Z     
2025-08-14T21:17:31.9608666Z     Module ``torch.distributed.launch``.
2025-08-14T21:17:31.9608760Z     
2025-08-14T21:17:31.9609179Z     ``torch.distributed.launch`` is a module that spawns up multiple distributed
2025-08-14T21:17:31.9609334Z     training processes on each of the training nodes.
2025-08-14T21:17:31.9609425Z     
2025-08-14T21:17:31.9609515Z     .. warning::
2025-08-14T21:17:31.9609606Z     
2025-08-14T21:17:31.9609859Z         This module is going to be deprecated in favor of :ref:`torchrun <launcher-api>`.
2025-08-14T21:17:31.9609937Z     
2025-08-14T21:17:31.9610194Z     The utility can be used for single-node distributed training, in which one or
2025-08-14T21:17:31.9610432Z     more processes per node will be spawned. The utility can be used for either
2025-08-14T21:17:31.9610648Z     CPU training or GPU training. If the utility is used for GPU training,
2025-08-14T21:17:31.9610913Z     each distributed process will be operating on a single GPU. This can achieve
2025-08-14T21:17:31.9611146Z     well-improved single-node training performance. It can also be used in
2025-08-14T21:17:31.9611498Z     multi-node distributed training, by spawning up multiple processes on each node
2025-08-14T21:17:31.9611731Z     for well-improved multi-node distributed training performance as well.
2025-08-14T21:17:31.9611961Z     This will especially be beneficial for systems with multiple Infiniband
2025-08-14T21:17:31.9612228Z     interfaces that have direct-GPU support, since all of them can be utilized for
2025-08-14T21:17:31.9612349Z     aggregated communication bandwidth.
2025-08-14T21:17:31.9612433Z     
2025-08-14T21:17:31.9612683Z     In both cases of single-node distributed training or multi-node distributed
2025-08-14T21:17:31.9612920Z     training, this utility will launch the given number of processes per node
2025-08-14T21:17:31.9613162Z     (``--nproc-per-node``). If used for GPU training, this number needs to be less
2025-08-14T21:17:31.9613379Z     or equal to the number of GPUs on the current system (``nproc_per_node``),
2025-08-14T21:17:31.9613580Z     and each process will be operating on a single GPU from *GPU 0 to
2025-08-14T21:17:31.9613702Z     GPU (nproc_per_node - 1)*.
2025-08-14T21:17:31.9613782Z     
2025-08-14T21:17:31.9613882Z     **How to use this module:**
2025-08-14T21:17:31.9613972Z     
2025-08-14T21:17:31.9614123Z     1. Single-Node multi-process distributed training
2025-08-14T21:17:31.9614201Z     
2025-08-14T21:17:31.9614298Z     ::
2025-08-14T21:17:31.9614378Z     
2025-08-14T21:17:31.9614654Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:31.9614910Z                    YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
2025-08-14T21:17:31.9615072Z                    arguments of your training script)
2025-08-14T21:17:31.9615166Z     
2025-08-14T21:17:31.9615376Z     2. Multi-Node multi-process distributed training: (e.g. two nodes)
2025-08-14T21:17:31.9615457Z     
2025-08-14T21:17:31.9615551Z     
2025-08-14T21:17:31.9615694Z     Node 1: *(IP: 192.168.1.1, and has a free port: 1234)*
2025-08-14T21:17:31.9615775Z     
2025-08-14T21:17:31.9615873Z     ::
2025-08-14T21:17:31.9615953Z     
2025-08-14T21:17:31.9616188Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:31.9616360Z                    --nnodes=2 --node-rank=0 --master-addr="192.168.1.1"
2025-08-14T21:17:31.9616567Z                    --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-08-14T21:17:31.9616733Z                    and all other arguments of your training script)
2025-08-14T21:17:31.9616814Z     
2025-08-14T21:17:31.9616899Z     Node 2:
2025-08-14T21:17:31.9616989Z     
2025-08-14T21:17:31.9617072Z     ::
2025-08-14T21:17:31.9617152Z     
2025-08-14T21:17:31.9617399Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-08-14T21:17:31.9617552Z                    --nnodes=2 --node-rank=1 --master-addr="192.168.1.1"
2025-08-14T21:17:31.9617757Z                    --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-08-14T21:17:31.9617921Z                    and all other arguments of your training script)
2025-08-14T21:17:31.9618004Z     
2025-08-14T21:17:31.9618177Z     3. To look up what optional arguments this module offers:
2025-08-14T21:17:31.9618255Z     
2025-08-14T21:17:31.9618336Z     ::
2025-08-14T21:17:31.9618426Z     
2025-08-14T21:17:31.9618562Z         python -m torch.distributed.launch --help
2025-08-14T21:17:31.9618640Z     
2025-08-14T21:17:31.9618731Z     
2025-08-14T21:17:31.9618832Z     **Important Notices:**
2025-08-14T21:17:31.9618913Z     
2025-08-14T21:17:31.9619115Z     1. This utility and multi-process distributed (single-node or
2025-08-14T21:17:31.9619361Z     multi-node) GPU training currently only achieves the best performance using
2025-08-14T21:17:31.9619611Z     the NCCL distributed backend. Thus NCCL backend is the recommended backend to
2025-08-14T21:17:31.9619720Z     use for GPU training.
2025-08-14T21:17:31.9619798Z     
2025-08-14T21:17:31.9620023Z     2. In your training program, you must parse the command-line argument:
2025-08-14T21:17:31.9620281Z     ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module.
2025-08-14T21:17:31.9620507Z     If your training program uses GPUs, you should ensure that your code only
2025-08-14T21:17:31.9620708Z     runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by:
2025-08-14T21:17:31.9620787Z     
2025-08-14T21:17:31.9620894Z     Parsing the local_rank argument
2025-08-14T21:17:31.9620985Z     
2025-08-14T21:17:31.9621072Z     ::
2025-08-14T21:17:31.9621150Z     
2025-08-14T21:17:31.9621261Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9621355Z         >>> import argparse
2025-08-14T21:17:31.9621481Z         >>> parser = argparse.ArgumentParser()
2025-08-14T21:17:31.9621687Z         >>> parser.add_argument("--local-rank", "--local_rank", type=int)
2025-08-14T21:17:31.9621795Z         >>> args = parser.parse_args()
2025-08-14T21:17:31.9621884Z     
2025-08-14T21:17:31.9622006Z     Set your device to local rank using either
2025-08-14T21:17:31.9622084Z     
2025-08-14T21:17:31.9622176Z     ::
2025-08-14T21:17:31.9622255Z     
2025-08-14T21:17:31.9622451Z         >>> torch.cuda.set_device(args.local_rank)  # before your code runs
2025-08-14T21:17:31.9622540Z     
2025-08-14T21:17:31.9622620Z     or
2025-08-14T21:17:31.9622698Z     
2025-08-14T21:17:31.9622788Z     ::
2025-08-14T21:17:31.9622868Z     
2025-08-14T21:17:31.9622999Z         >>> with torch.cuda.device(args.local_rank):
2025-08-14T21:17:31.9623136Z         >>>    # your code to run
2025-08-14T21:17:31.9623250Z         >>>    ...
2025-08-14T21:17:31.9623354Z     
2025-08-14T21:17:31.9623468Z     .. versionchanged:: 2.0.0
2025-08-14T21:17:31.9623545Z     
2025-08-14T21:17:31.9623803Z         The launcher will passes the ``--local-rank=<rank>`` argument to your script.
2025-08-14T21:17:31.9624039Z         From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the
2025-08-14T21:17:31.9624181Z         previously used underscored ``--local_rank``.
2025-08-14T21:17:31.9624272Z     
2025-08-14T21:17:31.9624512Z         For backward compatibility, it may be necessary for users to handle both
2025-08-14T21:17:31.9624779Z         cases in their argument parsing code. This means including both ``"--local-rank"``
2025-08-14T21:17:31.9625005Z         and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is
2025-08-14T21:17:31.9625256Z         provided, the launcher will trigger an error: "error: unrecognized arguments:
2025-08-14T21:17:31.9625503Z         --local-rank=<rank>". For training code that only supports PyTorch 2.0.0+,
2025-08-14T21:17:31.9625654Z         including ``"--local-rank"`` should be sufficient.
2025-08-14T21:17:31.9625735Z     
2025-08-14T21:17:31.9625983Z     3. In your training program, you are supposed to call the following function
2025-08-14T21:17:31.9626220Z     at the beginning to start the distributed backend. It is strongly recommended
2025-08-14T21:17:31.9626441Z     that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work,
2025-08-14T21:17:31.9626647Z     but ``env://`` is the one that is officially supported by this module.
2025-08-14T21:17:31.9626726Z     
2025-08-14T21:17:31.9626825Z     ::
2025-08-14T21:17:31.9626903Z     
2025-08-14T21:17:31.9627106Z         >>> torch.distributed.init_process_group(backend='YOUR BACKEND',
2025-08-14T21:17:31.9627259Z         >>>                                      init_method='env://')
2025-08-14T21:17:31.9627338Z     
2025-08-14T21:17:31.9627574Z     4. In your training program, you can either use regular distributed functions
2025-08-14T21:17:31.9627825Z     or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your
2025-08-14T21:17:31.9628030Z     training program uses GPUs for training and you would like to use
2025-08-14T21:17:31.9628218Z     :func:`torch.nn.parallel.DistributedDataParallel` module,
2025-08-14T21:17:31.9628336Z     here is how to configure it.
2025-08-14T21:17:31.9628426Z     
2025-08-14T21:17:31.9628519Z     ::
2025-08-14T21:17:31.9628598Z     
2025-08-14T21:17:31.9628818Z         >>> model = torch.nn.parallel.DistributedDataParallel(model,
2025-08-14T21:17:31.9628967Z         >>>                                                   device_ids=[args.local_rank],
2025-08-14T21:17:31.9629106Z         >>>                                                   output_device=args.local_rank)
2025-08-14T21:17:31.9629185Z     
2025-08-14T21:17:31.9629443Z     Please ensure that ``device_ids`` argument is set to be the only GPU device id
2025-08-14T21:17:31.9629679Z     that your code will be operating on. This is generally the local rank of the
2025-08-14T21:17:31.9629917Z     process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``,
2025-08-14T21:17:31.9630148Z     and ``output_device`` needs to be ``args.local_rank`` in order to use this
2025-08-14T21:17:31.9630231Z     utility
2025-08-14T21:17:31.9630322Z     
2025-08-14T21:17:31.9630562Z     5. Another way to pass ``local_rank`` to the subprocesses via environment variable
2025-08-14T21:17:31.9630780Z     ``LOCAL_RANK``. This behavior is enabled when you launch the script with
2025-08-14T21:17:31.9631007Z     ``--use-env=True``. You must adjust the subprocess example above to replace
2025-08-14T21:17:31.9631202Z     ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher
2025-08-14T21:17:31.9631374Z     will not pass ``--local-rank`` when you specify this flag.
2025-08-14T21:17:31.9631559Z     
2025-08-14T21:17:31.9631693Z     .. warning::
2025-08-14T21:17:31.9631796Z     
2025-08-14T21:17:31.9632012Z         ``local_rank`` is NOT globally unique: it is only unique per process
2025-08-14T21:17:31.9632226Z         on a machine.  Thus, don't use it to decide if you should, e.g.,
2025-08-14T21:17:31.9632358Z         write to a networked filesystem.  See
2025-08-14T21:17:31.9632577Z         https://github.com/pytorch/pytorch/issues/12042 for an example of
2025-08-14T21:17:31.9632743Z         how things can go wrong if you don't do this correctly.
2025-08-14T21:17:31.9632840Z     
2025-08-14T21:17:31.9632919Z     
2025-08-14T21:17:31.9632997Z     
2025-08-14T21:17:31.9633089Z     
2025-08-14T21:17:31.9633341Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9633418Z     
2025-08-14T21:17:31.9633526Z       warnings.warn(msg)
2025-08-14T21:17:31.9633607Z     
2025-08-14T21:17:31.9633839Z --- Parse Warning: 55 / 146 ---
2025-08-14T21:17:31.9634886Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361.
2025-08-14T21:17:31.9635154Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9635247Z     
2025-08-14T21:17:31.9635485Z     Creates an :class:`ShardedTensor` from local shards and the global metadata.
2025-08-14T21:17:31.9635630Z     Needs to be called on all ranks in an SPMD fashion.
2025-08-14T21:17:31.9635725Z     
2025-08-14T21:17:31.9635810Z     Args:
2025-08-14T21:17:31.9636093Z         local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list
2025-08-14T21:17:31.9636262Z             of shards that represent the local shards on this rank.
2025-08-14T21:17:31.9636485Z         global_size (int...):  a list, tuple, or `torch.Size` of integers defining the
2025-08-14T21:17:31.9636614Z             shape of the overall sharded tensor.
2025-08-14T21:17:31.9636694Z     
2025-08-14T21:17:31.9636782Z     Keyword args:
2025-08-14T21:17:31.9637051Z         process_group (ProcessGroup, optional): The process group to work on. If None,
2025-08-14T21:17:31.9637177Z             the default process group will be used.
2025-08-14T21:17:31.9637347Z         init_rrefs (bool, optional): Whether or not to initialize
2025-08-14T21:17:31.9637561Z             :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-08-14T21:17:31.9637751Z             Need to initialize the RPC Framework if specified as ``True``.
2025-08-14T21:17:31.9637924Z             Default: ``False``.
2025-08-14T21:17:31.9638005Z     
2025-08-14T21:17:31.9638091Z     Returns:
2025-08-14T21:17:31.9638251Z         A :class:`ShardedTensor` object handle on this rank
2025-08-14T21:17:31.9638329Z     
2025-08-14T21:17:31.9638405Z     
2025-08-14T21:17:31.9638504Z     Examples:
2025-08-14T21:17:31.9638756Z         Suppose we want construct a sharded tensor on two ranks, global size = (10, 5),
2025-08-14T21:17:31.9638942Z         each shard have a (5, 5) local tensor, we can do it like below:
2025-08-14T21:17:31.9639033Z     
2025-08-14T21:17:31.9639118Z         on rank 0:
2025-08-14T21:17:31.9639247Z         >>> # xdoctest: +SKIP("not distributed")
2025-08-14T21:17:31.9639371Z         >>> local_shard_metadata = ShardMetadata(
2025-08-14T21:17:31.9639472Z         >>>     shard_offsets=[0, 0],
2025-08-14T21:17:31.9639584Z         >>>     shard_lengths=[5, 5],
2025-08-14T21:17:31.9639693Z         >>>     placement="rank:0/cuda:0"
2025-08-14T21:17:31.9639777Z         >>> )
2025-08-14T21:17:31.9639978Z         >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-08-14T21:17:31.9640172Z         >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-08-14T21:17:31.9640252Z     
2025-08-14T21:17:31.9640347Z         on rank 1:
2025-08-14T21:17:31.9640467Z         >>> # xdoctest: +SKIP("not distributed")
2025-08-14T21:17:31.9640626Z         >>> local_shard_metadata = ShardMetadata(
2025-08-14T21:17:31.9640789Z         >>>     shard_offsets=[5, 0],
2025-08-14T21:17:31.9640889Z         >>>     shard_lengths=[5, 5],
2025-08-14T21:17:31.9641007Z         >>>     placement="rank:1/cuda:1"
2025-08-14T21:17:31.9641090Z         >>> )
2025-08-14T21:17:31.9641281Z         >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-08-14T21:17:31.9641483Z         >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-08-14T21:17:31.9641559Z     
2025-08-14T21:17:31.9641813Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9641904Z     
2025-08-14T21:17:31.9642001Z       warnings.warn(msg)
2025-08-14T21:17:31.9642080Z     
2025-08-14T21:17:31.9642279Z --- Parse Warning: 56 / 146 ---
2025-08-14T21:17:31.9643371Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835.
2025-08-14T21:17:31.9643649Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9643731Z     
2025-08-14T21:17:31.9643991Z     Initialize a ShardedTensor given only one local tensor, global sharded tensor
2025-08-14T21:17:31.9644114Z     size and sharding spec on each rank.
2025-08-14T21:17:31.9644193Z     
2025-08-14T21:17:31.9644276Z     Args:
2025-08-14T21:17:31.9644510Z         local_tensor (Tensor): Single tensor of local shard stored in each rank.
2025-08-14T21:17:31.9644774Z         sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`):
2025-08-14T21:17:31.9644958Z             The specification describing how to shard the Tensor.
2025-08-14T21:17:31.9645129Z         global_size (Sequence[int]): Size of the sharded tensor.
2025-08-14T21:17:31.9645384Z         process_group (ProcessGroup, optional): The process group to aggregate on.
2025-08-14T21:17:31.9645494Z             Default: None
2025-08-14T21:17:31.9645669Z         init_rrefs (bool, optional): Whether or not to initialize
2025-08-14T21:17:31.9645875Z             :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-08-14T21:17:31.9646074Z             Need to initialize the RPC Framework if specified as ``True``.
2025-08-14T21:17:31.9646171Z             Default: ``False``.
2025-08-14T21:17:31.9646262Z     
2025-08-14T21:17:31.9646342Z     Returns:
2025-08-14T21:17:31.9646616Z         A :class:`ShardedTensor` sharded based on the given sharding_spec with local
2025-08-14T21:17:31.9646746Z             tensor stored in the current rank.
2025-08-14T21:17:31.9646824Z     
2025-08-14T21:17:31.9646909Z     Examples:
2025-08-14T21:17:31.9647019Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9647154Z         >>> # All tensors below are of torch.int64 type.
2025-08-14T21:17:31.9647270Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9647459Z         >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank
2025-08-14T21:17:31.9647659Z         >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2]))
2025-08-14T21:17:31.9647760Z         >>> local_tensor
2025-08-14T21:17:31.9647856Z         tensor([[1, 2, 3, 4]]) # Rank 0
2025-08-14T21:17:31.9647953Z         tensor([[3, 4, 5, 6]]) # Rank 1
2025-08-14T21:17:31.9648059Z         >>> sharding_dim = 0
2025-08-14T21:17:31.9648179Z         >>> sharding_spec = ChunkShardingSpec(
2025-08-14T21:17:31.9648275Z                 dim=sharding_dim,
2025-08-14T21:17:31.9648384Z                 placements=[
2025-08-14T21:17:31.9648478Z                     "rank:0/cuda:0",
2025-08-14T21:17:31.9648570Z                     "rank:1/cuda:1",
2025-08-14T21:17:31.9648661Z                 ],
2025-08-14T21:17:31.9648742Z             )
2025-08-14T21:17:31.9648874Z         >>> st = ShardedTensor._init_from_local_tensor(
2025-08-14T21:17:31.9649031Z         ...     local_tensor, sharding_spec, [2, 4]
2025-08-14T21:17:31.9649137Z         ... )
2025-08-14T21:17:31.9649252Z         >>> st
2025-08-14T21:17:31.9649344Z         ShardedTensor(
2025-08-14T21:17:31.9649447Z             ShardedTensorMetadata(
2025-08-14T21:17:31.9649554Z                 shards_metadata=[
2025-08-14T21:17:31.9649822Z                     ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0),
2025-08-14T21:17:31.9650083Z                     ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1),
2025-08-14T21:17:31.9650177Z                 ],
2025-08-14T21:17:31.9650283Z                 size=torch.Size([2, 4])
2025-08-14T21:17:31.9650362Z         )
2025-08-14T21:17:31.9650467Z         >>> st.local_tensor()
2025-08-14T21:17:31.9650563Z         tensor([1, 2, 3, 4]) # Rank 0
2025-08-14T21:17:31.9650668Z         tensor([3, 4, 5, 6]) # Rank 1
2025-08-14T21:17:31.9650746Z     
2025-08-14T21:17:31.9651015Z     Warning: This API is experimental and subject to change. It lacks of a fully across
2025-08-14T21:17:31.9651265Z              rank validations, and we only validate the local shard on the current rank.
2025-08-14T21:17:31.9651477Z              We fully rely on the user to ensure local tensor is sharded based on the
2025-08-14T21:17:31.9651571Z              sharding spec.
2025-08-14T21:17:31.9651659Z     
2025-08-14T21:17:31.9651909Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9651991Z     
2025-08-14T21:17:31.9652095Z       warnings.warn(msg)
2025-08-14T21:17:31.9652169Z     
2025-08-14T21:17:31.9652359Z --- Parse Warning: 57 / 146 ---
2025-08-14T21:17:31.9653410Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076.
2025-08-14T21:17:31.9653678Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9653774Z     
2025-08-14T21:17:31.9654027Z     Reshard a sharded tensor given the ``resharding_spec``. For now, we only support
2025-08-14T21:17:31.9654119Z     single local shard.
2025-08-14T21:17:31.9654208Z     
2025-08-14T21:17:31.9654429Z     If ``resharding_spec`` is same as the original one, this becomes a no-op.
2025-08-14T21:17:31.9654684Z     If only ``resharding_spec`` shares the same sharding dim with the original one,
2025-08-14T21:17:31.9654790Z     we swap local shards directly.
2025-08-14T21:17:31.9655077Z     For more generic cases, we merge different shards across different ranks and split
2025-08-14T21:17:31.9655342Z     the local shards based on the ``resharding_spec`` via `all_to_all` collective API.
2025-08-14T21:17:31.9655423Z     
2025-08-14T21:17:31.9655505Z     Args:
2025-08-14T21:17:31.9655811Z         resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The
2025-08-14T21:17:31.9655978Z             specification describing how the tensor is sharded.
2025-08-14T21:17:31.9656059Z     
2025-08-14T21:17:31.9656155Z     Returns:
2025-08-14T21:17:31.9656357Z         A :class:`ShardedTensor` object whose local shards are resharded.
2025-08-14T21:17:31.9656447Z     
2025-08-14T21:17:31.9656530Z     Examples:
2025-08-14T21:17:31.9656627Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9656753Z         >>> # We have 2 process groups, 2 ranks.
2025-08-14T21:17:31.9656926Z         >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank
2025-08-14T21:17:31.9657046Z         >>> tensor = torch.stack([tensor, tensor])
2025-08-14T21:17:31.9657139Z         >>> tensor
2025-08-14T21:17:31.9657259Z         tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0
2025-08-14T21:17:31.9657376Z         tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1
2025-08-14T21:17:31.9657507Z         tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2
2025-08-14T21:17:31.9657628Z         tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3
2025-08-14T21:17:31.9657761Z         >>> sharding_dim = 0
2025-08-14T21:17:31.9657894Z         >>> spec = ChunkShardingSpec(
2025-08-14T21:17:31.9658017Z                 dim=sharding_dim,
2025-08-14T21:17:31.9658124Z                 placements=[
2025-08-14T21:17:31.9658216Z                     "rank:0/cuda:0",
2025-08-14T21:17:31.9658310Z                     "rank:1/cuda:1",
2025-08-14T21:17:31.9658416Z                     "rank:2/cuda:2",
2025-08-14T21:17:31.9658506Z                     "rank:3/cuda:3",
2025-08-14T21:17:31.9658588Z                 ],
2025-08-14T21:17:31.9658686Z             )
2025-08-14T21:17:31.9658793Z         >>> current_offsets = [0] * 2
2025-08-14T21:17:31.9658901Z         >>> current_offsets[0] = rank * 2
2025-08-14T21:17:31.9659026Z         >>> shard_metadata = ShardMetadata(
2025-08-14T21:17:31.9659177Z                 shard_offsets=copy.deepcopy(current_offsets),
2025-08-14T21:17:31.9659299Z                 shard_sizes=tensor.size(),
2025-08-14T21:17:31.9659419Z                 placement=spec.placements[rank],
2025-08-14T21:17:31.9659505Z             )
2025-08-14T21:17:31.9659614Z         >>> local_shards = [
2025-08-14T21:17:31.9659701Z                 Shard(
2025-08-14T21:17:31.9659799Z                     tensor=tensor,
2025-08-14T21:17:31.9659920Z                     metadata=shard_metadata,
2025-08-14T21:17:31.9660002Z                 )
2025-08-14T21:17:31.9660084Z             ]
2025-08-14T21:17:31.9660326Z         >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size())
2025-08-14T21:17:31.9660423Z         >>> sharding_dim = 1
2025-08-14T21:17:31.9660564Z         >>> resharding_spec = ChunkShardingSpec(
2025-08-14T21:17:31.9660661Z                 dim=sharding_dim,
2025-08-14T21:17:31.9660756Z                 placements=[
2025-08-14T21:17:31.9660864Z                     "rank:0/cuda:0",
2025-08-14T21:17:31.9660958Z                     "rank:1/cuda:1",
2025-08-14T21:17:31.9661049Z                     "rank:2/cuda:2",
2025-08-14T21:17:31.9661155Z                     "rank:3/cuda:3",
2025-08-14T21:17:31.9661245Z                 ],
2025-08-14T21:17:31.9661324Z             )
2025-08-14T21:17:31.9661449Z         >>> st.reshard(resharding_spec)
2025-08-14T21:17:31.9661564Z         >>> tensor = st.local_shards()[0].tensor
2025-08-14T21:17:31.9661648Z         >>> tensor
2025-08-14T21:17:31.9661799Z         tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0
2025-08-14T21:17:31.9661936Z         tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1
2025-08-14T21:17:31.9662087Z         tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2
2025-08-14T21:17:31.9662252Z         tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3
2025-08-14T21:17:31.9662335Z     
2025-08-14T21:17:31.9662599Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9662679Z     
2025-08-14T21:17:31.9662777Z       warnings.warn(msg)
2025-08-14T21:17:31.9662871Z     
2025-08-14T21:17:31.9663061Z --- Parse Warning: 58 / 146 ---
2025-08-14T21:17:31.9664046Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12.
2025-08-14T21:17:31.9664321Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9664397Z     
2025-08-14T21:17:31.9664626Z     Representation of a sharding plan, describes how to shard a module
2025-08-14T21:17:31.9664893Z     across hosts. `plan` is used to shard module parameters according to the spec provided,
2025-08-14T21:17:31.9665180Z     `output_plan` and `return_local_tensor` are optional, they are used to specify the output
2025-08-14T21:17:31.9665437Z     layout of a module with a spec, and when to convert back to data parallel fashion.
2025-08-14T21:17:31.9665513Z     
2025-08-14T21:17:31.9665597Z     Args:
2025-08-14T21:17:31.9665901Z         plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`,
2025-08-14T21:17:31.9666091Z               :class:`torch.distributed._shard.sharder.Sharder`]):
2025-08-14T21:17:31.9666406Z             a dict describes how to shard a module, there're currently two ways to shard a module:
2025-08-14T21:17:31.9666659Z                 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of
2025-08-14T21:17:31.9666779Z                    a parameter to a `ShardingSpec`.
2025-08-14T21:17:31.9667049Z                 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module
2025-08-14T21:17:31.9667156Z                    to a `Sharder` object.
2025-08-14T21:17:31.9667492Z         output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional):
2025-08-14T21:17:31.9667748Z             a dict specifies the layout of a module's output which produces a ShardedTensor,
2025-08-14T21:17:31.9667983Z             keyed by the name of module to ShardingSpec("" in key means the root module).
2025-08-14T21:17:31.9668091Z             Default: `None`
2025-08-14T21:17:31.9668345Z         return_local_tensor (List[str], optional): a list of string, each element enables
2025-08-14T21:17:31.9668582Z             a module's sharded output to be returned as a Tensor from its local shards to
2025-08-14T21:17:31.9668845Z             ensure further processing in a data parallel fashion. ("" in list means the
2025-08-14T21:17:31.9668937Z             root module).
2025-08-14T21:17:31.9669044Z             Default: None
2025-08-14T21:17:31.9669126Z     Example:
2025-08-14T21:17:31.9669411Z       Suppose we want to shard a module with two linear layers and then run it with DDP, we also
2025-08-14T21:17:31.9669704Z       want to convert the output of the second linear layer back to DDP, we can do it as follows:
2025-08-14T21:17:31.9669784Z     
2025-08-14T21:17:31.9669954Z         >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d)
2025-08-14T21:17:31.9670076Z         >>> class MyModule(nn.Module):
2025-08-14T21:17:31.9670186Z         >>>     def __init__(self) -> None:
2025-08-14T21:17:31.9670285Z         >>>        super().__init__()
2025-08-14T21:17:31.9670397Z         >>>        self.fc1 = nn.Linear()
2025-08-14T21:17:31.9670499Z         >>>        self.gelu = nn.GELU()
2025-08-14T21:17:31.9670611Z         >>>        self.fc2 = nn.Linear()
2025-08-14T21:17:31.9670712Z         >>>        self.relu = nn.Linear()
2025-08-14T21:17:31.9670797Z         >>>
2025-08-14T21:17:31.9670911Z         >>>     def forward(self, input):
2025-08-14T21:17:31.9671122Z         >>>         return self.relu(self.fc2(self.gelu(self.fc1(input))))
2025-08-14T21:17:31.9671203Z     
2025-08-14T21:17:31.9671290Z     
2025-08-14T21:17:31.9671490Z         >>> # xdoctest: +SKIP("Undefined spec1, spec2)
2025-08-14T21:17:31.9671605Z         >>> sharding_plan = ShardingPlan(
2025-08-14T21:17:31.9671705Z         >>>    plan={
2025-08-14T21:17:31.9671804Z         >>>        "fc1.weight": spec1,
2025-08-14T21:17:31.9671905Z         >>>        "fc2.weight": spec2
2025-08-14T21:17:31.9672002Z         >>>    },
2025-08-14T21:17:31.9672100Z         >>>    output_plan={
2025-08-14T21:17:31.9672210Z         >>>        "fc2": output_spec
2025-08-14T21:17:31.9672291Z         >>>    },
2025-08-14T21:17:31.9672400Z         >>>    return_local_tensor=["fc2"]
2025-08-14T21:17:31.9672495Z         >>> )
2025-08-14T21:17:31.9672577Z     
2025-08-14T21:17:31.9672830Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9672920Z     
2025-08-14T21:17:31.9673017Z       warnings.warn(msg)
2025-08-14T21:17:31.9673096Z     
2025-08-14T21:17:31.9673307Z --- Parse Warning: 59 / 146 ---
2025-08-14T21:17:31.9674415Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72.
2025-08-14T21:17:31.9674753Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9674861Z     
2025-08-14T21:17:31.9674970Z     Run post-localSGD algorithm.
2025-08-14T21:17:31.9675063Z     
2025-08-14T21:17:31.9675301Z     This DDP communication hook is used for running post-localSGD algorithm,
2025-08-14T21:17:31.9675460Z     by combining with a model averaging component (e.g.,
2025-08-14T21:17:31.9675798Z     :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`)
2025-08-14T21:17:31.9675909Z     that runs after the optimizer step.
2025-08-14T21:17:31.9675985Z     
2025-08-14T21:17:31.9676076Z     Args:
2025-08-14T21:17:31.9676298Z         state (PostLocalSGDState): State information to run post-localSGD.
2025-08-14T21:17:31.9676584Z             Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD.
2025-08-14T21:17:31.9677005Z         bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-08-14T21:17:31.9677254Z             Note that since DDP comm hook only supports single process single device mode,
2025-08-14T21:17:31.9677417Z             only exactly one tensor is stored in this bucket.
2025-08-14T21:17:31.9677496Z     
2025-08-14T21:17:31.9677577Z     Returns:
2025-08-14T21:17:31.9677827Z         Future handler of the communication, which updates the gradients in place.
2025-08-14T21:17:31.9677906Z     
2025-08-14T21:17:31.9678007Z     Example::
2025-08-14T21:17:31.9678103Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9678357Z         >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup,
2025-08-14T21:17:31.9678486Z                                   start_localSGD_iter=10)
2025-08-14T21:17:31.9678660Z         >>> ddp_model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:31.9678992Z         >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``.
2025-08-14T21:17:31.9679350Z         >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module.
2025-08-14T21:17:31.9679430Z     
2025-08-14T21:17:31.9679691Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9679770Z     
2025-08-14T21:17:31.9679864Z       warnings.warn(msg)
2025-08-14T21:17:31.9679950Z     
2025-08-14T21:17:31.9680134Z --- Parse Warning: 60 / 146 ---
2025-08-14T21:17:31.9681230Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342.
2025-08-14T21:17:31.9681503Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9681581Z     
2025-08-14T21:17:31.9681691Z     Implement PowerSGD algorithm.
2025-08-14T21:17:31.9681779Z     
2025-08-14T21:17:31.9682008Z     This DDP communication hook implements PowerSGD gradient compression
2025-08-14T21:17:31.9682255Z     algorithm described in the `paper <https://arxiv.org/abs/1905.13727>`_.
2025-08-14T21:17:31.9682496Z     Once gradient tensors are aggregated across all workers, this hook applies
2025-08-14T21:17:31.9682598Z     compression as follows:
2025-08-14T21:17:31.9682686Z     
2025-08-14T21:17:31.9683122Z     1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups:
2025-08-14T21:17:31.9683200Z     
2025-08-14T21:17:31.9683629Z         1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth.
2025-08-14T21:17:31.9683709Z     
2025-08-14T21:17:31.9684126Z         1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases).
2025-08-14T21:17:31.9684204Z     
2025-08-14T21:17:31.9684337Z     2. Handles uncompressed tensors:
2025-08-14T21:17:31.9684452Z     
2025-08-14T21:17:31.9684989Z         2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression;
2025-08-14T21:17:31.9685067Z     
2025-08-14T21:17:31.9685418Z         2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor.
2025-08-14T21:17:31.9685496Z     
2025-08-14T21:17:31.9685729Z     3. Handles the tensors that should be compressed by PowerSGD compression:
2025-08-14T21:17:31.9685815Z     
2025-08-14T21:17:31.9686055Z         3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M,
2025-08-14T21:17:31.9686375Z         such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized;
2025-08-14T21:17:31.9686454Z     
2025-08-14T21:17:31.9686602Z         3.2. Computes each P in Ps, which is equal to MQ;
2025-08-14T21:17:31.9686697Z     
2025-08-14T21:17:31.9686802Z         3.3. Allreduces Ps as a batch;
2025-08-14T21:17:31.9686881Z     
2025-08-14T21:17:31.9687009Z         3.4. Orthogonalizes each P in Ps;
2025-08-14T21:17:31.9687085Z     
2025-08-14T21:17:31.9687281Z         3.5. Computes each Q in Qs, which is approximately equal to M^TP;
2025-08-14T21:17:31.9687367Z     
2025-08-14T21:17:31.9687471Z         3.6. Allreduces Qs as a batch;
2025-08-14T21:17:31.9687561Z     
2025-08-14T21:17:31.9687859Z         3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T.
2025-08-14T21:17:31.9687937Z     
2025-08-14T21:17:31.9688360Z     Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations.
2025-08-14T21:17:31.9688640Z     This not only gives the user more control over the tradeoff between speedup and accuracy,
2025-08-14T21:17:31.9689072Z     but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers.
2025-08-14T21:17:31.9689165Z     
2025-08-14T21:17:31.9689248Z     Args:
2025-08-14T21:17:31.9689693Z         state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc.
2025-08-14T21:17:31.9690048Z             To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter``
2025-08-14T21:17:31.9690159Z             and ``min_compression_rate``.
2025-08-14T21:17:31.9690583Z         bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-08-14T21:17:31.9690858Z             Note that since DDP comm hook only supports single process single device mode,
2025-08-14T21:17:31.9691013Z             only exactly one tensor is stored in this bucket.
2025-08-14T21:17:31.9691104Z     
2025-08-14T21:17:31.9691186Z     Returns:
2025-08-14T21:17:31.9691443Z         Future handler of the communication, which updates the gradients in place.
2025-08-14T21:17:31.9691523Z     
2025-08-14T21:17:31.9691614Z     Example::
2025-08-14T21:17:31.9691726Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9692002Z         >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1,
2025-08-14T21:17:31.9692164Z                                   start_powerSGD_iter=10, min_compression_rate=0.5)
2025-08-14T21:17:31.9692337Z         >>> ddp_model.register_comm_hook(state, powerSGD_hook)
2025-08-14T21:17:31.9692417Z     
2025-08-14T21:17:31.9692671Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9692762Z     
2025-08-14T21:17:31.9692861Z       warnings.warn(msg)
2025-08-14T21:17:31.9692951Z     
2025-08-14T21:17:31.9693136Z --- Parse Warning: 61 / 146 ---
2025-08-14T21:17:31.9694278Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38.
2025-08-14T21:17:31.9694577Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9694686Z     
2025-08-14T21:17:31.9694875Z     Averages parameters periodically after the warm-up stage.
2025-08-14T21:17:31.9694968Z     
2025-08-14T21:17:31.9695224Z     This can be used for running `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-08-14T21:17:31.9695430Z     by running :class:`~torch.nn.DistributedDataParallel` (DDP)
2025-08-14T21:17:31.9695673Z     using the subgroups created by :meth:`~torch.distributed.new_subgroups`.
2025-08-14T21:17:31.9695752Z     
2025-08-14T21:17:31.9695851Z     Args:
2025-08-14T21:17:31.9696017Z         period (int): The number of steps per model averaging.
2025-08-14T21:17:31.9696286Z                       Usually the period should be greater than ``1`` to reduce the communication cost.
2025-08-14T21:17:31.9696430Z                       Otherwise, only DDP needs to be used.
2025-08-14T21:17:31.9696642Z         warmup_steps (int): The number of warm-up steps. During this stage,
2025-08-14T21:17:31.9696764Z                             model averaging is skipped.
2025-08-14T21:17:31.9696967Z         process_group: The process group to be used for all-reduce.
2025-08-14T21:17:31.9697108Z                        If ``None``, the default process group, which
2025-08-14T21:17:31.9697306Z                        is created by :func:`torch.distributed.init_process_group`,
2025-08-14T21:17:31.9697429Z                        will be used. (default: ``None``)
2025-08-14T21:17:31.9697512Z     
2025-08-14T21:17:31.9697616Z     Example::
2025-08-14T21:17:31.9697697Z     
2025-08-14T21:17:31.9697827Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9697936Z         >>> import torch
2025-08-14T21:17:31.9698056Z         >>> import torch.distributed as dist
2025-08-14T21:17:31.9698374Z         >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD
2025-08-14T21:17:31.9698656Z         >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-08-14T21:17:31.9698760Z         >>> import torch.nn as nn
2025-08-14T21:17:31.9698856Z         >>>
2025-08-14T21:17:31.9699030Z         >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-08-14T21:17:31.9699138Z         >>> torch.cuda.set_device(rank)
2025-08-14T21:17:31.9699276Z         >>> module = nn.Linear(1, 1, bias=False).cuda()
2025-08-14T21:17:31.9699424Z         >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:31.9699591Z         >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:31.9699681Z         >>> )
2025-08-14T21:17:31.9699824Z         >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:31.9700129Z         >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-08-14T21:17:31.9700289Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:31.9700371Z         >>>
2025-08-14T21:17:31.9700649Z         >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-08-14T21:17:31.9700805Z         >>> # After 100 steps, run model averaging every 4 steps.
2025-08-14T21:17:31.9701122Z         >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:31.9701380Z         >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-08-14T21:17:31.9701485Z         >>> for step in range(0, 200):
2025-08-14T21:17:31.9701600Z         >>>    optimizer.zero_grad()
2025-08-14T21:17:31.9701717Z         >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:31.9701817Z         >>>    loss.backward()
2025-08-14T21:17:31.9701928Z         >>>    optimizer.step()
2025-08-14T21:17:31.9702120Z         >>>    # Will average model parameters globally every 4 steps. Thus,
2025-08-14T21:17:31.9702346Z         >>>    # inter-node communication only occurs every 4 iterations after
2025-08-14T21:17:31.9702506Z         >>>    # the initial ``warmup_steps`` period.
2025-08-14T21:17:31.9702705Z         >>>    averager.average_parameters(model.parameters())
2025-08-14T21:17:31.9702783Z     
2025-08-14T21:17:31.9703046Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9703126Z     
2025-08-14T21:17:31.9703234Z       warnings.warn(msg)
2025-08-14T21:17:31.9703313Z     
2025-08-14T21:17:31.9703502Z --- Parse Warning: 62 / 146 ---
2025-08-14T21:17:31.9704732Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19.
2025-08-14T21:17:31.9704994Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9705075Z     
2025-08-14T21:17:31.9705422Z     Runs hierarchical model averaging (`hierarchical SGD <https://arxiv.org/pdf/2010.12998.pdf>`_).
2025-08-14T21:17:31.9705504Z     
2025-08-14T21:17:31.9705823Z     Process groups of different sizes are organized in a hierarchy, and they average parameters
2025-08-14T21:17:31.9706027Z     by using different periods concurrently after the warm-up stage.
2025-08-14T21:17:31.9706432Z     This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`
2025-08-14T21:17:31.9706781Z     that supports `post-local SGD <https://arxiv.org/abs/1808.07217>`_, which essentially only supports
2025-08-14T21:17:31.9707085Z     a two-level hierarchy: the intra-machine level and the global level, where the intra-machine
2025-08-14T21:17:31.9707446Z     level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`.
2025-08-14T21:17:31.9707744Z     Similarly, the process groups within this class do not have such an intra-machine process
2025-08-14T21:17:31.9708019Z     subgroup, which should be embedded by the post-local SGD communication hook instead.
2025-08-14T21:17:31.9708109Z     
2025-08-14T21:17:31.9708191Z     Args:
2025-08-14T21:17:31.9708449Z         period_group_size_dict: An ordered dict mapping keys of model averaging period to
2025-08-14T21:17:31.9708657Z                                 process group size, used for initializing process groups of
2025-08-14T21:17:31.9708882Z                                 different sizes in a hierarchy to average parameters concurrently.
2025-08-14T21:17:31.9709338Z                                 Particularly, at each iteration, there will be at most a single
2025-08-14T21:17:31.9709572Z                                 process group that runs averaging -- the period of such group should
2025-08-14T21:17:31.9709784Z                                 have the largest period which the current step can be divided by.
2025-08-14T21:17:31.9709967Z                                 For example, if the dict has three keys: 2, 4, and 8,
2025-08-14T21:17:31.9710176Z                                 then this means totally three process groups will be created to
2025-08-14T21:17:31.9710387Z                                 average parameters every 2, 4, and 8 iterations, respectively.
2025-08-14T21:17:31.9710592Z                                 At the 4th iteration, only the second process group will run
2025-08-14T21:17:31.9710769Z                                 averaging, because the first process group should be a
2025-08-14T21:17:31.9711004Z                                 subset of the second process group, and no need to execute the first
2025-08-14T21:17:31.9711126Z                                 process group redundantly.
2025-08-14T21:17:31.9711323Z                                 On the other hand, the third process group can only be triggered
2025-08-14T21:17:31.9711629Z                                 every 8 iterations, so it will not be triggered at the 4th iteration.
2025-08-14T21:17:31.9711984Z         warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped.
2025-08-14T21:17:31.9712518Z         process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging.
2025-08-14T21:17:31.9712693Z                                                 If ``None``, the default process group, which is created
2025-08-14T21:17:31.9712901Z                                                 by :func:`torch.distributed.init_process_group`, will be used.
2025-08-14T21:17:31.9713040Z                                                 (default: ``None``)
2025-08-14T21:17:31.9713123Z     
2025-08-14T21:17:31.9713218Z     Example::
2025-08-14T21:17:31.9713352Z         >>> # xdoctest: +SKIP('undefined rank')
2025-08-14T21:17:31.9713472Z         >>> from collections import OrderedDict
2025-08-14T21:17:31.9713580Z         >>> import torch
2025-08-14T21:17:31.9713696Z         >>> import torch.distributed as dist
2025-08-14T21:17:31.9713968Z         >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-08-14T21:17:31.9714087Z         >>>     PostLocalSGDState,
2025-08-14T21:17:31.9714186Z         >>>     post_localSGD_hook,
2025-08-14T21:17:31.9714266Z         >>> )
2025-08-14T21:17:31.9714653Z         >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD
2025-08-14T21:17:31.9714754Z         >>> import torch.nn as nn
2025-08-14T21:17:31.9714833Z         >>>
2025-08-14T21:17:31.9715024Z         >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-08-14T21:17:31.9715133Z         >>> torch.cuda.set_device(rank)
2025-08-14T21:17:31.9715278Z         >>> module = nn.Linear(1, 1, bias=False).to(rank)
2025-08-14T21:17:31.9715425Z         >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:31.9715563Z         >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:31.9715656Z         >>> )
2025-08-14T21:17:31.9715800Z         >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:31.9716074Z         >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4.
2025-08-14T21:17:31.9716204Z         >>> subgroup, _ = dist.new_subgroups()
2025-08-14T21:17:31.9716513Z         >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100)
2025-08-14T21:17:31.9716685Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:31.9716765Z         >>>
2025-08-14T21:17:31.9717074Z         >>> # Average parameters among each group of 8 processes every 4 iterations, and among all
2025-08-14T21:17:31.9717207Z         >>> # the 16 processes every 16 iterations.
2025-08-14T21:17:31.9717395Z         >>> averager = hierarchicalSGD.HierarchicalModelAverager(
2025-08-14T21:17:31.9717625Z         >>>     period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100)
2025-08-14T21:17:31.9717952Z         >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:31.9718220Z         >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-08-14T21:17:31.9718385Z         >>> # After 100 steps, run model averaging at two levels.
2025-08-14T21:17:31.9718489Z         >>> for step in range(0, 200):
2025-08-14T21:17:31.9718591Z         >>>    optimizer.zero_grad()
2025-08-14T21:17:31.9718715Z         >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:31.9718810Z         >>>    loss.backward()
2025-08-14T21:17:31.9718908Z         >>>    optimizer.step()
2025-08-14T21:17:31.9719077Z         >>>    # Average parameters after ``optimizer.step()``.
2025-08-14T21:17:31.9719359Z         >>>    # Thus, the inter-node communication only occurs periodically after ``warmup_steps``.
2025-08-14T21:17:31.9719520Z         >>>    averager.average_parameters(model.parameters())
2025-08-14T21:17:31.9719614Z     
2025-08-14T21:17:31.9719701Z     .. warning ::
2025-08-14T21:17:31.9719990Z         The last group size in the dict must be the size of the provided ``process_group``,
2025-08-14T21:17:31.9720271Z         which indicates model averaging at the highest level of the hierarchy.
2025-08-14T21:17:31.9720572Z         If ``process_group`` is not provided, then the last group size should be equal to the world size.
2025-08-14T21:17:31.9720665Z     
2025-08-14T21:17:31.9720752Z     .. warning ::
2025-08-14T21:17:31.9720984Z         `HierarchicalModelAverager` is experimental and subject to change.
2025-08-14T21:17:31.9721075Z     
2025-08-14T21:17:31.9721326Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9721418Z     
2025-08-14T21:17:31.9721512Z       warnings.warn(msg)
2025-08-14T21:17:31.9721592Z     
2025-08-14T21:17:31.9721817Z --- Parse Warning: 63 / 146 ---
2025-08-14T21:17:31.9722891Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40.
2025-08-14T21:17:31.9723158Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9723250Z     
2025-08-14T21:17:31.9723541Z     StorageReader for reading a Torch Save file. This reader will read the entire checkpoint
2025-08-14T21:17:31.9723800Z     on the coordinator rank, and then broadcast and shard each tensor to all ranks.
2025-08-14T21:17:31.9723877Z     
2025-08-14T21:17:31.9724045Z     . N.B. Intended to be used with DynamicMetaLoadPlanner
2025-08-14T21:17:31.9724140Z     
2025-08-14T21:17:31.9724226Z     .. warning::
2025-08-14T21:17:31.9724399Z         Current implementation only supports loading Tensors.
2025-08-14T21:17:31.9724491Z     
2025-08-14T21:17:31.9724606Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9724701Z     >>> sd = {"mode": model}
2025-08-14T21:17:31.9724796Z     >>> dcp.load(
2025-08-14T21:17:31.9724881Z     >>>    sd,
2025-08-14T21:17:31.9725033Z     >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-08-14T21:17:31.9725171Z     >>>    planner=DynamicMetaLoadPlanner(),
2025-08-14T21:17:31.9725284Z     >>>    checkpoint_id="path_to_model.pt"
2025-08-14T21:17:31.9725377Z     >>> )
2025-08-14T21:17:31.9725456Z     
2025-08-14T21:17:31.9725710Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9725802Z     
2025-08-14T21:17:31.9725898Z       warnings.warn(msg)
2025-08-14T21:17:31.9725976Z     
2025-08-14T21:17:31.9726200Z --- Parse Warning: 64 / 146 ---
2025-08-14T21:17:31.9727241Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151.
2025-08-14T21:17:31.9727506Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9727600Z     
2025-08-14T21:17:31.9727969Z     Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict,
2025-08-14T21:17:31.9728305Z     avoiding the need to read metadata from disk. This is useful when reading formats which don't have a
2025-08-14T21:17:31.9728420Z     metadata file, like Torch Save files.
2025-08-14T21:17:31.9728501Z     
2025-08-14T21:17:31.9728695Z     . N.B. Intended to be used with BroadcastingTorchSaveReader
2025-08-14T21:17:31.9728775Z     
2025-08-14T21:17:31.9728865Z     .. warning::
2025-08-14T21:17:31.9729054Z         Current implementation only supports loading Tensors.
2025-08-14T21:17:31.9729135Z     
2025-08-14T21:17:31.9729249Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9729358Z     >>> sd = {"mode": model}
2025-08-14T21:17:31.9729445Z     >>> dcp.load(
2025-08-14T21:17:31.9729542Z     >>>    sd,
2025-08-14T21:17:31.9737397Z     >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-08-14T21:17:31.9737666Z     >>>    planner=DynamicMetaLoadPlanner(),
2025-08-14T21:17:31.9737832Z     >>>    checkpoint_id="path_to_model.pt"
2025-08-14T21:17:31.9737915Z     >>> )
2025-08-14T21:17:31.9738007Z     
2025-08-14T21:17:31.9738272Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9738352Z     
2025-08-14T21:17:31.9738462Z       warnings.warn(msg)
2025-08-14T21:17:31.9738543Z     
2025-08-14T21:17:31.9738787Z --- Parse Warning: 65 / 146 ---
2025-08-14T21:17:31.9739869Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221.
2025-08-14T21:17:31.9740135Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9740230Z     
2025-08-14T21:17:31.9740443Z     Load a state_dict in conjunction with FSDP sharded optimizer state.
2025-08-14T21:17:31.9740532Z     
2025-08-14T21:17:31.9740714Z     This is the current recommended way to checkpoint FSDP.
2025-08-14T21:17:31.9740811Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9740968Z     >>> import torch.distributed.checkpoint as dist_cp
2025-08-14T21:17:31.9741063Z     >>> # Save
2025-08-14T21:17:31.9741164Z     >>> model: torch.nn.Model
2025-08-14T21:17:31.9741295Z     >>> optim_params = model.parameters()
2025-08-14T21:17:31.9741439Z     >>> optim = torch.optim.SGD(optim_params, lr=0.01)
2025-08-14T21:17:31.9741525Z     >>> # Save
2025-08-14T21:17:31.9741758Z     >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT):
2025-08-14T21:17:31.9741853Z     >>>     state_dict = {
2025-08-14T21:17:31.9742008Z     >>>         "optimizer": FSDP.optim_state_dict(model, optim),
2025-08-14T21:17:31.9742130Z     >>>         "model": model.state_dict()
2025-08-14T21:17:31.9742213Z     >>>     }
2025-08-14T21:17:31.9742317Z     >>>     dist_cp.save_state_dict(
2025-08-14T21:17:31.9742438Z     >>>         state_dict=optim_state,
2025-08-14T21:17:31.9742622Z     >>>         storage_writer=dist_cp.FileSystemWriter("checkpoint"),
2025-08-14T21:17:31.9742767Z     >>>         planner=dist_cp.DefaultSavePlanner(),
2025-08-14T21:17:31.9742846Z     >>>     )
2025-08-14T21:17:31.9742930Z     >>>
2025-08-14T21:17:31.9743025Z     >>> # Load
2025-08-14T21:17:31.9743253Z     >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT):
2025-08-14T21:17:31.9743384Z     >>>     model_state_dict = model_tp.state_dict()
2025-08-14T21:17:31.9743525Z     >>>     checkpoint = {
2025-08-14T21:17:31.9743632Z     >>>         "model": model_state_dict
2025-08-14T21:17:31.9743712Z     >>>     }
2025-08-14T21:17:31.9743830Z     >>>     dist_cp.load_state_dict(
2025-08-14T21:17:31.9743936Z     >>>         state_dict=checkpoint,
2025-08-14T21:17:31.9744127Z     >>>         storage_reader=dist_cp.FileSystemReader(checkpoint_file),
2025-08-14T21:17:31.9744278Z     >>>         planner=dist_cp.DefaultLoadPlanner(),
2025-08-14T21:17:31.9744360Z     >>>     )
2025-08-14T21:17:31.9744519Z     >>>     model.load_state_dict(checkpoint["model_state"])
2025-08-14T21:17:31.9744599Z     >>>
2025-08-14T21:17:31.9744768Z     >>>     optim_state = dist_cp.load_sharded_optimizer_state_dict(
2025-08-14T21:17:31.9744877Z     >>>         model_state_dict,
2025-08-14T21:17:31.9744988Z     >>>         optimizer_key="optimizer",
2025-08-14T21:17:31.9745164Z     >>>         storage_reader=dist_cp.FileSystemReader("checkpoint"),
2025-08-14T21:17:31.9745253Z     >>>     )
2025-08-14T21:17:31.9745336Z     >>>
2025-08-14T21:17:31.9745480Z     >>>     flattened_osd = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:31.9745618Z     >>>        model, optim, optim_state["optimizer"]
2025-08-14T21:17:31.9745698Z     >>>     )
2025-08-14T21:17:31.9745787Z     >>>
2025-08-14T21:17:31.9745906Z     >>>     optim.load_state_dict(flattened_osd)
2025-08-14T21:17:31.9746016Z     
2025-08-14T21:17:31.9746318Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9746425Z     
2025-08-14T21:17:31.9746523Z       warnings.warn(msg)
2025-08-14T21:17:31.9746614Z     
2025-08-14T21:17:31.9746805Z --- Parse Warning: 66 / 146 ---
2025-08-14T21:17:31.9747764Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122.
2025-08-14T21:17:31.9748041Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9748120Z     
2025-08-14T21:17:31.9748421Z     Abstract class defining the protocol used by save_state_dict to plan the save process.
2025-08-14T21:17:31.9748502Z     
2025-08-14T21:17:31.9748795Z     SavePlanners are stateful objects that can be used to customize the whole save process.
2025-08-14T21:17:31.9748888Z     
2025-08-14T21:17:31.9749168Z     SavePlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-08-14T21:17:31.9749285Z     will be visible to the whole process.
2025-08-14T21:17:31.9749375Z     
2025-08-14T21:17:31.9749648Z     A planner subclass can expect the following sequence of calls during save_state_dict:
2025-08-14T21:17:31.9749726Z     
2025-08-14T21:17:31.9749860Z     1) set_up_planner - called on all ranks.
2025-08-14T21:17:31.9749984Z         Signals the start of a checkpoint save.
2025-08-14T21:17:31.9750072Z     
2025-08-14T21:17:31.9750198Z     2) create_local_plan - called on all ranks.
2025-08-14T21:17:31.9750481Z         Process the state_dict and produces a `SavePlan` that will be sent for global planning.
2025-08-14T21:17:31.9750572Z     
2025-08-14T21:17:31.9750751Z     3) create_global_plan - called on the coordinator rank only.
2025-08-14T21:17:31.9750947Z         Takes the SavePlan from all ranks and make any global decision.
2025-08-14T21:17:31.9751039Z     
2025-08-14T21:17:31.9751152Z     4) finish_plan - called on all ranks.
2025-08-14T21:17:31.9751368Z         This gives each rank a chance to adjust to global planning decisions.
2025-08-14T21:17:31.9751586Z     
2025-08-14T21:17:31.9751742Z     5) resolve_data - called multiple times on each rank
2025-08-14T21:17:31.9751957Z         Lookups a value on the `state_dict` for the storage layer to write.
2025-08-14T21:17:31.9752037Z     
2025-08-14T21:17:31.9752340Z     Users are recommended to extend DefaultSavePlanner instead of this interface directly as
2025-08-14T21:17:31.9752576Z     most changes can be expressed by changes in a single method.
2025-08-14T21:17:31.9752657Z     
2025-08-14T21:17:31.9752776Z     There are 3 usual patterns of extension:
2025-08-14T21:17:31.9752866Z     
2025-08-14T21:17:31.9753119Z     Rewriting state_dict. This is the simplest way to extend the save process as it
2025-08-14T21:17:31.9753346Z     doesn't requite understanding the intrincacies of how SavePlan works:
2025-08-14T21:17:31.9753441Z     
2025-08-14T21:17:31.9753557Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9753705Z     >>> class RenamePlanner(DefaultSavePlanner):
2025-08-14T21:17:31.9753809Z     >>>     def set_up_planner(
2025-08-14T21:17:31.9753898Z     >>>         self,
2025-08-14T21:17:31.9754024Z     >>>         state_dict: STATE_DICT_TYPE,
2025-08-14T21:17:31.9754151Z     >>>         storage_meta: Optional[StorageMeta],
2025-08-14T21:17:31.9754257Z     >>>         is_coordinator: bool,
2025-08-14T21:17:31.9754359Z     >>>     ) -> None:
2025-08-14T21:17:31.9754465Z     >>> # prefix all keys with `foo_``
2025-08-14T21:17:31.9754760Z     >>>         super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator)
2025-08-14T21:17:31.9754849Z     
2025-08-14T21:17:31.9755176Z     Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted
2025-08-14T21:17:31.9755267Z     
2025-08-14T21:17:31.9755410Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9755557Z     >>> class FP16Planner(DefaultSavePlanner):
2025-08-14T21:17:31.9755706Z     >>>     def create_local_plan(self):
2025-08-14T21:17:31.9755826Z     >>>         plan = super().create_local_plan()
2025-08-14T21:17:31.9755922Z     >>>         for p in plan:
2025-08-14T21:17:31.9756051Z     >>>             if p.tensor_data is not None:
2025-08-14T21:17:31.9756212Z     >>>                 p.tensor_data.properties.dtype = torch.float16
2025-08-14T21:17:31.9756302Z     >>>         return plan
2025-08-14T21:17:31.9756395Z     >>>
2025-08-14T21:17:31.9756514Z     >>>     def resolve_data(self, write_item):
2025-08-14T21:17:31.9756650Z     >>>         item = super().resolve_data(write_item)
2025-08-14T21:17:31.9756923Z     >>>         return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16)
2025-08-14T21:17:31.9757001Z     
2025-08-14T21:17:31.9757356Z     Using the global planning step to make central decisions that can't be made individually by each rank
2025-08-14T21:17:31.9757436Z     
2025-08-14T21:17:31.9757547Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9757674Z     >>> from itertools import zip_longest
2025-08-14T21:17:31.9757784Z     >>> from dataclasses import replace
2025-08-14T21:17:31.9757952Z     >>> class DDPLoadBalancingPlanner(DefaultSavePlanner):
2025-08-14T21:17:31.9758242Z     >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0
2025-08-14T21:17:31.9758372Z     >>> # This sample doesn't handle ShardedTensors
2025-08-14T21:17:31.9758516Z     >>>     def create_global_plan(self, all_plans):
2025-08-14T21:17:31.9758667Z     >>>         iters = [iter(all_plans[0].items)] * len(all_plans)
2025-08-14T21:17:31.9758764Z     >>>         items_per_rank = [
2025-08-14T21:17:31.9758910Z     >>>             [item for item in items if item is not None]
2025-08-14T21:17:31.9759073Z     >>>             for items in zip(*zip_longest(*iters), strict=True)
2025-08-14T21:17:31.9759156Z     >>>         ]
2025-08-14T21:17:31.9759264Z     >>>         all_plans = [
2025-08-14T21:17:31.9759378Z     >>>             replace(plan, items=items)
2025-08-14T21:17:31.9759578Z     >>>             for plan, items in zip(all_plans, items_per_rank, strict=True)
2025-08-14T21:17:31.9759661Z     >>>         ]
2025-08-14T21:17:31.9759801Z     >>>         return super().create_global_plan(all_plans)
2025-08-14T21:17:31.9759893Z     
2025-08-14T21:17:31.9760156Z     Finally, some planners need to save additional metadata in the checkpoint, this is
2025-08-14T21:17:31.9760451Z     accomplished by having each rank contribute their data items in the local plan and
2025-08-14T21:17:31.9760575Z     the global planner aggregate them:
2025-08-14T21:17:31.9760654Z     
2025-08-14T21:17:31.9760765Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9760932Z     >>> class SaveExtraDataPlanner(DefaultSavePlanner):
2025-08-14T21:17:31.9761062Z     >>>     def create_local_plan(self) -> SavePlan:
2025-08-14T21:17:31.9761193Z     >>>         plan = super().create_local_plan()
2025-08-14T21:17:31.9761355Z     >>>         return replace(plan, planner_data="per-rank-data")
2025-08-14T21:17:31.9761434Z     >>>
2025-08-14T21:17:31.9761742Z     >>>     def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]:
2025-08-14T21:17:31.9761938Z     >>>         global_plan, metadata = super().create_global_plan(all_plans)
2025-08-14T21:17:31.9762091Z     >>>         merged_data = [p.planner_data for p in global_plan]
2025-08-14T21:17:31.9762276Z     >>>         metadata = replace(metadata, planner_data=merged_data)
2025-08-14T21:17:31.9762386Z     >>>         return global_plan, metadata
2025-08-14T21:17:31.9762465Z     
2025-08-14T21:17:31.9762730Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9762807Z     
2025-08-14T21:17:31.9762917Z       warnings.warn(msg)
2025-08-14T21:17:31.9762996Z     
2025-08-14T21:17:31.9763233Z --- Parse Warning: 67 / 146 ---
2025-08-14T21:17:31.9764235Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305.
2025-08-14T21:17:31.9764522Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9764601Z     
2025-08-14T21:17:31.9764901Z     Abstract class defining the protocol used by load_state_dict to plan the load process.
2025-08-14T21:17:31.9764982Z     
2025-08-14T21:17:31.9765287Z     LoadPlanner are stateful objects that can be used to customize the whole load process.
2025-08-14T21:17:31.9765367Z     
2025-08-14T21:17:31.9765645Z     LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-08-14T21:17:31.9765772Z     will be visible to the whole process.
2025-08-14T21:17:31.9765850Z     
2025-08-14T21:17:31.9766125Z     A planner subclass can expect the following sequence of calls during load_state_dict:
2025-08-14T21:17:31.9766220Z     
2025-08-14T21:17:31.9766337Z     1) set_up_planner - called on all ranks.
2025-08-14T21:17:31.9766468Z         Signals the start of loading a checkpoint.
2025-08-14T21:17:31.9766559Z     
2025-08-14T21:17:31.9766684Z     2) create_local_plan - called on all ranks.
2025-08-14T21:17:31.9766982Z         Process the state_dict and produces a `LoadPlan` that will be sent for global planning.
2025-08-14T21:17:31.9767060Z     
2025-08-14T21:17:31.9767242Z     3) create_global_plan - called on the coordinator rank only.
2025-08-14T21:17:31.9767453Z         Takes the LoadPlan from all ranks and make any global decision.
2025-08-14T21:17:31.9767534Z     
2025-08-14T21:17:31.9767680Z     4) load_bytes - called multiple times on each rank
2025-08-14T21:17:31.9767859Z         This is called once per non-tensor value in state_dict.
2025-08-14T21:17:31.9767937Z     
2025-08-14T21:17:31.9768161Z     5) resolve_tensor and commit_tensor - called multiple times on each rank
2025-08-14T21:17:31.9768356Z         They are called in pair for each Tensor value in state_dict.
2025-08-14T21:17:31.9768436Z     
2025-08-14T21:17:31.9768754Z     Users are recommended to extend DefaultLoadPlanner instead of this interface directly as
2025-08-14T21:17:31.9768933Z     most changes can be expressed by changes in a single method.
2025-08-14T21:17:31.9769012Z     
2025-08-14T21:17:31.9769150Z     There are two usual patterns of extension:
2025-08-14T21:17:31.9769230Z     
2025-08-14T21:17:31.9769506Z     Rewriting state_dict. This is the simplest way to extend the load process as it
2025-08-14T21:17:31.9769775Z     doesn't requite understanding the intrincacies of how LoadPlan works. We need
2025-08-14T21:17:31.9770001Z     to keep a reference to the original state_dict as load happens in place so
2025-08-14T21:17:31.9770124Z     we need to be able to perform it in place
2025-08-14T21:17:31.9770216Z     
2025-08-14T21:17:31.9770335Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9770485Z     >>> class RenamePlanner(DefaultLoadPlanner):
2025-08-14T21:17:31.9770582Z     >>>     def set_up_planner(
2025-08-14T21:17:31.9770663Z     >>>         self,
2025-08-14T21:17:31.9770790Z     >>>         state_dict: STATE_DICT_TYPE,
2025-08-14T21:17:31.9770889Z     >>>         metadata: Metadata,
2025-08-14T21:17:31.9770994Z     >>>         is_coordinator: bool,
2025-08-14T21:17:31.9771097Z     >>>     ) -> None:
2025-08-14T21:17:31.9771219Z     >>>         self.original_state_dict = state_dict
2025-08-14T21:17:31.9771394Z     >>>         state_dict = {"foo_" + k: v for k, v in state_dict.items()}
2025-08-14T21:17:31.9771486Z     >>>
2025-08-14T21:17:31.9771603Z     >>>         if self.flatten_sharded_tensors:
2025-08-14T21:17:31.9771768Z     >>>             state_dict = _flatten_sharded_tensors(state_dict)
2025-08-14T21:17:31.9771850Z     >>>
2025-08-14T21:17:31.9771958Z     >>>         if self.flatten_state_dict:
2025-08-14T21:17:31.9772211Z     >>>             state_dict, self.mappings = flatten_state_dict(state_dict)
2025-08-14T21:17:31.9772318Z     >>>
2025-08-14T21:17:31.9772425Z     >>>         self.state_dict = state_dict
2025-08-14T21:17:31.9772544Z     >>>         self.metadata = metadata
2025-08-14T21:17:31.9772667Z     >>>         self.is_coordinator = is_coordinator
2025-08-14T21:17:31.9772746Z     >>>
2025-08-14T21:17:31.9772878Z     >>>     def load_bytes(self, read_item, value):
2025-08-14T21:17:31.9772980Z     >>> # Remove the "foo_" prefix
2025-08-14T21:17:31.9773314Z     >>>         self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False)
2025-08-14T21:17:31.9773391Z     
2025-08-14T21:17:31.9773471Z     
2025-08-14T21:17:31.9773746Z     Modifying resolve_tensor and commit_tensor to handle load time transformation.
2025-08-14T21:17:31.9773825Z     
2025-08-14T21:17:31.9773940Z     >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:31.9774108Z     >>> class MetaModelMaterialize(DefaultSavePlanner):
2025-08-14T21:17:31.9774224Z     >>>     def resolve_tensor(self, read_item):
2025-08-14T21:17:31.9774357Z     >>>         tensor = super().resolve_tensor(read_item)
2025-08-14T21:17:31.9774513Z     >>>         return torch.empty_like(tensor, device="cpu")
2025-08-14T21:17:31.9774592Z     >>>
2025-08-14T21:17:31.9774720Z     >>>     def commit_tensor(self, read_item, tensor):
2025-08-14T21:17:31.9774886Z     >>>         self.state_dict[read_item.dest_index.fqn] = tensor
2025-08-14T21:17:31.9774966Z     
2025-08-14T21:17:31.9775233Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9775310Z     
2025-08-14T21:17:31.9775404Z       warnings.warn(msg)
2025-08-14T21:17:31.9775492Z     
2025-08-14T21:17:31.9775681Z --- Parse Warning: 68 / 146 ---
2025-08-14T21:17:31.9776658Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118.
2025-08-14T21:17:31.9776936Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9777016Z     
2025-08-14T21:17:31.9777190Z     Return the model state_dict and optimizers state_dict.
2025-08-14T21:17:31.9777267Z     
2025-08-14T21:17:31.9777484Z     ``get_state_dict`` can process any module that is parallelized by PyTorch
2025-08-14T21:17:31.9777745Z     FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any
2025-08-14T21:17:31.9778018Z     combination of these parallelisms. The main functions of ``get_state_dict``
2025-08-14T21:17:31.9778234Z     are: 1.) returning a model and optimizer state_dict that can be resharded
2025-08-14T21:17:31.9778455Z     with a different number of trainers and/or different parallelisms.
2025-08-14T21:17:31.9778703Z     2.) hiding the parallelism-specific state_dict APIs. Users don't have to call
2025-08-14T21:17:31.9778808Z     these APIs.
2025-08-14T21:17:31.9778932Z     3.) sanity checking the result state_dict.
2025-08-14T21:17:31.9779013Z     
2025-08-14T21:17:31.9779237Z     The keys of the result state dictionary are the canonical FQNs (Fully
2025-08-14T21:17:31.9779473Z     Qualified Names).  A canonical FQN refers to the FQN based on a parameter's
2025-08-14T21:17:31.9779706Z     position in an nn.Module hierarchy. More specifically, a canonical FQN to a
2025-08-14T21:17:31.9779922Z     parameter is the FQN returned by ``module.named_parameters()`` or
2025-08-14T21:17:31.9780133Z     ``module.named_buffers()`` when the module is not distributed by any
2025-08-14T21:17:31.9780397Z     parallelisms. Since the optimizer internally uses parameter IDs to represent
2025-08-14T21:17:31.9780610Z     a parameter, there will be a conversion from the parameter IDs to the
2025-08-14T21:17:31.9780724Z     canonical FQNs when calling this API.
2025-08-14T21:17:31.9780818Z     
2025-08-14T21:17:31.9781084Z     ``get_state_dict`` can also process a module that is not parallelized. In
2025-08-14T21:17:31.9781382Z     such a case, ``get_state_dict`` only performs one function -- converting the
2025-08-14T21:17:31.9781538Z     optimizer parameter IDs to the canonical FQNs.
2025-08-14T21:17:31.9781618Z     
2025-08-14T21:17:31.9781703Z     Example:
2025-08-14T21:17:31.9781813Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9781903Z         >>> import torch
2025-08-14T21:17:31.9782139Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:31.9782354Z         >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-08-14T21:17:31.9782577Z         >>> from torch.distributed.checkpoint.state_dict import get_state_dict
2025-08-14T21:17:31.9782669Z     
2025-08-14T21:17:31.9782796Z         >>> fsdp_model = FSDP(copy.deepcopy(model))
2025-08-14T21:17:31.9782978Z         >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-08-14T21:17:31.9783116Z         >>> ddp_model = DDP(copy.deepcopy(model))
2025-08-14T21:17:31.9783298Z         >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-08-14T21:17:31.9783380Z     
2025-08-14T21:17:31.9783472Z     
2025-08-14T21:17:31.9783706Z         >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim)
2025-08-14T21:17:31.9783888Z         >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict(
2025-08-14T21:17:31.9783989Z         ...     fsdp_model, fsdp_optim
2025-08-14T21:17:31.9784072Z         ... )
2025-08-14T21:17:31.9784164Z     
2025-08-14T21:17:31.9784378Z         >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(),
2025-08-14T21:17:31.9784484Z         >>> # the asserts will fail.
2025-08-14T21:17:31.9784623Z         >>> assert ddp_state_dict == fsdp_state_dict
2025-08-14T21:17:31.9784767Z         >>> assert ddp_optim_state == fsdp_optim_state_dict
2025-08-14T21:17:31.9784847Z     
2025-08-14T21:17:31.9784935Z     
2025-08-14T21:17:31.9785018Z     Args:
2025-08-14T21:17:31.9785164Z         model (nn.Module): the nn.Module to the model.
2025-08-14T21:17:31.9785364Z         optimizers (Union[None, Optimizer, Iterable[Optimizer]]):
2025-08-14T21:17:31.9785521Z             The optimizers that are used to optimize ``model``.
2025-08-14T21:17:31.9785811Z         submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters
2025-08-14T21:17:31.9785922Z             that belong to the submodules.
2025-08-14T21:17:31.9786093Z         options (StateDictOptions): the options to control how
2025-08-14T21:17:31.9786337Z             model state_dict and optimizer state_dict should be returned. See
2025-08-14T21:17:31.9786461Z             `StateDictOptions` for the details.
2025-08-14T21:17:31.9786539Z     
2025-08-14T21:17:31.9786636Z     Returns:
2025-08-14T21:17:31.9786834Z         ``Tuple`` that contain model state_dict and optimizer state_dict.
2025-08-14T21:17:31.9786925Z     
2025-08-14T21:17:31.9787153Z     :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType]
2025-08-14T21:17:31.9787237Z     
2025-08-14T21:17:31.9787502Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9787581Z     
2025-08-14T21:17:31.9787678Z       warnings.warn(msg)
2025-08-14T21:17:31.9787770Z     
2025-08-14T21:17:31.9787960Z --- Parse Warning: 69 / 146 ---
2025-08-14T21:17:31.9788933Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69.
2025-08-14T21:17:31.9789204Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9789282Z     
2025-08-14T21:17:31.9789492Z     Load a checkpoint into a distributed state dict in SPMD style.
2025-08-14T21:17:31.9789573Z     
2025-08-14T21:17:31.9789823Z     Each rank must have the same keys in their ``state_dict`` provided to this
2025-08-14T21:17:31.9790092Z     API. Mismatched keys may result in hangs or errors. If unsure, you can use
2025-08-14T21:17:31.9790336Z     the ``utils._assert_same_keys`` API to check (but may incur communication
2025-08-14T21:17:31.9790418Z     costs).
2025-08-14T21:17:31.9790506Z     
2025-08-14T21:17:31.9790684Z     Each rank will try to read the least amount of data necessary
2025-08-14T21:17:31.9790914Z     to fulfill the requested `state_dict`. When loading :class:`ShardedTensor`
2025-08-14T21:17:31.9791170Z     or :class:`DTensor` instances, each rank only reads data for their local shards.
2025-08-14T21:17:31.9791249Z     
2025-08-14T21:17:31.9791610Z     For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-08-14T21:17:31.9791865Z     load will first call ``state_dict`` before attempting deserialization, followed by
2025-08-14T21:17:31.9792033Z     ``load_state_dict`` once the deserialization is complete.
2025-08-14T21:17:31.9792307Z     For each non-``Stateful`` object, load will deserialize the object, and then replace
2025-08-14T21:17:31.9792462Z     it in the ``state_dict`` with the deserialized object.
2025-08-14T21:17:31.9792543Z     
2025-08-14T21:17:31.9792656Z     .. warning::
2025-08-14T21:17:31.9792822Z         All tensors in ``state_dict`` must be allocated on their
2025-08-14T21:17:31.9792997Z         destination device *prior to* calling this function.
2025-08-14T21:17:31.9793073Z     
2025-08-14T21:17:31.9793297Z         All non-tensor data is loaded using `torch.load()` and modified in place
2025-08-14T21:17:31.9793398Z         on state_dict.
2025-08-14T21:17:31.9793477Z     
2025-08-14T21:17:31.9793562Z     .. warning::
2025-08-14T21:17:31.9793777Z         Users must call `load_state_dict` on the root module to ensure load
2025-08-14T21:17:31.9793957Z         pos-processing and non-tensor data properly propagates.
2025-08-14T21:17:31.9794040Z     
2025-08-14T21:17:31.9794134Z     .. note:
2025-08-14T21:17:31.9794358Z         If no process group is initialized, this function will assume the intent
2025-08-14T21:17:31.9794595Z         is to load a checkpoint into the local process. This can be useful in the
2025-08-14T21:17:31.9794842Z         case of local inference, and when using regular Tensors (as opposed to DTensor
2025-08-14T21:17:31.9794939Z          or ShardedTensor)
2025-08-14T21:17:31.9795028Z     
2025-08-14T21:17:31.9795107Z     .. note:
2025-08-14T21:17:31.9795241Z         Rank 0 is assumed to be the coordinator rank.
2025-08-14T21:17:31.9795323Z     
2025-08-14T21:17:31.9795415Z     Args:
2025-08-14T21:17:31.9795658Z         state_dict (Dict[str, Any]): The state_dict to load the checkpoint into.
2025-08-14T21:17:31.9795813Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:31.9796021Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:31.9796220Z             depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:31.9796396Z             It can also be a key if the storage is a key-value store.
2025-08-14T21:17:31.9796496Z             (Default: ``None``)
2025-08-14T21:17:31.9796624Z         storage_reader (Optional[StorageReader]):
2025-08-14T21:17:31.9796839Z             Instance of StorageWriter used to perform reads. If this is not
2025-08-14T21:17:31.9797038Z             specified, DCP will automatically infer the reader based on the
2025-08-14T21:17:31.9797245Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:31.9797352Z             be raised. (Default: ``None``)
2025-08-14T21:17:31.9797468Z         planner (Optional[LoadPlanner]):
2025-08-14T21:17:31.9797670Z             Instance of LoadPlanner. If this is not specified, the default
2025-08-14T21:17:31.9797798Z             planner will be used. (Default: ``None``)
2025-08-14T21:17:31.9797925Z         process_group (Optional[ProcessGroup]):
2025-08-14T21:17:31.9798121Z             ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:31.9798269Z             (Default: ``None``)
2025-08-14T21:17:31.9798512Z         no_dist (bool): If ``True``, this function will assume the intent is to load
2025-08-14T21:17:31.9798759Z             a checkpoint without using cross-rank synchronization. (Default: ``False``)
2025-08-14T21:17:31.9798846Z     Returns:
2025-08-14T21:17:31.9798939Z         None.
2025-08-14T21:17:31.9799019Z     
2025-08-14T21:17:31.9799102Z     Examples
2025-08-14T21:17:31.9799204Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9799303Z         >>> my_model = MyModule()
2025-08-14T21:17:31.9799444Z         >>> optimizer = Adagrad(my_model.parameters())
2025-08-14T21:17:31.9799583Z         >>> model_state_dict = my_model.state_dict()
2025-08-14T21:17:31.9799815Z         >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader(
2025-08-14T21:17:31.9799908Z         ...     "/checkpoint/1"
2025-08-14T21:17:31.9799999Z         ... )
2025-08-14T21:17:31.9800075Z     
2025-08-14T21:17:31.9800238Z         >>> torch.distributed.checkpoint.load_state_dict(
2025-08-14T21:17:31.9800352Z         >>>     state_dict=model_state_dict,
2025-08-14T21:17:31.9800469Z         >>>     storage_reader=fs_storage_reader,
2025-08-14T21:17:31.9800556Z         >>> )
2025-08-14T21:17:31.9800635Z     
2025-08-14T21:17:31.9800826Z         >>> # module.load_state_dict() function might have customized steps
2025-08-14T21:17:31.9800962Z         >>> # to flush the state_dict, must call it to
2025-08-14T21:17:31.9801066Z         >>> # ensure correct behavior.
2025-08-14T21:17:31.9801193Z         >>> my_model.load_state_dict(model_state_dict)
2025-08-14T21:17:31.9801284Z     
2025-08-14T21:17:31.9801368Z     .. note::
2025-08-14T21:17:31.9801584Z         load_state_dict uses collectives to coordinate reads across ranks.
2025-08-14T21:17:31.9801795Z         For NCCL-based process groups, internal tensor representations of
2025-08-14T21:17:31.9802021Z         objects must be moved to the GPU device before communication takes place.
2025-08-14T21:17:31.9802251Z         In this case, the device used is given by ``torch.cuda.current_device()``
2025-08-14T21:17:31.9802480Z         and it is the user's responsibility to ensure that this is set so that each
2025-08-14T21:17:31.9802663Z         rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-08-14T21:17:31.9802755Z     
2025-08-14T21:17:31.9803005Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9803096Z     
2025-08-14T21:17:31.9803191Z       warnings.warn(msg)
2025-08-14T21:17:31.9803270Z     
2025-08-14T21:17:31.9803517Z --- Parse Warning: 70 / 146 ---
2025-08-14T21:17:31.9804479Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97.
2025-08-14T21:17:31.9804740Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9804835Z     
2025-08-14T21:17:31.9804956Z     Save a distributed model in SPMD style.
2025-08-14T21:17:31.9805036Z     
2025-08-14T21:17:31.9805241Z     This function is different from ``torch.save()`` as it handles
2025-08-14T21:17:31.9805496Z     ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards.
2025-08-14T21:17:31.9805589Z     
2025-08-14T21:17:31.9805846Z     For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-08-14T21:17:31.9805994Z     save will call ``state_dict`` before serialization.
2025-08-14T21:17:31.9806087Z     
2025-08-14T21:17:31.9806177Z     .. warning::
2025-08-14T21:17:31.9806409Z         There is no guarantees of Backwards Compatibility across PyTorch versions
2025-08-14T21:17:31.9806520Z         for saved state_dicts.
2025-08-14T21:17:31.9806599Z     
2025-08-14T21:17:31.9806684Z     .. warning::
2025-08-14T21:17:31.9806929Z         If using the `process_group` argument, make sure that only its ranks
2025-08-14T21:17:31.9807155Z         call `save_state_dict` and that all data in state_dict belong to it.
2025-08-14T21:17:31.9807271Z     
2025-08-14T21:17:31.9807354Z     .. note::
2025-08-14T21:17:31.9807605Z         When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of
2025-08-14T21:17:31.9807876Z         the shard_group should be calling `save_state_dict` and the corresponding process
2025-08-14T21:17:31.9807984Z         group needs to be passed in.
2025-08-14T21:17:31.9808061Z     
2025-08-14T21:17:31.9808156Z     .. note::
2025-08-14T21:17:31.9808427Z         If no process group is available, this function assumes the intention is to save the
2025-08-14T21:17:31.9808536Z          state_dict in the local process.
2025-08-14T21:17:31.9808626Z     
2025-08-14T21:17:31.9808707Z     .. note:
2025-08-14T21:17:31.9808854Z         Rank 0 is assumed to be the coordinator rank.
2025-08-14T21:17:31.9808932Z     
2025-08-14T21:17:31.9809236Z     
2025-08-14T21:17:31.9809337Z     Args:
2025-08-14T21:17:31.9809493Z         state_dict (Dict[str, Any]): The state_dict to save.
2025-08-14T21:17:31.9809640Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:31.9809864Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:31.9810063Z             depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:31.9810227Z             It can also be a key if the storage is a key-value store.
2025-08-14T21:17:31.9810337Z             (Default: ``None``)
2025-08-14T21:17:31.9810467Z         storage_writer (Optional[StorageWriter]):
2025-08-14T21:17:31.9810689Z             Instance of StorageWriter used to perform writes. If this is not
2025-08-14T21:17:31.9810888Z             specified, DCP will automatically infer the writer based on the
2025-08-14T21:17:31.9811087Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:31.9811207Z             be raised. (Default: ``None``)
2025-08-14T21:17:31.9811322Z         planner (Optional[SavePlanner]):
2025-08-14T21:17:31.9811522Z             Instance of SavePlanner. If this is not specified, the default
2025-08-14T21:17:31.9811658Z             planner will be used. (Default: ``None``)
2025-08-14T21:17:31.9811785Z         process_group (Optional[ProcessGroup]):
2025-08-14T21:17:31.9811981Z             ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:31.9812079Z             (Default: ``None``)
2025-08-14T21:17:31.9812168Z         no_dist (bool):
2025-08-14T21:17:31.9812441Z             If ``True``, this function will assume the intent is to load
2025-08-14T21:17:31.9812565Z             a checkpoint on a single rank/process.
2025-08-14T21:17:31.9812662Z             (Default: ``False``)
2025-08-14T21:17:31.9812930Z         use_collectives (bool): If ``False``, this function will assume the intent is to save
2025-08-14T21:17:31.9813103Z             a checkpoint without using cross-rank synchronization.
2025-08-14T21:17:31.9813203Z             (Default: ``True``)
2025-08-14T21:17:31.9813440Z             This configuration is experimental and should be used with caution.
2025-08-14T21:17:31.9813708Z             It will change the format of the saved checkpoint and may not be backward compatible.
2025-08-14T21:17:31.9813802Z     
2025-08-14T21:17:31.9813884Z     Returns:
2025-08-14T21:17:31.9814040Z         Metadata: Metadata object for the saved checkpoint.
2025-08-14T21:17:31.9814130Z     
2025-08-14T21:17:31.9814211Z     Example:
2025-08-14T21:17:31.9814309Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9814421Z         >>> my_model = MyModule()
2025-08-14T21:17:31.9814499Z     
2025-08-14T21:17:31.9814612Z         >>> state_dict = {"model": my_model}
2025-08-14T21:17:31.9814703Z     
2025-08-14T21:17:31.9814935Z         >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-08-14T21:17:31.9815031Z         ...     "/checkpoint/1"
2025-08-14T21:17:31.9815120Z         ... )
2025-08-14T21:17:31.9815288Z         >>> torch.distributed.checkpoint.save(
2025-08-14T21:17:31.9815474Z         >>>     state_dict=state_dict,
2025-08-14T21:17:31.9815591Z         >>>     storage_writer=fs_storage_writer,
2025-08-14T21:17:31.9815672Z         >>> )
2025-08-14T21:17:31.9815762Z     
2025-08-14T21:17:31.9815846Z     .. note::
2025-08-14T21:17:31.9816058Z         save_state_dict uses collectives to coordinate writes across ranks.
2025-08-14T21:17:31.9816282Z         For NCCL-based process groups, internal tensor representations of
2025-08-14T21:17:31.9816511Z         objects must be moved to the GPU device before communication takes place.
2025-08-14T21:17:31.9816730Z         In this case, the device used is given by ``torch.cuda.current_device()``
2025-08-14T21:17:31.9816949Z         and it is the user's responsibility to ensure that this is set so that
2025-08-14T21:17:31.9817146Z         each rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-08-14T21:17:31.9817241Z     
2025-08-14T21:17:31.9817495Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9817579Z     
2025-08-14T21:17:31.9817690Z       warnings.warn(msg)
2025-08-14T21:17:31.9817769Z     
2025-08-14T21:17:31.9817981Z --- Parse Warning: 71 / 146 ---
2025-08-14T21:17:31.9818993Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230.
2025-08-14T21:17:31.9819260Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9819540Z     Asynchronous version of ``save``. This code first de-stages the state_dict on to the
2025-08-14T21:17:31.9819826Z         staging storage (defaults to CPU memory), and then calls the `save` in a separate thread.
2025-08-14T21:17:31.9819906Z     
2025-08-14T21:17:31.9820008Z         .. warning::
2025-08-14T21:17:31.9820167Z             This feature is experimental and subject to change.
2025-08-14T21:17:31.9820314Z             MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED
2025-08-14T21:17:31.9820406Z     
2025-08-14T21:17:31.9820485Z         Args:
2025-08-14T21:17:31.9820639Z             state_dict (Dict[str, Any]): The state_dict to save.
2025-08-14T21:17:31.9820796Z             checkpoint_id (Union[str, os.PathLike, None]):
2025-08-14T21:17:31.9821005Z                 The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-08-14T21:17:31.9821247Z                 depends on the storage. It can be a path to a folder or to a file.
2025-08-14T21:17:31.9821413Z                 It can also be a key if the storage is a key-value store.
2025-08-14T21:17:31.9821512Z                 (Default: ``None``)
2025-08-14T21:17:31.9821657Z             storage_writer (Optional[StorageWriter]):
2025-08-14T21:17:31.9821871Z                 Instance of StorageWriter used to perform 'stage' and  'save'. If
2025-08-14T21:17:31.9822122Z                 this is not specified, DCP will automatically infer the writer based on the
2025-08-14T21:17:31.9822327Z                 checkpoint_id. If checkpoint_id is also None, an exception will
2025-08-14T21:17:31.9822439Z                 be raised. (Default: ``None``)
2025-08-14T21:17:31.9822568Z             planner (Optional[SavePlanner]):
2025-08-14T21:17:31.9822763Z                 Instance of SavePlanner. If this is not specified, the default
2025-08-14T21:17:31.9822894Z                 planner will be used. (Default: ``None``)
2025-08-14T21:17:31.9823039Z             process_group (Optional[ProcessGroup]):
2025-08-14T21:17:31.9823220Z                 ProcessGroup to be used for cross-rank synchronization.
2025-08-14T21:17:31.9823320Z                 (Default: ``None``)
2025-08-14T21:17:31.9823490Z             async_checkpointer_type (AsyncCheckpointerType):
2025-08-14T21:17:31.9823658Z                 whether to do checkpoint in separate thread or process
2025-08-14T21:17:31.9823843Z                 (Default: ``AsyncCheckpointerType.THREAD``)
2025-08-14T21:17:31.9824001Z             async_stager (AsyncStager):
2025-08-14T21:17:31.9824257Z                 provides staging implementation. If storage_writer implements AsyncStager
2025-08-14T21:17:31.9824482Z                 and async_stager is provided, async_stager will be used for staging
2025-08-14T21:17:31.9824577Z             no_dist (bool):
2025-08-14T21:17:31.9824747Z                 If ``True``, this function will assume the intent is to save
2025-08-14T21:17:31.9824890Z                 a checkpoint on a single rank/process.
2025-08-14T21:17:31.9824994Z                 (Default: ``False``)
2025-08-14T21:17:31.9825320Z             use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``)
2025-08-14T21:17:31.9825542Z                 This configuration is experimental and should be used with caution.
2025-08-14T21:17:31.9825816Z                 It will change the format of the saved checkpoint and may not be backward compatible.
2025-08-14T21:17:31.9825911Z     
2025-08-14T21:17:31.9825997Z         Returns:
2025-08-14T21:17:31.9826210Z             Future: A future holding the resultant Metadata object from `save`.
2025-08-14T21:17:31.9826301Z     
2025-08-14T21:17:31.9826386Z         Example:
2025-08-14T21:17:31.9826486Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9826599Z             >>> my_model = MyModule()
2025-08-14T21:17:31.9826676Z     
2025-08-14T21:17:31.9826800Z             >>> state_dict = {"model": my_model}
2025-08-14T21:17:31.9826877Z     
2025-08-14T21:17:31.9827111Z             >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-08-14T21:17:31.9827220Z             ...     "/checkpoint/1"
2025-08-14T21:17:31.9827302Z             ... )
2025-08-14T21:17:31.9827514Z             >>> checkpoint_future = torch.distributed.checkpoint.async_save(
2025-08-14T21:17:31.9827632Z             >>>     state_dict=state_dict,
2025-08-14T21:17:31.9827755Z             >>>     storage_writer=fs_storage_writer,
2025-08-14T21:17:31.9827841Z             >>> )
2025-08-14T21:17:31.9827934Z             >>>
2025-08-14T21:17:31.9828033Z             >>> # ... do some work ...
2025-08-14T21:17:31.9828125Z             >>>
2025-08-14T21:17:31.9828234Z             >>> checkpoint_future.result()
2025-08-14T21:17:31.9828311Z     
2025-08-14T21:17:31.9828406Z         
2025-08-14T21:17:31.9828659Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9828739Z     
2025-08-14T21:17:31.9828847Z       warnings.warn(msg)
2025-08-14T21:17:31.9828927Z     
2025-08-14T21:17:31.9829147Z --- Parse Warning: 72 / 146 ---
2025-08-14T21:17:31.9830213Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94.
2025-08-14T21:17:31.9830479Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9830576Z     
2025-08-14T21:17:31.9830775Z     Initialize rendezvous event object and record its operations.
2025-08-14T21:17:31.9830852Z     
2025-08-14T21:17:31.9830946Z     Args:
2025-08-14T21:17:31.9831073Z         run_id (str): The run id of the rendezvous.
2025-08-14T21:17:31.9831218Z         message (str): The message describing the event.
2025-08-14T21:17:31.9831564Z         node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED).
2025-08-14T21:17:31.9831750Z         name (str): Event name. (E.g. Current action being performed).
2025-08-14T21:17:31.9831865Z         hostname (str): Hostname of the node.
2025-08-14T21:17:31.9832019Z         pid (Optional[int]): The process id of the node.
2025-08-14T21:17:31.9832262Z         master_endpoint (str): The master endpoint for the rendezvous store, if known.
2025-08-14T21:17:31.9832573Z         local_id (Optional[int]):  The local_id of the node, if defined in dynamic_rendezvous.py
2025-08-14T21:17:31.9832761Z         rank (Optional[int]): The rank of the node, if known.
2025-08-14T21:17:31.9832873Z     Returns:
2025-08-14T21:17:31.9832967Z         None
2025-08-14T21:17:31.9833050Z     Example:
2025-08-14T21:17:31.9833176Z         >>> # See DynamicRendezvousHandler class
2025-08-14T21:17:31.9833280Z         >>> def _record(
2025-08-14T21:17:31.9833362Z         ...     self,
2025-08-14T21:17:31.9833455Z         ...     message: str,
2025-08-14T21:17:31.9833605Z         ...     node_state: NodeState = NodeState.RUNNING,
2025-08-14T21:17:31.9833713Z         ...     rank: Optional[int] = None,
2025-08-14T21:17:31.9833813Z         ... ) -> None:
2025-08-14T21:17:31.9833932Z         ...     construct_and_record_rdzv_event(
2025-08-14T21:17:31.9834097Z         ...         name=f"{self.__class__.__name__}.{get_method_name()}",
2025-08-14T21:17:31.9834227Z         ...         run_id=self._settings.run_id,
2025-08-14T21:17:31.9834326Z         ...         message=message,
2025-08-14T21:17:31.9834429Z         ...         node_state=node_state,
2025-08-14T21:17:31.9834559Z         ...         hostname=self._this_node.addr,
2025-08-14T21:17:31.9834664Z         ...         pid=self._this_node.pid,
2025-08-14T21:17:31.9834790Z         ...         local_id=self._this_node.local_id,
2025-08-14T21:17:31.9834892Z         ...         rank=rank,
2025-08-14T21:17:31.9834972Z         ...     )
2025-08-14T21:17:31.9835062Z     
2025-08-14T21:17:31.9835317Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9835396Z     
2025-08-14T21:17:31.9835507Z       warnings.warn(msg)
2025-08-14T21:17:31.9835584Z     
2025-08-14T21:17:31.9835780Z --- Parse Warning: 73 / 146 ---
2025-08-14T21:17:31.9836714Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114.
2025-08-14T21:17:31.9836975Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9837055Z     
2025-08-14T21:17:31.9837231Z     This configures FSDP-native mixed precision training.
2025-08-14T21:17:31.9837309Z     
2025-08-14T21:17:31.9837408Z     Attributes:
2025-08-14T21:17:31.9837639Z         param_dtype (Optional[torch.dtype]): This specifies the dtype for model
2025-08-14T21:17:31.9837837Z             parameters during forward and backward and thus the dtype for
2025-08-14T21:17:31.9838096Z             forward and backward computation. Outside forward and backward, the
2025-08-14T21:17:31.9838286Z             *sharded* parameters are kept in full precision (e.g. for the
2025-08-14T21:17:31.9838489Z             optimizer step), and for model checkpointing, the parameters are
2025-08-14T21:17:31.9838663Z             always saved in full precision. (Default: ``None``)
2025-08-14T21:17:31.9838874Z         reduce_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-08-14T21:17:31.9839101Z             gradient reduction (i.e. reduce-scatter or all-reduce). If this is
2025-08-14T21:17:31.9839277Z             ``None`` but ``param_dtype`` is not ``None``, then this takes on
2025-08-14T21:17:31.9839472Z             the ``param_dtype`` value, still running gradient reduction in low
2025-08-14T21:17:31.9839690Z             precision. This is permitted to differ from ``param_dtype``, e.g.
2025-08-14T21:17:31.9839884Z             to force gradient reduction to run in full precision. (Default:
2025-08-14T21:17:31.9839969Z             ``None``)
2025-08-14T21:17:31.9840194Z         buffer_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-08-14T21:17:31.9840392Z             buffers. FSDP does not shard buffers. Rather, FSDP casts them to
2025-08-14T21:17:31.9840600Z             ``buffer_dtype`` in the first forward pass and keeps them in that
2025-08-14T21:17:31.9840830Z             dtype thereafter. For model checkpointing, the buffers are saved
2025-08-14T21:17:31.9841036Z             in full precision except for ``LOCAL_STATE_DICT``. (Default:
2025-08-14T21:17:31.9841171Z             ``None``)
2025-08-14T21:17:31.9841364Z         keep_low_precision_grads (bool): If ``False``, then FSDP upcasts
2025-08-14T21:17:31.9841579Z             gradients to full precision after the backward pass in preparation
2025-08-14T21:17:31.9841794Z             for the optimizer step. If ``True``, then FSDP keeps the gradients
2025-08-14T21:17:31.9841990Z             in the dtype used for gradient reduction, which can save memory if
2025-08-14T21:17:31.9842206Z             using a custom optimizer that supports running in low precision.
2025-08-14T21:17:31.9842302Z             (Default: ``False``)
2025-08-14T21:17:31.9842508Z         cast_forward_inputs (bool): If ``True``, then this FSDP module casts
2025-08-14T21:17:31.9842719Z             its forward args and kwargs to ``param_dtype``. This is to ensure
2025-08-14T21:17:31.9842930Z             that parameter and input dtypes match for forward computation, as
2025-08-14T21:17:31.9843134Z             required by many ops. This may need to be set to ``True`` when only
2025-08-14T21:17:31.9843363Z             applying mixed precision to some but not all FSDP modules, in which
2025-08-14T21:17:31.9843569Z             case a mixed-precision FSDP submodule needs to recast its inputs.
2025-08-14T21:17:31.9843676Z             (Default: ``False``)
2025-08-14T21:17:31.9843891Z         cast_root_forward_inputs (bool): If ``True``, then the root FSDP module
2025-08-14T21:17:31.9844089Z             casts its forward args and kwargs to ``param_dtype``, overriding
2025-08-14T21:17:31.9844285Z             the value of ``cast_forward_inputs``. For non-root FSDP modules,
2025-08-14T21:17:31.9844425Z             this does not do anything. (Default: ``True``)
2025-08-14T21:17:31.9844641Z         _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies
2025-08-14T21:17:31.9844840Z             module classes to ignore for mixed precision when using an
2025-08-14T21:17:31.9845018Z             ``auto_wrap_policy``: Modules of these classes will have FSDP
2025-08-14T21:17:31.9845241Z             applied to them separately with mixed precision disabled (meaning
2025-08-14T21:17:31.9845443Z             that the final FSDP construction would deviate from the specified
2025-08-14T21:17:31.9845628Z             policy). If ``auto_wrap_policy`` is not specified, then this does
2025-08-14T21:17:31.9845835Z             not do anything. This API is experimental and subject to change.
2025-08-14T21:17:31.9845969Z             (Default: ``(_BatchNorm,)``)
2025-08-14T21:17:31.9846050Z     
2025-08-14T21:17:31.9846229Z     .. note:: This API is experimental and subject to change.
2025-08-14T21:17:31.9846306Z     
2025-08-14T21:17:31.9846536Z     .. note:: Only floating point tensors are cast to their specified dtypes.
2025-08-14T21:17:31.9846615Z     
2025-08-14T21:17:31.9846792Z     .. note:: In ``summon_full_params``, parameters are forced to full
2025-08-14T21:17:31.9846912Z         precision, but buffers are not.
2025-08-14T21:17:31.9846992Z     
2025-08-14T21:17:31.9847190Z     .. note:: Layer norm and batch norm accumulate in ``float32`` even when
2025-08-14T21:17:31.9847408Z         their inputs are in a low precision like ``float16`` or ``bfloat16``.
2025-08-14T21:17:31.9847636Z         Disabling FSDP's mixed precision for those norm modules only means that
2025-08-14T21:17:31.9847858Z         the affine parameters are kept in ``float32``. However, this incurs
2025-08-14T21:17:31.9848094Z         separate all-gathers and reduce-scatters for those norm modules, which
2025-08-14T21:17:31.9848310Z         may be inefficient, so if the workload permits, the user should prefer
2025-08-14T21:17:31.9848470Z         to still apply mixed precision to those modules.
2025-08-14T21:17:31.9848549Z     
2025-08-14T21:17:31.9848749Z     .. note:: By default, if the user passes a model with any ``_BatchNorm``
2025-08-14T21:17:31.9848989Z         modules and specifies an ``auto_wrap_policy``, then the batch norm
2025-08-14T21:17:31.9849262Z         modules will have FSDP applied to them separately with mixed precision
2025-08-14T21:17:31.9849446Z         disabled. See the ``_module_classes_to_ignore`` argument.
2025-08-14T21:17:31.9849525Z     
2025-08-14T21:17:31.9849730Z     .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and
2025-08-14T21:17:31.9849952Z         ``cast_forward_inputs=False`` by default. For the root FSDP instance,
2025-08-14T21:17:31.9850123Z         its ``cast_root_forward_inputs`` takes precedence over its
2025-08-14T21:17:31.9850298Z         ``cast_forward_inputs``. For non-root FSDP instances, their
2025-08-14T21:17:31.9850525Z         ``cast_root_forward_inputs`` values are ignored. The default setting is
2025-08-14T21:17:31.9850746Z         sufficient for the typical case where each FSDP instance has the same
2025-08-14T21:17:31.9850984Z         ``MixedPrecision`` configuration and only needs to cast inputs to the
2025-08-14T21:17:31.9851167Z         ``param_dtype`` at the beginning of the model's forward pass.
2025-08-14T21:17:31.9851248Z     
2025-08-14T21:17:31.9851462Z     .. note:: For nested FSDP instances with different ``MixedPrecision``
2025-08-14T21:17:31.9851699Z         configurations, we recommend setting individual ``cast_forward_inputs``
2025-08-14T21:17:31.9851901Z         values to configure casting inputs or not before each instance's
2025-08-14T21:17:31.9852101Z         forward. In such a case, since the casts happen before each FSDP
2025-08-14T21:17:31.9852316Z         instance's forward, a parent FSDP instance should have its non-FSDP
2025-08-14T21:17:31.9852554Z         submodules run before its FSDP submodules to avoid the activation dtype
2025-08-14T21:17:31.9852764Z         being changed due to a different ``MixedPrecision`` configuration.
2025-08-14T21:17:31.9852845Z     
2025-08-14T21:17:31.9852942Z         Example::
2025-08-14T21:17:31.9853021Z     
2025-08-14T21:17:31.9853152Z             >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9853333Z             >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3))
2025-08-14T21:17:31.9853430Z             >>> model[1] = FSDP(
2025-08-14T21:17:31.9853531Z             >>>     model[1],
2025-08-14T21:17:31.9853836Z             >>>     mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True),
2025-08-14T21:17:31.9853917Z             >>> )
2025-08-14T21:17:31.9854019Z             >>> model = FSDP(
2025-08-14T21:17:31.9854104Z             >>>     model,
2025-08-14T21:17:31.9854436Z             >>>     mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True),
2025-08-14T21:17:31.9854531Z             >>> )
2025-08-14T21:17:31.9854609Z     
2025-08-14T21:17:31.9854819Z         The above shows a working example. On the other hand, if ``model[1]``
2025-08-14T21:17:31.9855029Z         were replaced with ``model[0]``, meaning that the submodule using
2025-08-14T21:17:31.9855255Z         different ``MixedPrecision`` ran its forward first, then ``model[1]``
2025-08-14T21:17:31.9855480Z         would incorrectly see ``float16`` activations instead of ``bfloat16``
2025-08-14T21:17:31.9855584Z         ones.
2025-08-14T21:17:31.9855662Z     
2025-08-14T21:17:31.9855741Z     
2025-08-14T21:17:31.9856001Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9856080Z     
2025-08-14T21:17:31.9856175Z       warnings.warn(msg)
2025-08-14T21:17:31.9856263Z     
2025-08-14T21:17:31.9856459Z --- Parse Warning: 74 / 146 ---
2025-08-14T21:17:31.9857420Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295.
2025-08-14T21:17:31.9857682Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9857759Z     
2025-08-14T21:17:31.9858031Z     ``FullStateDictConfig`` is a config class meant to be used with
2025-08-14T21:17:31.9858250Z     ``StateDictType.FULL_STATE_DICT``. We recommend enabling both
2025-08-14T21:17:31.9858451Z     ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state
2025-08-14T21:17:31.9858677Z     dicts to save GPU memory and CPU memory, respectively. This config class
2025-08-14T21:17:31.9858875Z     is meant to be used via the :func:`state_dict_type` context manager as
2025-08-14T21:17:31.9858966Z     follows:
2025-08-14T21:17:31.9859047Z     
2025-08-14T21:17:31.9859178Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9859420Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:31.9859548Z         >>> fsdp = FSDP(model, auto_wrap_policy=...)
2025-08-14T21:17:31.9859749Z         >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True)
2025-08-14T21:17:31.9859978Z         >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg):
2025-08-14T21:17:31.9860088Z         >>>     state = fsdp.state_dict()
2025-08-14T21:17:31.9860305Z         >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0.
2025-08-14T21:17:31.9860542Z         >>> # To reload checkpoint for inference, finetuning, transfer learning, etc:
2025-08-14T21:17:31.9860775Z         >>> model = model_fn()  # Initialize model in preparation for wrapping with FSDP
2025-08-14T21:17:31.9860885Z         >>> if dist.get_rank() == 0:
2025-08-14T21:17:31.9861067Z         >>> # Load checkpoint only on rank 0 to avoid memory redundancy
2025-08-14T21:17:31.9861210Z         >>>     state_dict = torch.load("my_checkpoint.pt")
2025-08-14T21:17:31.9861340Z         >>>     model.load_state_dict(state_dict)
2025-08-14T21:17:31.9861572Z         >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument
2025-08-14T21:17:31.9861818Z         >>> # communicates loaded checkpoint states from rank 0 to rest of the world.
2025-08-14T21:17:31.9861913Z         >>> fsdp = FSDP(
2025-08-14T21:17:31.9861998Z         ...     model,
2025-08-14T21:17:31.9862139Z         ...     device_id=torch.cuda.current_device(),
2025-08-14T21:17:31.9862241Z         ...     auto_wrap_policy=...,
2025-08-14T21:17:31.9862347Z         ...     sync_module_states=True,
2025-08-14T21:17:31.9862435Z         ... )
2025-08-14T21:17:31.9862642Z         >>> # After this point, all ranks have FSDP model with loaded checkpoint.
2025-08-14T21:17:31.9862719Z     
2025-08-14T21:17:31.9862815Z     Attributes:
2025-08-14T21:17:31.9863037Z         rank0_only (bool): If ``True``, then only rank 0 saves the full state
2025-08-14T21:17:31.9863245Z             dict, and nonzero ranks save an empty dict. If ``False``, then all
2025-08-14T21:17:31.9863399Z             ranks save the full state dict. (Default: ``False``)
2025-08-14T21:17:31.9863476Z     
2025-08-14T21:17:31.9863733Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9863816Z     
2025-08-14T21:17:31.9863911Z       warnings.warn(msg)
2025-08-14T21:17:31.9864001Z     
2025-08-14T21:17:31.9864187Z --- Parse Warning: 75 / 146 ---
2025-08-14T21:17:31.9865367Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634.
2025-08-14T21:17:31.9865634Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9865881Z     Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-08-14T21:17:31.9865967Z     
2025-08-14T21:17:31.9866227Z             Also takes (optional) configuration for the model's and optimizer's state dict.
2025-08-14T21:17:31.9866431Z             The target module does not have to be a FSDP module. If the target
2025-08-14T21:17:31.9866670Z             module is a FSDP module, its ``state_dict_type`` will also be changed.
2025-08-14T21:17:31.9866795Z     
2025-08-14T21:17:31.9866995Z             .. note:: This API should be called for only the top-level (root)
2025-08-14T21:17:31.9867078Z                 module.
2025-08-14T21:17:31.9867157Z     
2025-08-14T21:17:31.9867367Z             .. note:: This API enables users to transparently use the conventional
2025-08-14T21:17:31.9867552Z                 ``state_dict`` API to take model checkpoints in cases where the
2025-08-14T21:17:31.9867757Z                 root FSDP module is wrapped by another ``nn.Module``. For example,
2025-08-14T21:17:31.9867972Z                 the following will ensure ``state_dict`` is called on all non-FSDP
2025-08-14T21:17:31.9868204Z                 instances, while dispatching into `sharded_state_dict` implementation
2025-08-14T21:17:31.9868303Z                 for FSDP:
2025-08-14T21:17:31.9868378Z     
2025-08-14T21:17:31.9868468Z             Example::
2025-08-14T21:17:31.9868558Z     
2025-08-14T21:17:31.9868688Z                 >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9868797Z                 >>> model = DDP(FSDP(...))
2025-08-14T21:17:31.9868912Z                 >>> FSDP.set_state_dict_type(
2025-08-14T21:17:31.9869003Z                 >>>     model,
2025-08-14T21:17:31.9869132Z                 >>>     StateDictType.SHARDED_STATE_DICT,
2025-08-14T21:17:31.9869352Z                 >>>     state_dict_config = ShardedStateDictConfig(offload_to_cpu=True),
2025-08-14T21:17:31.9869575Z                 >>>     optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True),
2025-08-14T21:17:31.9869663Z                 >>> )
2025-08-14T21:17:31.9869789Z                 >>> param_state_dict = model.state_dict()
2025-08-14T21:17:31.9869957Z                 >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-08-14T21:17:31.9870039Z     
2025-08-14T21:17:31.9870120Z             Args:
2025-08-14T21:17:31.9870247Z                 module (torch.nn.Module): Root module.
2025-08-14T21:17:31.9870482Z                 state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-08-14T21:17:31.9870718Z                 state_dict_config (Optional[StateDictConfig]): the configuration for the
2025-08-14T21:17:31.9870828Z                     target ``state_dict_type``.
2025-08-14T21:17:31.9871087Z                 optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration
2025-08-14T21:17:31.9871203Z                     for the optimizer state dict.
2025-08-14T21:17:31.9871281Z     
2025-08-14T21:17:31.9871365Z             Returns:
2025-08-14T21:17:31.9871693Z                 A StateDictSettings that include the previous state_dict type and
2025-08-14T21:17:31.9871818Z                 configuration for the module.
2025-08-14T21:17:31.9871902Z             
2025-08-14T21:17:31.9872148Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9872239Z     
2025-08-14T21:17:31.9872337Z       warnings.warn(msg)
2025-08-14T21:17:31.9872412Z     
2025-08-14T21:17:31.9872618Z --- Parse Warning: 76 / 146 ---
2025-08-14T21:17:31.9873786Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792.
2025-08-14T21:17:31.9874054Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9874304Z     Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-08-14T21:17:31.9874377Z     
2025-08-14T21:17:31.9874700Z             This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of
2025-08-14T21:17:31.9874829Z             :meth:`set_state_dict_type` for the detail.
2025-08-14T21:17:31.9874907Z     
2025-08-14T21:17:31.9875011Z             Example::
2025-08-14T21:17:31.9875157Z     
2025-08-14T21:17:31.9875298Z                 >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9875428Z                 >>> model = DDP(FSDP(...))
2025-08-14T21:17:31.9875537Z                 >>> with FSDP.state_dict_type(
2025-08-14T21:17:31.9875635Z                 >>>     model,
2025-08-14T21:17:31.9875764Z                 >>>     StateDictType.SHARDED_STATE_DICT,
2025-08-14T21:17:31.9875845Z                 >>> ):
2025-08-14T21:17:31.9875977Z                 >>>     checkpoint = model.state_dict()
2025-08-14T21:17:31.9876054Z     
2025-08-14T21:17:31.9876137Z             Args:
2025-08-14T21:17:31.9876274Z                 module (torch.nn.Module): Root module.
2025-08-14T21:17:31.9876503Z                 state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-08-14T21:17:31.9876741Z                 state_dict_config (Optional[StateDictConfig]): the model ``state_dict``
2025-08-14T21:17:31.9876900Z                     configuration for the target ``state_dict_type``.
2025-08-14T21:17:31.9877132Z                 optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer
2025-08-14T21:17:31.9877338Z                    ``state_dict`` configuration for the target ``state_dict_type``.
2025-08-14T21:17:31.9877419Z             
2025-08-14T21:17:31.9877663Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9877754Z     
2025-08-14T21:17:31.9877849Z       warnings.warn(msg)
2025-08-14T21:17:31.9877925Z     
2025-08-14T21:17:31.9878119Z --- Parse Warning: 77 / 146 ---
2025-08-14T21:17:31.9879297Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805.
2025-08-14T21:17:31.9879569Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9879651Z     
2025-08-14T21:17:31.9879887Z     Transform the state-dict of an optimizer corresponding to a sharded model.
2025-08-14T21:17:31.9879978Z     
2025-08-14T21:17:31.9880167Z     The given state-dict can be transformed to one of three types:
2025-08-14T21:17:31.9880470Z     1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict.
2025-08-14T21:17:31.9880548Z     
2025-08-14T21:17:31.9880773Z     For full optimizer state_dict, all states are unflattened and not sharded.
2025-08-14T21:17:31.9881026Z     Rank0 only and CPU only can be specified via :meth:`state_dict_type` to
2025-08-14T21:17:31.9881115Z     avoid OOM.
2025-08-14T21:17:31.9881190Z     
2025-08-14T21:17:31.9881434Z     For sharded optimizer state_dict, all states are unflattened but sharded.
2025-08-14T21:17:31.9881635Z     CPU only can be specified via :meth:`state_dict_type` to further save
2025-08-14T21:17:31.9881713Z     memory.
2025-08-14T21:17:31.9881802Z     
2025-08-14T21:17:31.9882017Z     For local state_dict, no transformation will be performed. But a state
2025-08-14T21:17:31.9882266Z     will be converted from nn.Tensor to ShardedTensor to represent its sharding
2025-08-14T21:17:31.9882377Z     nature (this is not supported yet).
2025-08-14T21:17:31.9882450Z     
2025-08-14T21:17:31.9882548Z     Example::
2025-08-14T21:17:31.9882625Z     
2025-08-14T21:17:31.9882749Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9882993Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:31.9883150Z         >>> from torch.distributed.fsdp import StateDictType
2025-08-14T21:17:31.9883324Z         >>> from torch.distributed.fsdp import FullStateDictConfig
2025-08-14T21:17:31.9883535Z         >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-08-14T21:17:31.9883628Z         >>> # Save a checkpoint
2025-08-14T21:17:31.9883744Z         >>> model, optim = ...
2025-08-14T21:17:31.9883875Z         >>> FSDP.set_state_dict_type(
2025-08-14T21:17:31.9883981Z         >>>     model,
2025-08-14T21:17:31.9884132Z         >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:31.9884259Z         >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9884396Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9884488Z         >>> )
2025-08-14T21:17:31.9884596Z         >>> state_dict = model.state_dict()
2025-08-14T21:17:31.9884762Z         >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-08-14T21:17:31.9884916Z         >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-08-14T21:17:31.9885010Z         >>> # Load a checkpoint
2025-08-14T21:17:31.9885119Z         >>> model, optim = ...
2025-08-14T21:17:31.9885268Z         >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-08-14T21:17:31.9885370Z         >>> FSDP.set_state_dict_type(
2025-08-14T21:17:31.9885465Z         >>>     model,
2025-08-14T21:17:31.9885584Z         >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:31.9885711Z         >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9885861Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9885939Z         >>> )
2025-08-14T21:17:31.9886051Z         >>> model.load_state_dict(state_dict)
2025-08-14T21:17:31.9886208Z         >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:31.9886314Z         >>>     model, optim, optim_state_dict
2025-08-14T21:17:31.9886404Z         >>> )
2025-08-14T21:17:31.9886525Z         >>> optim.load_state_dict(optim_state_dict)
2025-08-14T21:17:31.9886601Z     
2025-08-14T21:17:31.9886690Z     Args:
2025-08-14T21:17:31.9886884Z         model (torch.nn.Module): Root module (which may or may not be a
2025-08-14T21:17:31.9887078Z             :class:`FullyShardedDataParallel` instance) whose parameters
2025-08-14T21:17:31.9887223Z             were passed into the optimizer ``optim``.
2025-08-14T21:17:31.9887404Z         optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-08-14T21:17:31.9887497Z             parameters.
2025-08-14T21:17:31.9887722Z         optim_state_dict (Dict[str, Any]): the target optimizer state_dict to
2025-08-14T21:17:31.9887926Z             transform. If the value is None, optim.state_dict() will be used. (
2025-08-14T21:17:31.9888035Z             Default: ``None``)
2025-08-14T21:17:31.9888272Z         group (dist.ProcessGroup): Model's process group across which parameters
2025-08-14T21:17:31.9888454Z             are sharded or ``None`` if using the default process group. (
2025-08-14T21:17:31.9888603Z             Default: ``None``)
2025-08-14T21:17:31.9888682Z     
2025-08-14T21:17:31.9888760Z     Returns:
2025-08-14T21:17:31.9888963Z         Dict[str, Any]: A :class:`dict` containing the optimizer state for
2025-08-14T21:17:31.9889128Z         ``model``. The sharding of the optimizer state is based on
2025-08-14T21:17:31.9889224Z         ``state_dict_type``.
2025-08-14T21:17:31.9889317Z     
2025-08-14T21:17:31.9889567Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9889665Z     
2025-08-14T21:17:31.9889763Z       warnings.warn(msg)
2025-08-14T21:17:31.9889843Z     
2025-08-14T21:17:31.9890047Z --- Parse Warning: 78 / 146 ---
2025-08-14T21:17:31.9891256Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903.
2025-08-14T21:17:31.9891522Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9891618Z     
2025-08-14T21:17:31.9891975Z     Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model.
2025-08-14T21:17:31.9892071Z     
2025-08-14T21:17:31.9892242Z     Given a ``optim_state_dict`` that is transformed through
2025-08-14T21:17:31.9892511Z     :meth:`optim_state_dict`, it gets converted to the flattened optimizer
2025-08-14T21:17:31.9892761Z     state_dict that can be loaded to ``optim`` which is the optimizer for
2025-08-14T21:17:31.9892951Z     ``model``. ``model`` must be sharded by FullyShardedDataParallel.
2025-08-14T21:17:31.9893032Z     
2025-08-14T21:17:31.9893179Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9893414Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-08-14T21:17:31.9893572Z         >>> from torch.distributed.fsdp import StateDictType
2025-08-14T21:17:31.9893764Z         >>> from torch.distributed.fsdp import FullStateDictConfig
2025-08-14T21:17:31.9893965Z         >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-08-14T21:17:31.9894079Z         >>> # Save a checkpoint
2025-08-14T21:17:31.9894180Z         >>> model, optim = ...
2025-08-14T21:17:31.9894285Z         >>> FSDP.set_state_dict_type(
2025-08-14T21:17:31.9894388Z         >>>     model,
2025-08-14T21:17:31.9894508Z         >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:31.9894641Z         >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9894794Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9894876Z         >>> )
2025-08-14T21:17:31.9894988Z         >>> state_dict = model.state_dict()
2025-08-14T21:17:31.9895120Z         >>> original_osd = optim.state_dict()
2025-08-14T21:17:31.9895250Z         >>> optim_state_dict = FSDP.optim_state_dict(
2025-08-14T21:17:31.9895348Z         >>>     model,
2025-08-14T21:17:31.9895433Z         >>>     optim,
2025-08-14T21:17:31.9895544Z         >>>     optim_state_dict=original_osd
2025-08-14T21:17:31.9895637Z         >>> )
2025-08-14T21:17:31.9895780Z         >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-08-14T21:17:31.9895877Z         >>> # Load a checkpoint
2025-08-14T21:17:31.9895985Z         >>> model, optim = ...
2025-08-14T21:17:31.9896136Z         >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-08-14T21:17:31.9896247Z         >>> FSDP.set_state_dict_type(
2025-08-14T21:17:31.9896343Z         >>>     model,
2025-08-14T21:17:31.9896461Z         >>>     StateDictType.FULL_STATE_DICT,
2025-08-14T21:17:31.9896601Z         >>>     FullStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9896741Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-08-14T21:17:31.9896824Z         >>> )
2025-08-14T21:17:31.9896952Z         >>> model.load_state_dict(state_dict)
2025-08-14T21:17:31.9897127Z         >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-08-14T21:17:31.9897241Z         >>>     model, optim, optim_state_dict
2025-08-14T21:17:31.9897335Z         >>> )
2025-08-14T21:17:31.9897457Z         >>> optim.load_state_dict(optim_state_dict)
2025-08-14T21:17:31.9897536Z     
2025-08-14T21:17:31.9897631Z     Args:
2025-08-14T21:17:31.9897827Z         model (torch.nn.Module): Root module (which may or may not be a
2025-08-14T21:17:31.9898043Z             :class:`FullyShardedDataParallel` instance) whose parameters
2025-08-14T21:17:31.9898178Z             were passed into the optimizer ``optim``.
2025-08-14T21:17:31.9898357Z         optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-08-14T21:17:31.9898461Z             parameters.
2025-08-14T21:17:31.9898672Z         optim_state_dict (Dict[str, Any]): The optimizer states to be loaded.
2025-08-14T21:17:31.9898873Z         is_named_optimizer (bool): Is this optimizer a NamedOptimizer or
2025-08-14T21:17:31.9899080Z             KeyedOptimizer. Only set to True if ``optim`` is TorchRec's
2025-08-14T21:17:31.9899257Z             KeyedOptimizer or torch.distributed's NamedOptimizer.
2025-08-14T21:17:31.9899463Z         load_directly (bool): If this is set to True, this API will also
2025-08-14T21:17:31.9899663Z             call optim.load_state_dict(result) before returning the result.
2025-08-14T21:17:31.9899912Z             Otherwise, users are responsible to call ``optim.load_state_dict()``
2025-08-14T21:17:31.9900047Z             (Default: ``False``)
2025-08-14T21:17:31.9900310Z         group (dist.ProcessGroup): Model's process group across which parameters
2025-08-14T21:17:31.9900495Z             are sharded or ``None`` if using the default process group. (
2025-08-14T21:17:31.9900608Z             Default: ``None``)
2025-08-14T21:17:31.9900688Z     
2025-08-14T21:17:31.9900935Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9901028Z     
2025-08-14T21:17:31.9901124Z       warnings.warn(msg)
2025-08-14T21:17:31.9901216Z     
2025-08-14T21:17:31.9901406Z --- Parse Warning: 79 / 146 ---
2025-08-14T21:17:31.9902409Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129.
2025-08-14T21:17:31.9902683Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9902766Z     
2025-08-14T21:17:31.9902990Z     RemoteModule instance can only be created after RPC initialization.
2025-08-14T21:17:31.9903081Z     
2025-08-14T21:17:31.9903274Z     It creates a user-specified module on a specified remote node.
2025-08-14T21:17:31.9903519Z     It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-08-14T21:17:31.9903627Z     executed on the remote node.
2025-08-14T21:17:31.9903864Z     It takes care of autograd recording to ensure the backward pass propagates
2025-08-14T21:17:31.9904037Z     gradients back to the corresponding remote module.
2025-08-14T21:17:31.9904398Z     It can be shared across processors using `RPC framework <https://pytorch.org/docs/stable/rpc.html>`__,
2025-08-14T21:17:31.9904592Z     without incurring any overheads of copying the actual module,
2025-08-14T21:17:31.9904804Z     which is equivalent to an :class:`~torch.distributed.rpc.RRef`
2025-08-14T21:17:31.9904918Z     pointing to the remote module.
2025-08-14T21:17:31.9905014Z     
2025-08-14T21:17:31.9905211Z     The arguments of ``forward_async`` and ``forward`` are the same as
2025-08-14T21:17:31.9905412Z     the ``forward`` method of the module returned by the ``module_cls``.
2025-08-14T21:17:31.9905505Z     
2025-08-14T21:17:31.9905814Z     Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now.
2025-08-14T21:17:31.9905891Z     
2025-08-14T21:17:31.9906152Z     Particularly, to create a hybrid model, typically the local modules should be
2025-08-14T21:17:31.9906555Z     created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``).
2025-08-14T21:17:31.9906647Z     Hybrid Example:
2025-08-14T21:17:31.9906776Z             >>> class HybridModel(nn.Module):
2025-08-14T21:17:31.9906888Z             >>>     def __init__(self) -> None:
2025-08-14T21:17:31.9907014Z             >>>         nn.Module.__init__(self)
2025-08-14T21:17:31.9907159Z             >>>         self.remote_embedding = RemoteModule(...)
2025-08-14T21:17:31.9907284Z             >>>         self.local_linear = nn.Linear(...)
2025-08-14T21:17:31.9907378Z     
2025-08-14T21:17:31.9907573Z     For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-08-14T21:17:31.9907819Z     that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``,
2025-08-14T21:17:31.9908044Z     the generated ``RemoteModule`` will have 2 methods in signature of
2025-08-14T21:17:31.9908173Z     ``def forward(input: Tensor) -> Tensor:`` and
2025-08-14T21:17:31.9908352Z     ``def forward_async(input: Tensor) -> Future[Tensor]:``.
2025-08-14T21:17:31.9908433Z     
2025-08-14T21:17:31.9908521Z     .. note::
2025-08-14T21:17:31.9908677Z         If the remote module is placed on a cuda device,
2025-08-14T21:17:31.9908913Z         any input CPU tensors will be automatically moved to the same cuda device,
2025-08-14T21:17:31.9909552Z         and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend.
2025-08-14T21:17:31.9909715Z     
2025-08-14T21:17:31.9909798Z     Args:
2025-08-14T21:17:31.9910093Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:31.9910397Z             The device can be a local device or a remote device specified by one of the following remote
2025-08-14T21:17:31.9910483Z             formats:
2025-08-14T21:17:31.9910577Z     
2025-08-14T21:17:31.9910720Z                 1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-08-14T21:17:31.9910873Z                 2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-08-14T21:17:31.9910971Z     
2025-08-14T21:17:31.9911219Z             In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:31.9911340Z         module_cls (nn.Module): For example,
2025-08-14T21:17:31.9911548Z             >>> class MyModule(nn.Module):
2025-08-14T21:17:31.9911654Z             >>>     def forward(input):
2025-08-14T21:17:31.9911757Z             >>>         return input + 1
2025-08-14T21:17:31.9911855Z             >>>
2025-08-14T21:17:31.9911955Z             >>> module_cls = MyModule
2025-08-14T21:17:31.9912166Z         args (Sequence, optional): args to be passed to ``module_cls``.
2025-08-14T21:17:31.9912359Z         kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-08-14T21:17:31.9912637Z         _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-08-14T21:17:31.9912889Z             to be created. The type object should be decorated by @torch.jit.interface.
2025-08-14T21:17:31.9913107Z             If not provided, the generated RemoteModule is not torchscript-able.
2025-08-14T21:17:31.9913341Z             Warning, this is an experimental API and susceptible to frequent changes.
2025-08-14T21:17:31.9913434Z     
2025-08-14T21:17:31.9913517Z     Returns:
2025-08-14T21:17:31.9913776Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:31.9914007Z         user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-08-14T21:17:31.9914277Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:31.9914434Z         on the user-provided module on the remote side.
2025-08-14T21:17:31.9914513Z     
2025-08-14T21:17:31.9914604Z     Example::
2025-08-14T21:17:31.9914768Z         Run the following code in two different processes:
2025-08-14T21:17:31.9914848Z     
2025-08-14T21:17:31.9915004Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:31.9915110Z         >>> # On worker 0:
2025-08-14T21:17:31.9915201Z         >>> import torch
2025-08-14T21:17:31.9915340Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9915448Z         >>> from torch import nn, Tensor
2025-08-14T21:17:31.9915672Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:31.9915769Z         >>>
2025-08-14T21:17:31.9915910Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:31.9916035Z         >>> remote_linear_module = RemoteModule(
2025-08-14T21:17:31.9916174Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:31.9916256Z         >>> )
2025-08-14T21:17:31.9916361Z         >>> input = torch.randn(128, 20)
2025-08-14T21:17:31.9916526Z         >>> ret_fut = remote_linear_module.forward_async(input)
2025-08-14T21:17:31.9916625Z         >>> ret = ret_fut.wait()
2025-08-14T21:17:31.9916735Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9916813Z     
2025-08-14T21:17:31.9916903Z         >>> # On worker 1:
2025-08-14T21:17:31.9917005Z         >>> import torch
2025-08-14T21:17:31.9917129Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9917209Z         >>>
2025-08-14T21:17:31.9917357Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:31.9917504Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9917643Z     
2025-08-14T21:17:31.9917910Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9918016Z     
2025-08-14T21:17:31.9918111Z       warnings.warn(msg)
2025-08-14T21:17:31.9918203Z     
2025-08-14T21:17:31.9918413Z --- Parse Warning: 80 / 146 ---
2025-08-14T21:17:31.9919504Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506.
2025-08-14T21:17:31.9919767Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9919845Z     
2025-08-14T21:17:31.9920179Z     Besides the constructor, a RemoteModule instance can also be initialized given a module RRef.
2025-08-14T21:17:31.9920260Z     
2025-08-14T21:17:31.9920587Z     This alternate initialization method can be particularly useful if we want to create multiple
2025-08-14T21:17:31.9920920Z     RemoteModule instances that share the same underlying module and reduce memory consumption.
2025-08-14T21:17:31.9921001Z     
2025-08-14T21:17:31.9921292Z     Moreover, this also provides a workaround for passing script RemoteModule over RPC,
2025-08-14T21:17:31.9921470Z     which is not supported. The recommended way is as follows:
2025-08-14T21:17:31.9921549Z     
2025-08-14T21:17:31.9921683Z         1. the sender creates a RemoteModule;
2025-08-14T21:17:31.9921825Z         2. the sender sends its ``module_rref`` over RPC;
2025-08-14T21:17:31.9922162Z         3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``.
2025-08-14T21:17:31.9922255Z     
2025-08-14T21:17:31.9922345Z     Example::
2025-08-14T21:17:31.9922499Z         Run the following code in two different processes:
2025-08-14T21:17:31.9922594Z     
2025-08-14T21:17:31.9922712Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:31.9922821Z         >>> # On worker 0:
2025-08-14T21:17:31.9922914Z         >>> import torch
2025-08-14T21:17:31.9923038Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9923160Z         >>> from torch import nn, Tensor
2025-08-14T21:17:31.9923379Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:31.9923465Z         >>>
2025-08-14T21:17:31.9923618Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:31.9923731Z         >>> remote_module = RemoteModule(
2025-08-14T21:17:31.9923885Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:31.9923980Z         >>> )
2025-08-14T21:17:31.9924061Z         >>>
2025-08-14T21:17:31.9924186Z         >>> remote_module1 = rpc.rpc_sync(
2025-08-14T21:17:31.9924284Z         >>>     "worker1/cpu",
2025-08-14T21:17:31.9924406Z         >>>     RemoteModule.init_from_module_rref,
2025-08-14T21:17:31.9924575Z         >>>     ("worker1/cpu", remote_module1.get_module_rref()),
2025-08-14T21:17:31.9924656Z         >>> )
2025-08-14T21:17:31.9924753Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9924847Z     
2025-08-14T21:17:31.9924939Z         >>> # On worker 1:
2025-08-14T21:17:31.9925027Z         >>> import torch
2025-08-14T21:17:31.9925163Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9925240Z         >>>
2025-08-14T21:17:31.9925376Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:31.9925481Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9925558Z     
2025-08-14T21:17:31.9925650Z     Args:
2025-08-14T21:17:31.9925943Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:31.9926231Z             The device can be a local device or a remote device specified by one of the following remote
2025-08-14T21:17:31.9926329Z             formats:
2025-08-14T21:17:31.9926407Z     
2025-08-14T21:17:31.9926574Z                 1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-08-14T21:17:31.9926757Z                 2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-08-14T21:17:31.9926860Z     
2025-08-14T21:17:31.9927106Z             In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:31.9927364Z         module_rref (RRef[nn.Module]): The module reference shared by both the caller and
2025-08-14T21:17:31.9927469Z             the created remote module.
2025-08-14T21:17:31.9927755Z         _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-08-14T21:17:31.9927983Z             to be created. The type object should be decorated by @torch.jit.interface.
2025-08-14T21:17:31.9928198Z             If not provided, the generated RemoteModule is not torchscript-able.
2025-08-14T21:17:31.9928441Z             Warning, this is an experimental API and susceptible to frequent changes.
2025-08-14T21:17:31.9928522Z     
2025-08-14T21:17:31.9928603Z     Returns:
2025-08-14T21:17:31.9928857Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:31.9929088Z         user-provided ``module_rref``, it has a blocking ``forward`` method and an
2025-08-14T21:17:31.9929373Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:31.9929513Z         on the user-provided module on the remote side.
2025-08-14T21:17:31.9929595Z     
2025-08-14T21:17:31.9929860Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9929939Z     
2025-08-14T21:17:31.9930036Z       warnings.warn(msg)
2025-08-14T21:17:31.9930128Z     
2025-08-14T21:17:31.9930317Z --- Parse Warning: 81 / 146 ---
2025-08-14T21:17:31.9931293Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598.
2025-08-14T21:17:31.9931570Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9931651Z     
2025-08-14T21:17:31.9931901Z         A RemoteModule instance can only be created after RPC initialization.
2025-08-14T21:17:31.9931980Z     
2025-08-14T21:17:31.9932173Z         It creates a user-specified module on a specified remote node.
2025-08-14T21:17:31.9932419Z         It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-08-14T21:17:31.9932525Z         executed on the remote node.
2025-08-14T21:17:31.9932786Z         It takes care of autograd recording to ensure the backward pass propagates
2025-08-14T21:17:31.9932958Z         gradients back to the corresponding remote module.
2025-08-14T21:17:31.9933038Z     
2025-08-14T21:17:31.9933262Z         It generates two methods ``forward_async`` and ``forward`` based on the
2025-08-14T21:17:31.9933474Z         signature of the ``forward`` method of ``module_cls``. ``forward_async``
2025-08-14T21:17:31.9933732Z         runs asynchronously and returns a Future. The arguments of ``forward_async``
2025-08-14T21:17:31.9933943Z         and ``forward`` are the same as the ``forward`` method of the module
2025-08-14T21:17:31.9934049Z         returned by the ``module_cls``.
2025-08-14T21:17:31.9934129Z     
2025-08-14T21:17:31.9934338Z         For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-08-14T21:17:31.9934587Z         that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``,
2025-08-14T21:17:31.9934822Z         the generated ``RemoteModule`` will have 2 methods with the signatures:
2025-08-14T21:17:31.9934900Z     
2025-08-14T21:17:31.9935023Z         | ``def forward(input: Tensor) -> Tensor:``
2025-08-14T21:17:31.9935198Z         | ``def forward_async(input: Tensor) -> Future[Tensor]:``
2025-08-14T21:17:31.9935276Z     
2025-08-14T21:17:31.9935356Z     Args:
2025-08-14T21:17:31.9935687Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-08-14T21:17:31.9936476Z             The format should be "<workername>/<device>", where the device field can be parsed as torch.device type.
2025-08-14T21:17:31.9936653Z             E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0".
2025-08-14T21:17:31.9936898Z             In addition, the device field can be optional and the default value is "cpu".
2025-08-14T21:17:31.9937147Z         module_cls (nn.Module): Class for the module to be created remotely. For example,
2025-08-14T21:17:31.9937245Z     
2025-08-14T21:17:31.9937356Z             >>> class MyModule(nn.Module):
2025-08-14T21:17:31.9937464Z             >>>     def forward(input):
2025-08-14T21:17:31.9937578Z             >>>         return input + 1
2025-08-14T21:17:31.9937656Z             >>>
2025-08-14T21:17:31.9937756Z             >>> module_cls = MyModule
2025-08-14T21:17:31.9937846Z     
2025-08-14T21:17:31.9938042Z         args (Sequence, optional): args to be passed to ``module_cls``.
2025-08-14T21:17:31.9938247Z         kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-08-14T21:17:31.9938327Z     
2025-08-14T21:17:31.9938410Z     Returns:
2025-08-14T21:17:31.9938662Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-08-14T21:17:31.9938891Z         user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-08-14T21:17:31.9939161Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-08-14T21:17:31.9939316Z         on the user-provided module on the remote side.
2025-08-14T21:17:31.9939396Z     
2025-08-14T21:17:31.9939487Z     Example::
2025-08-14T21:17:31.9939650Z         Run the following code in two different processes:
2025-08-14T21:17:31.9939729Z     
2025-08-14T21:17:31.9939853Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:31.9939942Z         >>> # On worker 0:
2025-08-14T21:17:31.9940031Z         >>> import torch
2025-08-14T21:17:31.9940168Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9940275Z         >>> from torch import nn, Tensor
2025-08-14T21:17:31.9940496Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-08-14T21:17:31.9940589Z         >>>
2025-08-14T21:17:31.9940725Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:31.9940847Z         >>> remote_linear_module = RemoteModule(
2025-08-14T21:17:31.9940984Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-08-14T21:17:31.9941065Z         >>> )
2025-08-14T21:17:31.9941169Z         >>> input = torch.randn(128, 20)
2025-08-14T21:17:31.9941373Z         >>> ret_fut = remote_linear_module.forward_async(input)
2025-08-14T21:17:31.9941471Z         >>> ret = ret_fut.wait()
2025-08-14T21:17:31.9941579Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9941657Z     
2025-08-14T21:17:31.9941744Z         >>> # On worker 1:
2025-08-14T21:17:31.9941846Z         >>> import torch
2025-08-14T21:17:31.9941971Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9942053Z         >>>
2025-08-14T21:17:31.9942203Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:31.9942297Z         >>> rpc.shutdown()
2025-08-14T21:17:31.9942376Z     
2025-08-14T21:17:31.9942580Z         Furthermore, a more practical example that is combined with
2025-08-14T21:17:31.9943055Z         `DistributedDataParallel <https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel>`__ (DDP)
2025-08-14T21:17:31.9943395Z         can be found in this `tutorial <https://pytorch.org/tutorials/advanced/rpc_ddp_tutorial.html>`__.
2025-08-14T21:17:31.9943476Z     
2025-08-14T21:17:31.9943726Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9943814Z     
2025-08-14T21:17:31.9943908Z       warnings.warn(msg)
2025-08-14T21:17:31.9943990Z     
2025-08-14T21:17:31.9944198Z --- Parse Warning: 82 / 146 ---
2025-08-14T21:17:31.9945226Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129.
2025-08-14T21:17:31.9945550Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9945630Z     
2025-08-14T21:17:31.9945871Z     DistributedOptimizer takes remote references to parameters scattered
2025-08-14T21:17:31.9946179Z     across workers and applies the given optimizer locally for each parameter.
2025-08-14T21:17:31.9946257Z     
2025-08-14T21:17:31.9946489Z     This class uses :meth:`~torch.distributed.autograd.get_gradients` in order
2025-08-14T21:17:31.9946657Z     to retrieve the gradients for specific parameters.
2025-08-14T21:17:31.9946734Z     
2025-08-14T21:17:31.9946828Z     Concurrent calls to
2025-08-14T21:17:31.9947048Z     :meth:`~torch.distributed.optim.DistributedOptimizer.step`,
2025-08-14T21:17:31.9947192Z     either from the same or different clients, will
2025-08-14T21:17:31.9947430Z     be serialized on each worker -- as each worker's optimizer can only work
2025-08-14T21:17:31.9947636Z     on one set of gradients at a time. However, there is no guarantee that
2025-08-14T21:17:31.9947881Z     the full forward-backward-optimizer sequence will execute for one client
2025-08-14T21:17:31.9948110Z     at a time. This means that the gradients being applied may not correspond
2025-08-14T21:17:31.9948329Z     to the latest forward pass executed on a given worker. Also, there is no
2025-08-14T21:17:31.9948446Z     guaranteed ordering across workers.
2025-08-14T21:17:31.9948536Z     
2025-08-14T21:17:31.9948797Z     `DistributedOptimizer` creates the local optimizer with TorchScript enabled
2025-08-14T21:17:31.9949035Z     by default, so that optimizer updates are not blocked by the Python Global
2025-08-14T21:17:31.9949277Z     Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed
2025-08-14T21:17:31.9949514Z     Model Parallel). This feature is currently enabled for most optimizers. You
2025-08-14T21:17:31.9949780Z     can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support
2025-08-14T21:17:31.9949890Z     for your own custom optimizers.
2025-08-14T21:17:31.9949969Z     
2025-08-14T21:17:31.9950064Z     Args:
2025-08-14T21:17:31.9950259Z         optimizer_class (optim.Optimizer): the class of optimizer to
2025-08-14T21:17:31.9950363Z             instantiate on each worker.
2025-08-14T21:17:31.9950581Z         params_rref (list[RRef]): list of RRefs to local or remote parameters
2025-08-14T21:17:31.9950695Z             to optimize.
2025-08-14T21:17:31.9950918Z         args: arguments to pass to the optimizer constructor on each worker.
2025-08-14T21:17:31.9951138Z         kwargs: arguments to pass to the optimizer constructor on each worker.
2025-08-14T21:17:31.9951218Z     
2025-08-14T21:17:31.9951320Z     Example::
2025-08-14T21:17:31.9951516Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:31.9951689Z         >>> import torch.distributed.autograd as dist_autograd
2025-08-14T21:17:31.9951832Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:31.9951937Z         >>> from torch import optim
2025-08-14T21:17:31.9952125Z         >>> from torch.distributed.optim import DistributedOptimizer
2025-08-14T21:17:31.9952222Z         >>>
2025-08-14T21:17:31.9952358Z         >>> with dist_autograd.context() as context_id:
2025-08-14T21:17:31.9952470Z         >>>   # Forward pass.
2025-08-14T21:17:31.9952670Z         >>>   rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3))
2025-08-14T21:17:31.9952863Z         >>>   rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1))
2025-08-14T21:17:31.9953007Z         >>>   loss = rref1.to_here() + rref2.to_here()
2025-08-14T21:17:31.9953089Z         >>>
2025-08-14T21:17:31.9953188Z         >>>   # Backward pass.
2025-08-14T21:17:31.9953353Z         >>>   dist_autograd.backward(context_id, [loss.sum()])
2025-08-14T21:17:31.9953493Z         >>>
2025-08-14T21:17:31.9953585Z         >>>   # Optimizer.
2025-08-14T21:17:31.9953750Z         >>>   dist_optim = DistributedOptimizer(
2025-08-14T21:17:31.9953839Z         >>>      optim.SGD,
2025-08-14T21:17:31.9953951Z         >>>      [rref1, rref2],
2025-08-14T21:17:31.9954041Z         >>>      lr=0.05,
2025-08-14T21:17:31.9954123Z         >>>   )
2025-08-14T21:17:31.9954247Z         >>>   dist_optim.step(context_id)
2025-08-14T21:17:31.9954327Z     
2025-08-14T21:17:31.9954482Z     __ https://github.com/pytorch/tutorials/pull/1465
2025-08-14T21:17:31.9954578Z     
2025-08-14T21:17:31.9954836Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9954912Z     
2025-08-14T21:17:31.9955022Z       warnings.warn(msg)
2025-08-14T21:17:31.9955101Z     
2025-08-14T21:17:31.9955299Z --- Parse Warning: 83 / 146 ---
2025-08-14T21:17:31.9956381Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9.
2025-08-14T21:17:31.9956650Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9956741Z     
2025-08-14T21:17:31.9957131Z     Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-08-14T21:17:31.9957286Z     This optimizer runs local optimizer at every step.
2025-08-14T21:17:31.9957637Z     After the warm-up stage, it averages parameters periodically after the local optimizer is applied.
2025-08-14T21:17:31.9957717Z     
2025-08-14T21:17:31.9957814Z     Args:
2025-08-14T21:17:31.9957924Z         optim: The local optimizer.
2025-08-14T21:17:31.9958142Z         averager: A model averager instance to run post-localSGD algorithm.
2025-08-14T21:17:31.9958235Z     
2025-08-14T21:17:31.9958322Z     Example::
2025-08-14T21:17:31.9958402Z     
2025-08-14T21:17:31.9958546Z         >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:31.9958640Z         >>> import torch
2025-08-14T21:17:31.9958757Z         >>> import torch.distributed as dist
2025-08-14T21:17:31.9959038Z         >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-08-14T21:17:31.9959139Z         >>> import torch.nn as nn
2025-08-14T21:17:31.9959331Z         >>> from torch.distributed.optim import PostLocalSGDOptimizer
2025-08-14T21:17:31.9959614Z         >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-08-14T21:17:31.9959741Z         >>>   PostLocalSGDState,
2025-08-14T21:17:31.9959851Z         >>>   post_localSGD_hook,
2025-08-14T21:17:31.9959932Z         >>> )
2025-08-14T21:17:31.9960010Z         >>>
2025-08-14T21:17:31.9960177Z         >>> model = nn.parallel.DistributedDataParallel(
2025-08-14T21:17:31.9960316Z         >>>    module, device_ids=[rank], output_device=rank
2025-08-14T21:17:31.9960398Z         >>> )
2025-08-14T21:17:31.9960492Z         >>>
2025-08-14T21:17:31.9960636Z         >>> # Register a post-localSGD communication hook.
2025-08-14T21:17:31.9960930Z         >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-08-14T21:17:31.9961103Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-08-14T21:17:31.9961182Z         >>>
2025-08-14T21:17:31.9961395Z         >>> # Create a post-localSGD optimizer that wraps a local optimizer.
2025-08-14T21:17:31.9961643Z         >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as
2025-08-14T21:17:31.9961809Z         >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-08-14T21:17:31.9962035Z         >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01)
2025-08-14T21:17:31.9962152Z         >>> opt = PostLocalSGDOptimizer(
2025-08-14T21:17:31.9962253Z         >>>     optim=local_optim,
2025-08-14T21:17:31.9962540Z         >>>     averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-08-14T21:17:31.9962667Z         >>> )
2025-08-14T21:17:31.9962761Z         >>>
2025-08-14T21:17:31.9962982Z         >>> # In the first 100 steps, DDP runs global gradient averaging at every step.
2025-08-14T21:17:31.9963282Z         >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default),
2025-08-14T21:17:31.9963668Z         >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer.
2025-08-14T21:17:31.9963775Z         >>> for step in range(0, 200):
2025-08-14T21:17:31.9963872Z         >>>    opt.zero_grad()
2025-08-14T21:17:31.9963995Z         >>>    loss = loss_fn(output, labels)
2025-08-14T21:17:31.9964091Z         >>>    loss.backward()
2025-08-14T21:17:31.9964180Z         >>>    opt.step()
2025-08-14T21:17:31.9964274Z     
2025-08-14T21:17:31.9964526Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9964624Z     
2025-08-14T21:17:31.9964718Z       warnings.warn(msg)
2025-08-14T21:17:31.9964796Z     
2025-08-14T21:17:31.9964996Z --- Parse Warning: 84 / 146 ---
2025-08-14T21:17:31.9966088Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284.
2025-08-14T21:17:31.9966348Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9966442Z     
2025-08-14T21:17:31.9966848Z     Wrap an arbitrary :class:`optim.Optimizer <torch.optim.Optimizer>` and shards its states across ranks in the group.
2025-08-14T21:17:31.9966939Z     
2025-08-14T21:17:31.9967183Z     The sharing is done as described by `ZeRO <https://arxiv.org/abs/1910.02054>`_.
2025-08-14T21:17:31.9967262Z     
2025-08-14T21:17:31.9967422Z     The local optimizer instance in each rank is only
2025-08-14T21:17:31.9967666Z     responsible for updating approximately ``1 / world_size`` parameters and
2025-08-14T21:17:31.9967869Z     hence only needs to keep ``1 / world_size`` optimizer states. After
2025-08-14T21:17:31.9968124Z     parameters are updated locally, each rank will broadcast its parameters to
2025-08-14T21:17:31.9968309Z     all other peers to keep all model replicas in the same state.
2025-08-14T21:17:31.9968514Z     ``ZeroRedundancyOptimizer`` can be used in conjunction with
2025-08-14T21:17:31.9968801Z     :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak
2025-08-14T21:17:31.9968897Z     memory consumption.
2025-08-14T21:17:31.9968988Z     
2025-08-14T21:17:31.9969248Z     ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number
2025-08-14T21:17:31.9969475Z     of parameters at each rank. Each parameter belongs to a single rank and is
2025-08-14T21:17:31.9969729Z     not divided among ranks. The partition is arbitrary and might not match the
2025-08-14T21:17:31.9969861Z     the parameter registration or usage order.
2025-08-14T21:17:31.9969939Z     
2025-08-14T21:17:31.9970036Z     Arguments:
2025-08-14T21:17:31.9970228Z         params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s
2025-08-14T21:17:31.9970425Z             or :class:`dict` s giving all parameters, which will be sharded
2025-08-14T21:17:31.9970518Z             across ranks.
2025-08-14T21:17:31.9970595Z     
2025-08-14T21:17:31.9970693Z     Keyword Args:
2025-08-14T21:17:31.9970916Z         optimizer_class (:class:`torch.nn.Optimizer`): the class of the local
2025-08-14T21:17:31.9971002Z             optimizer.
2025-08-14T21:17:31.9971220Z         process_group (``ProcessGroup``, optional): ``torch.distributed``
2025-08-14T21:17:31.9971412Z             ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by
2025-08-14T21:17:31.9971557Z             :meth:`torch.distributed.init_process_group`).
2025-08-14T21:17:31.9971820Z         parameters_as_bucket_view (bool, optional): if ``True``, parameters are
2025-08-14T21:17:31.9972099Z             packed into buckets to speed up communication, and ``param.data``
2025-08-14T21:17:31.9972309Z             fields point to bucket views at different offsets; if ``False``,
2025-08-14T21:17:31.9972512Z             each individual parameter is communicated separately, and each
2025-08-14T21:17:31.9972660Z             ``params.data`` stays intact (default: ``False``).
2025-08-14T21:17:31.9972861Z         overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is
2025-08-14T21:17:31.9973060Z             overlapped with :class:`DistributedDataParallel` 's gradient
2025-08-14T21:17:31.9973273Z             synchronization; this requires (1) either a functional optimizer
2025-08-14T21:17:31.9973466Z             for the ``optimizer_class`` argument or one with a functional
2025-08-14T21:17:31.9973639Z             equivalent and (2) registering a DDP communication hook
2025-08-14T21:17:31.9973850Z             constructed from one of the functions in ``ddp_zero_hook.py``;
2025-08-14T21:17:31.9974019Z             parameters are packed into buckets matching those in
2025-08-14T21:17:31.9974175Z             :class:`DistributedDataParallel`, meaning that the
2025-08-14T21:17:31.9974341Z             ``parameters_as_bucket_view`` argument is ignored.
2025-08-14T21:17:31.9974526Z             If ``False``, :meth:`step` runs disjointly after the backward pass
2025-08-14T21:17:31.9974619Z             (per normal).
2025-08-14T21:17:31.9974730Z             (default: ``False``)
2025-08-14T21:17:31.9974940Z         **defaults: any trailing arguments, which are forwarded to the local
2025-08-14T21:17:31.9975039Z             optimizer.
2025-08-14T21:17:31.9975118Z     
2025-08-14T21:17:31.9975203Z     Example::
2025-08-14T21:17:31.9975298Z     
2025-08-14T21:17:31.9975393Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9975496Z         >>> import torch.nn as nn
2025-08-14T21:17:31.9975713Z         >>> from torch.distributed.optim import ZeroRedundancyOptimizer
2025-08-14T21:17:31.9975914Z         >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-08-14T21:17:31.9976138Z         >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)])
2025-08-14T21:17:31.9976272Z         >>> ddp = DDP(model, device_ids=[rank])
2025-08-14T21:17:31.9976388Z         >>> opt = ZeroRedundancyOptimizer(
2025-08-14T21:17:31.9976501Z         >>>     ddp.parameters(),
2025-08-14T21:17:31.9976622Z         >>>     optimizer_class=torch.optim.Adam,
2025-08-14T21:17:31.9976705Z         >>>     lr=0.01
2025-08-14T21:17:31.9976824Z         >>> )
2025-08-14T21:17:31.9976932Z         >>> ddp(inputs).sum().backward()
2025-08-14T21:17:31.9977020Z         >>> opt.step()
2025-08-14T21:17:31.9977111Z     
2025-08-14T21:17:31.9977200Z     .. warning::
2025-08-14T21:17:31.9977407Z         Currently, ``ZeroRedundancyOptimizer`` requires that all of the
2025-08-14T21:17:31.9977562Z         passed-in parameters are the same dense type.
2025-08-14T21:17:31.9977643Z     
2025-08-14T21:17:31.9977727Z     .. warning::
2025-08-14T21:17:31.9977950Z         If you pass ``overlap_with_ddp=True``, be wary of the following: Given
2025-08-14T21:17:31.9978150Z         the way that overlapping :class:`DistributedDataParallel` with
2025-08-14T21:17:31.9978394Z         :class:`ZeroRedundancyOptimizer` is currently implemented, the first
2025-08-14T21:17:31.9978607Z         two or three training iterations do not perform parameter updates in
2025-08-14T21:17:31.9978799Z         the optimizer step, depending on if ``static_graph=False`` or
2025-08-14T21:17:31.9978999Z         ``static_graph=True``, respectively. This is because it needs
2025-08-14T21:17:31.9979184Z         information about the gradient bucketing strategy used by
2025-08-14T21:17:31.9979400Z         :class:`DistributedDataParallel`, which is not finalized until the
2025-08-14T21:17:31.9979613Z         second forward pass if ``static_graph=False`` or until the third
2025-08-14T21:17:31.9979843Z         forward pass if ``static_graph=True``. To adjust for this, one option
2025-08-14T21:17:31.9980013Z         is to prepend dummy inputs.
2025-08-14T21:17:31.9980099Z     
2025-08-14T21:17:31.9980350Z     .. warning:: ZeroRedundancyOptimizer is experimental and subject to change.
2025-08-14T21:17:31.9980439Z     
2025-08-14T21:17:31.9980687Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9980762Z     
2025-08-14T21:17:31.9980870Z       warnings.warn(msg)
2025-08-14T21:17:31.9980950Z     
2025-08-14T21:17:31.9981141Z --- Parse Warning: 85 / 146 ---
2025-08-14T21:17:31.9982144Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29.
2025-08-14T21:17:31.9982403Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9982499Z     
2025-08-14T21:17:31.9982729Z     Custom reducer class that can be used to specify a custom operation that
2025-08-14T21:17:31.9982905Z     reduces losses of multiple microbatches into one value.
2025-08-14T21:17:31.9982998Z     
2025-08-14T21:17:31.9983082Z     Example:
2025-08-14T21:17:31.9983176Z     >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9983302Z     >>> sum_reducer = _CustomReducer(
2025-08-14T21:17:31.9983412Z     >>>     torch.tensor(0.0),
2025-08-14T21:17:31.9983521Z     >>>     lambda a, b: a + b
2025-08-14T21:17:31.9983601Z     >>> )
2025-08-14T21:17:31.9983680Z     
2025-08-14T21:17:31.9983948Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:31.9984028Z     
2025-08-14T21:17:31.9984125Z       warnings.warn(msg)
2025-08-14T21:17:31.9984219Z     
2025-08-14T21:17:31.9984401Z --- Parse Warning: 86 / 146 ---
2025-08-14T21:17:31.9985326Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6.
2025-08-14T21:17:31.9985604Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:31.9985684Z     
2025-08-14T21:17:31.9985940Z     A decorator for a function indicating that the return value of the function
2025-08-14T21:17:31.9986150Z     is guaranteed to be a :class:`~torch.futures.Future` object and this
2025-08-14T21:17:31.9986423Z     function can run asynchronously on the RPC callee. More specifically, the
2025-08-14T21:17:31.9986673Z     callee extracts the :class:`~torch.futures.Future` returned by the wrapped
2025-08-14T21:17:31.9986911Z     function and installs subsequent processing steps as a callback to that
2025-08-14T21:17:31.9987143Z     :class:`~torch.futures.Future`. The installed callback will read the value
2025-08-14T21:17:31.9987361Z     from the :class:`~torch.futures.Future` when completed and send the
2025-08-14T21:17:31.9987543Z     value back as the RPC response. That also means the returned
2025-08-14T21:17:31.9987789Z     :class:`~torch.futures.Future` only exists on the callee side and is never
2025-08-14T21:17:31.9988011Z     sent through RPC. This decorator is useful when the wrapped function's
2025-08-14T21:17:31.9988207Z     (``fn``) execution needs to pause and resume due to, e.g., containing
2025-08-14T21:17:31.9988448Z     :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals.
2025-08-14T21:17:31.9988533Z     
2025-08-14T21:17:31.9988751Z     .. note:: To enable asynchronous execution, applications must pass the
2025-08-14T21:17:31.9988997Z         function object returned by this decorator to RPC APIs. If RPC detected
2025-08-14T21:17:31.9989216Z         attributes installed by this decorator, it knows that this function
2025-08-14T21:17:31.9989413Z         returns a ``Future`` object and will handle that accordingly.
2025-08-14T21:17:31.9989653Z         However, this does not mean this decorator has to be outmost one when
2025-08-14T21:17:31.9989926Z         defining a function. For example, when combined with ``@staticmethod``
2025-08-14T21:17:31.9990147Z         or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the
2025-08-14T21:17:31.9990371Z         inner decorator to allow the target function be recognized as a static
2025-08-14T21:17:31.9990614Z         or class function. This target function can still execute asynchronously
2025-08-14T21:17:31.9990839Z         because, when accessed, the static or class method preserves attributes
2025-08-14T21:17:31.9990995Z         installed by ``@rpc.functions.async_execution``.
2025-08-14T21:17:31.9991090Z     
2025-08-14T21:17:31.9991171Z     
2025-08-14T21:17:31.9991259Z     Example::
2025-08-14T21:17:31.9991566Z         The returned :class:`~torch.futures.Future` object can come from
2025-08-14T21:17:31.9991703Z         :meth:`~torch.distributed.rpc.rpc_async`,
2025-08-14T21:17:31.9991928Z         :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future`
2025-08-14T21:17:31.9992121Z         constructor. The example below shows directly using the
2025-08-14T21:17:31.9992253Z         :class:`~torch.futures.Future` returned by
2025-08-14T21:17:31.9992388Z         :meth:`~torch.futures.Future.then`.
2025-08-14T21:17:31.9992469Z     
2025-08-14T21:17:31.9992588Z         >>> from torch.distributed import rpc
2025-08-14T21:17:31.9992683Z         >>>
2025-08-14T21:17:31.9992797Z         >>> # omitting setup and shutdown RPC
2025-08-14T21:17:31.9992878Z         >>>
2025-08-14T21:17:31.9992985Z         >>> # On all workers
2025-08-14T21:17:31.9993101Z         >>> @rpc.functions.async_execution
2025-08-14T21:17:31.9993214Z         >>> def async_add_chained(to, x, y, z):
2025-08-14T21:17:31.9993417Z         >>>     # This function runs on "worker1" and returns immediately when
2025-08-14T21:17:31.9993601Z         >>>     # the callback is installed through the `then(cb)` API. In the
2025-08-14T21:17:31.9993797Z         >>>     # mean time, the `rpc_async` to "worker2" can run concurrently.
2025-08-14T21:17:31.9993955Z         >>>     # When the return value of that `rpc_async` arrives at
2025-08-14T21:17:31.9994141Z         >>>     # "worker1", "worker1" will run the lambda function accordingly
2025-08-14T21:17:31.9994336Z         >>>     # and set the value for the previously returned `Future`, which
2025-08-14T21:17:31.9994516Z         >>>     # will then trigger RPC to send the result back to "worker0".
2025-08-14T21:17:31.9994712Z         >>>     return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:31.9994838Z         >>>         lambda fut: fut.wait() + z
2025-08-14T21:17:31.9994920Z         >>>     )
2025-08-14T21:17:31.9995016Z         >>>
2025-08-14T21:17:31.9995107Z         >>> # On worker0
2025-08-14T21:17:31.9995205Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:31.9995317Z         >>> ret = rpc.rpc_sync(
2025-08-14T21:17:31.9995406Z         >>>     "worker1",
2025-08-14T21:17:31.9995509Z         >>>     async_add_chained,
2025-08-14T21:17:31.9995649Z         >>>     args=("worker2", torch.ones(2), 1, 1)
2025-08-14T21:17:31.9995731Z         >>> )
2025-08-14T21:17:31.9995850Z         >>> print(ret)  # prints tensor([3., 3.])
2025-08-14T21:17:31.9995945Z     
2025-08-14T21:17:31.9996170Z         When combined with TorchScript decorators, this decorator must be the
2025-08-14T21:17:31.9996263Z         outmost one.
2025-08-14T21:17:31.9996359Z     
2025-08-14T21:17:31.9996463Z         >>> from torch import Tensor
2025-08-14T21:17:31.9996593Z         >>> from torch.futures import Future
2025-08-14T21:17:31.9996711Z         >>> from torch.distributed import rpc
2025-08-14T21:17:31.9996789Z         >>>
2025-08-14T21:17:31.9996913Z         >>> # omitting setup and shutdown RPC
2025-08-14T21:17:31.9996992Z         >>>
2025-08-14T21:17:31.9997085Z         >>> # On all workers
2025-08-14T21:17:31.9997194Z         >>> @torch.jit.script
2025-08-14T21:17:31.9997368Z         >>> def script_add(x: Tensor, y: Tensor) -> Tensor:
2025-08-14T21:17:31.9997485Z         >>>     return x + y
2025-08-14T21:17:31.9997604Z         >>>
2025-08-14T21:17:31.9997718Z         >>> @rpc.functions.async_execution
2025-08-14T21:17:31.9997816Z         >>> @torch.jit.script
2025-08-14T21:17:31.9998016Z         >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]:
2025-08-14T21:17:31.9998157Z         >>>     return rpc.rpc_async(to, script_add, (x, y))
2025-08-14T21:17:31.9998249Z         >>>
2025-08-14T21:17:31.9998337Z         >>> # On worker0
2025-08-14T21:17:31.9998435Z         >>> ret = rpc.rpc_sync(
2025-08-14T21:17:31.9998539Z         >>>     "worker1",
2025-08-14T21:17:31.9998630Z         >>>     async_add,
2025-08-14T21:17:31.9998746Z         >>>     args=("worker2", torch.ones(2), 1)
2025-08-14T21:17:31.9998837Z         >>> )
2025-08-14T21:17:31.9998955Z         >>> print(ret)  # prints tensor([2., 2.])
2025-08-14T21:17:31.9999034Z     
2025-08-14T21:17:31.9999268Z         When combined with static or class method, this decorator must be the
2025-08-14T21:17:31.9999357Z         inner one.
2025-08-14T21:17:31.9999437Z     
2025-08-14T21:17:31.9999568Z         >>> from torch.distributed import rpc
2025-08-14T21:17:31.9999649Z         >>>
2025-08-14T21:17:31.9999775Z         >>> # omitting setup and shutdown RPC
2025-08-14T21:17:31.9999854Z         >>>
2025-08-14T21:17:31.9999947Z         >>> # On all workers
2025-08-14T21:17:32.0000071Z         >>> class AsyncExecutionClass:
2025-08-14T21:17:32.0000149Z         >>>
2025-08-14T21:17:32.0000245Z         >>>     @staticmethod
2025-08-14T21:17:32.0000376Z         >>>     @rpc.functions.async_execution
2025-08-14T21:17:32.0000492Z         >>>     def static_async_add(to, x, y, z):
2025-08-14T21:17:32.0000662Z         >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:32.0000785Z         >>>             lambda fut: fut.wait() + z
2025-08-14T21:17:32.0000869Z         >>>         )
2025-08-14T21:17:32.0000951Z         >>>
2025-08-14T21:17:32.0001057Z         >>>     @classmethod
2025-08-14T21:17:32.0001175Z         >>>     @rpc.functions.async_execution
2025-08-14T21:17:32.0001313Z         >>>     def class_async_add(cls, to, x, y, z):
2025-08-14T21:17:32.0001437Z         >>>         ret_fut = torch.futures.Future()
2025-08-14T21:17:32.0001584Z         >>>         rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:32.0001743Z         >>>             lambda fut: ret_fut.set_result(fut.wait() + z)
2025-08-14T21:17:32.0001827Z         >>>         )
2025-08-14T21:17:32.0001921Z         >>>         return ret_fut
2025-08-14T21:17:32.0002043Z         >>>
2025-08-14T21:17:32.0002161Z         >>>     @rpc.functions.async_execution
2025-08-14T21:17:32.0002284Z         >>>     def bound_async_add(self, to, x, y, z):
2025-08-14T21:17:32.0002462Z         >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-08-14T21:17:32.0002573Z         >>>             lambda fut: fut.wait() + z
2025-08-14T21:17:32.0002672Z         >>>         )
2025-08-14T21:17:32.0002753Z         >>>
2025-08-14T21:17:32.0002843Z         >>> # On worker0
2025-08-14T21:17:32.0002953Z         >>> ret = rpc.rpc_sync(
2025-08-14T21:17:32.0003042Z         >>>     "worker1",
2025-08-14T21:17:32.0003173Z         >>>     AsyncExecutionClass.static_async_add,
2025-08-14T21:17:32.0003300Z         >>>     args=("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:32.0003380Z         >>> )
2025-08-14T21:17:32.0003491Z         >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:32.0003579Z         >>>
2025-08-14T21:17:32.0003678Z         >>> ret = rpc.rpc_sync(
2025-08-14T21:17:32.0003775Z         >>>     "worker1",
2025-08-14T21:17:32.0003900Z         >>>     AsyncExecutionClass.class_async_add,
2025-08-14T21:17:32.0004015Z         >>>     args=("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:32.0004108Z         >>> )
2025-08-14T21:17:32.0004222Z         >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:32.0004302Z     
2025-08-14T21:17:32.0004537Z         This decorator also works with RRef helpers, i.e., .
2025-08-14T21:17:32.0004700Z         :meth:`torch.distributed.rpc.RRef.rpc_sync`,
2025-08-14T21:17:32.0004854Z         :meth:`torch.distributed.rpc.RRef.rpc_async`, and
2025-08-14T21:17:32.0005003Z         :meth:`torch.distributed.rpc.RRef.remote`.
2025-08-14T21:17:32.0005083Z     
2025-08-14T21:17:32.0005202Z         >>> from torch.distributed import rpc
2025-08-14T21:17:32.0005295Z         >>>
2025-08-14T21:17:32.0005430Z         >>> # reuse the AsyncExecutionClass class above
2025-08-14T21:17:32.0005598Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:32.0005806Z         >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2)
2025-08-14T21:17:32.0005921Z         >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:32.0006014Z         >>>
2025-08-14T21:17:32.0006166Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:32.0006402Z         >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait()
2025-08-14T21:17:32.0006534Z         >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:32.0006616Z         >>>
2025-08-14T21:17:32.0006780Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-08-14T21:17:32.0007012Z         >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here()
2025-08-14T21:17:32.0007131Z         >>> print(ret)  # prints tensor([4., 4.])
2025-08-14T21:17:32.0007225Z     
2025-08-14T21:17:32.0007475Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0007555Z     
2025-08-14T21:17:32.0007667Z       warnings.warn(msg)
2025-08-14T21:17:32.0007746Z     
2025-08-14T21:17:32.0007962Z --- Parse Warning: 87 / 146 ---
2025-08-14T21:17:32.0009219Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113.
2025-08-14T21:17:32.0009487Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0009583Z     
2025-08-14T21:17:32.0009788Z     Set device mapping between each RPC caller and callee pair. This
2025-08-14T21:17:32.0009971Z     function can be called multiple times to incrementally add
2025-08-14T21:17:32.0010097Z     device placement configurations.
2025-08-14T21:17:32.0010177Z     
2025-08-14T21:17:32.0010259Z     Args:
2025-08-14T21:17:32.0010451Z         to (str): Callee name.
2025-08-14T21:17:32.0010652Z         device_map (Dict of int, str, or torch.device): Device placement
2025-08-14T21:17:32.0010845Z             mappings from this worker to the callee. This map must be
2025-08-14T21:17:32.0010936Z             invertible.
2025-08-14T21:17:32.0011016Z     
2025-08-14T21:17:32.0011115Z     Example:
2025-08-14T21:17:32.0011234Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:32.0011328Z         >>> # both workers
2025-08-14T21:17:32.0011437Z         >>> def add(x, y):
2025-08-14T21:17:32.0011575Z         >>>     print(x)  # tensor([1., 1.], device='cuda:1')
2025-08-14T21:17:32.0011682Z         >>>     return x + y, (x + y).to(2)
2025-08-14T21:17:32.0011782Z         >>>
2025-08-14T21:17:32.0011873Z         >>> # on worker 0
2025-08-14T21:17:32.0012008Z         >>> options = TensorPipeRpcBackendOptions(
2025-08-14T21:17:32.0012126Z         >>>     num_worker_threads=8,
2025-08-14T21:17:32.0012240Z         >>>     device_maps={"worker1": {0: 1}}
2025-08-14T21:17:32.0012383Z         >>> # maps worker0's cuda:0 to worker1's cuda:1
2025-08-14T21:17:32.0012465Z         >>> )
2025-08-14T21:17:32.0012594Z         >>> options.set_device_map("worker1", {1: 2})
2025-08-14T21:17:32.0012739Z         >>> # maps worker0's cuda:1 to worker1's cuda:2
2025-08-14T21:17:32.0012823Z         >>>
2025-08-14T21:17:32.0012917Z         >>> rpc.init_rpc(
2025-08-14T21:17:32.0013056Z         >>>     "worker0",
2025-08-14T21:17:32.0013176Z         >>>     rank=0,
2025-08-14T21:17:32.0013305Z         >>>     world_size=2,
2025-08-14T21:17:32.0013445Z         >>>     backend=rpc.BackendType.TENSORPIPE,
2025-08-14T21:17:32.0013558Z         >>>     rpc_backend_options=options
2025-08-14T21:17:32.0020761Z         >>> )
2025-08-14T21:17:32.0020908Z         >>>
2025-08-14T21:17:32.0021015Z         >>> x = torch.ones(2)
2025-08-14T21:17:32.0021203Z         >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1))
2025-08-14T21:17:32.0021402Z         >>> # The first argument will be moved to cuda:1 on worker1. When
2025-08-14T21:17:32.0021599Z         >>> # sending the return value back, it will follow the invert of
2025-08-14T21:17:32.0021775Z         >>> # the device map, and hence will be moved back to cuda:0 and
2025-08-14T21:17:32.0021874Z         >>> # cuda:1 on worker0
2025-08-14T21:17:32.0022039Z         >>> print(rets[0])  # tensor([2., 2.], device='cuda:0')
2025-08-14T21:17:32.0022186Z         >>> print(rets[1])  # tensor([2., 2.], device='cuda:1')
2025-08-14T21:17:32.0022272Z     
2025-08-14T21:17:32.0022541Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0022623Z     
2025-08-14T21:17:32.0022730Z       warnings.warn(msg)
2025-08-14T21:17:32.0022811Z     
2025-08-14T21:17:32.0023054Z --- Parse Warning: 88 / 146 ---
2025-08-14T21:17:32.0024183Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19.
2025-08-14T21:17:32.0024451Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0024530Z     
2025-08-14T21:17:32.0024744Z     It has the same API as ``torch.autograd.profiler.profile`` class,
2025-08-14T21:17:32.0025027Z     except that it enables profiling on all threads running RPC server request callbacks.
2025-08-14T21:17:32.0025121Z     
2025-08-14T21:17:32.0025400Z     Context manager that manages autograd profiler state and holds a summary of results.
2025-08-14T21:17:32.0025635Z     Under the hood it just records events of functions being executed in C++ and
2025-08-14T21:17:32.0025880Z     exposes those events to Python. You can wrap any code into it and it will
2025-08-14T21:17:32.0026008Z     only report runtime of PyTorch functions.
2025-08-14T21:17:32.0026277Z     Note: profiler is thread local and is automatically propagated into the async tasks
2025-08-14T21:17:32.0026462Z     
2025-08-14T21:17:32.0026547Z     Args:
2025-08-14T21:17:32.0026816Z         enabled (bool, optional): Setting this to False makes this context manager a no-op.
2025-08-14T21:17:32.0026929Z             Default: ``True``.
2025-08-14T21:17:32.0027011Z     
2025-08-14T21:17:32.0027312Z         use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API.
2025-08-14T21:17:32.0027514Z             Adds approximately 4us of overhead to each tensor operation.
2025-08-14T21:17:32.0027613Z             Default: ``False``
2025-08-14T21:17:32.0027705Z     
2025-08-14T21:17:32.0027931Z         record_shapes (bool, optional): If shapes recording is set, information
2025-08-14T21:17:32.0028160Z             about input dimensions will be collected. This allows one to see which
2025-08-14T21:17:32.0028393Z             dimensions have been used under the hood and further group by them
2025-08-14T21:17:32.0028613Z             using prof.key_averages(group_by_input_shape=True). Please note that
2025-08-14T21:17:32.0028853Z             shape recording might skew your profiling data. It is recommended to
2025-08-14T21:17:32.0029089Z             use separate runs with and without shape recording to validate the timing.
2025-08-14T21:17:32.0029315Z             Most likely the skew will be negligible for bottom most events (in a case
2025-08-14T21:17:32.0029577Z             of nested function calls). But for higher level functions the total
2025-08-14T21:17:32.0029840Z             self cpu time might be artificially increased because of the shape
2025-08-14T21:17:32.0029932Z             collection.
2025-08-14T21:17:32.0030023Z     
2025-08-14T21:17:32.0030288Z         profile_memory (bool, optional): Whether to report memory usage, default: ``False``
2025-08-14T21:17:32.0030380Z     
2025-08-14T21:17:32.0030477Z     .. warning::
2025-08-14T21:17:32.0030679Z         Enabling memory profiling incurs additional profiler overhead
2025-08-14T21:17:32.0030775Z     
2025-08-14T21:17:32.0030863Z     .. warning::
2025-08-14T21:17:32.0031152Z         Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`),
2025-08-14T21:17:32.0031359Z         one cannot use the profiler with ``use_cuda = True`` to benchmark
2025-08-14T21:17:32.0031720Z         DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading,
2025-08-14T21:17:32.0031888Z         please use ``use_cuda = False`` or ``num_workers = 0``.
2025-08-14T21:17:32.0031979Z     
2025-08-14T21:17:32.0032065Z     Example:
2025-08-14T21:17:32.0032172Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0032264Z         >>> # On worker 0:
2025-08-14T21:17:32.0032355Z         >>> import torch
2025-08-14T21:17:32.0032496Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:32.0032635Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-08-14T21:17:32.0032759Z         >>> x, y = torch.tensor(1), torch.tensor(2)
2025-08-14T21:17:32.0032885Z         >>> outer_profile_rref = rpc.remote(
2025-08-14T21:17:32.0033051Z         ...     dst_worker_name, rpc._server_process_global_profile
2025-08-14T21:17:32.0033135Z         ... )
2025-08-14T21:17:32.0033276Z         >>> outer_profile_rref.rpc_sync().__enter__()
2025-08-14T21:17:32.0033423Z         >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y))
2025-08-14T21:17:32.0033550Z         >>> inner_profile_rref = rpc.remote(
2025-08-14T21:17:32.0033711Z         ...     dst_worker_name, rpc._server_process_global_profile
2025-08-14T21:17:32.0033797Z         ... )
2025-08-14T21:17:32.0033942Z         >>> inner_profile_rref.rpc_sync().__enter__()
2025-08-14T21:17:32.0034088Z         >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y))
2025-08-14T21:17:32.0034262Z         >>> inner_profile_rref.rpc_sync().__exit__(None, None, None)
2025-08-14T21:17:32.0034443Z         >>> outer_profile_rref.rpc_sync().__exit__(None, None, None)
2025-08-14T21:17:32.0034601Z         >>> print(inner_profile_rref.rpc_sync().key_averages())
2025-08-14T21:17:32.0034873Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0035197Z         Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-08-14T21:17:32.0035421Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0035625Z         sub        85.06%           76.275us         100.00%          89.667us         89.667us         1
2025-08-14T21:17:32.0035814Z         empty      14.94%           13.392us         14.94%           13.392us         13.392us         1
2025-08-14T21:17:32.0036036Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0036158Z         Self CPU time total: 89.667us
2025-08-14T21:17:32.0036320Z         >>> print(outer_profile_rref.rpc_sync().key_averages())
2025-08-14T21:17:32.0036557Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0036860Z         Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-08-14T21:17:32.0037104Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0037320Z         sub        35.65%           76.275us         41.91%           89.667us         89.667us         1
2025-08-14T21:17:32.0037531Z         empty      12.67%           27.101us         12.67%           27.101us         13.551us         2
2025-08-14T21:17:32.0037721Z         add        51.68%           110.550us        58.09%           124.259us        124.259us        1
2025-08-14T21:17:32.0037940Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-08-14T21:17:32.0038049Z         Self CPU time total: 213.926us
2025-08-14T21:17:32.0038161Z         >>> rpc.shutdown()
2025-08-14T21:17:32.0038239Z     
2025-08-14T21:17:32.0038332Z         >>> # On worker 1:
2025-08-14T21:17:32.0038473Z         >>> import torch.distributed.rpc as rpc
2025-08-14T21:17:32.0038611Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-08-14T21:17:32.0038786Z         >>> # wait for worker 0 to finish work, and then shutdown.
2025-08-14T21:17:32.0038884Z         >>> rpc.shutdown()
2025-08-14T21:17:32.0038966Z     
2025-08-14T21:17:32.0039231Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0039312Z     
2025-08-14T21:17:32.0039405Z       warnings.warn(msg)
2025-08-14T21:17:32.0039497Z     
2025-08-14T21:17:32.0039706Z --- Parse Warning: 89 / 146 ---
2025-08-14T21:17:32.0040703Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35.
2025-08-14T21:17:32.0040979Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0041059Z     
2025-08-14T21:17:32.0041334Z     :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s
2025-08-14T21:17:32.0041613Z     to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting
2025-08-14T21:17:32.0041879Z     the local components of :class:`DTensor`, call the function, and wrap the outputs to
2025-08-14T21:17:32.0042052Z     :class:`DTensor` according to the ``out_placements``.
2025-08-14T21:17:32.0042133Z     
2025-08-14T21:17:32.0042216Z     Args:
2025-08-14T21:17:32.0042439Z         func (Callable): the function to be applied on each local shard of
2025-08-14T21:17:32.0042538Z             :class:`DTensor` s.
2025-08-14T21:17:32.0042775Z         out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]):
2025-08-14T21:17:32.0043060Z             the desired placements of the :class:`DTensor` s in ``func``'s flattened output.
2025-08-14T21:17:32.0043301Z             If the flattened ``output`` is a single value, the ``out_placements`` should be
2025-08-14T21:17:32.0043560Z             of type `PlacementType`. Otherwise if the flattened ``output`` has multiple
2025-08-14T21:17:32.0043805Z             values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1
2025-08-14T21:17:32.0043927Z             mapping to the flattened ``output``.
2025-08-14T21:17:32.0044142Z             Besides, for :class:`Tensor` output, we use `PlacementType` as its
2025-08-14T21:17:32.0044410Z             placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType`
2025-08-14T21:17:32.0044520Z             should be `None`.
2025-08-14T21:17:32.0044756Z             Note that the only exception is when no :class:`DTensor` argument is passed
2025-08-14T21:17:32.0044978Z             in. In this case, even if `out_placements` is not `None`, the result function
2025-08-14T21:17:32.0045246Z             should ignore the desired placements because the function is not running with
2025-08-14T21:17:32.0045345Z             :class:`DTensor` s.
2025-08-14T21:17:32.0045515Z         in_placements (Tuple[`PlacementType`, ...], optional):
2025-08-14T21:17:32.0045846Z             the required placements of the :class:`DTensor` s in the flattened inputs of ``func``.
2025-08-14T21:17:32.0046103Z             If ``in_placements`` is specified, :meth:`local_map` would examine whether the
2025-08-14T21:17:32.0046372Z             placements of each :class:`DTensor` argument is the same as the required
2025-08-14T21:17:32.0046555Z             placements or not. If the placements are not the same and
2025-08-14T21:17:32.0046801Z             ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if
2025-08-14T21:17:32.0047062Z             ``redistribute_inputs`` is ``True``, the argument will be first redistributed to
2025-08-14T21:17:32.0047718Z             the required sharding placements before passing its local tensor to ``func``.
2025-08-14T21:17:32.0048343Z             The only exception is when required placements are not ``None`` and the
2025-08-14T21:17:32.0048942Z             argument is a :class:`torch.Tensor`. In this case, the placements examination
2025-08-14T21:17:32.0049529Z             will be skipped and the argument will be directly passed to ``func``.
2025-08-14T21:17:32.0050086Z             If ``in_placements`` is ``None``, no placements examination will be performed.
2025-08-14T21:17:32.0050540Z             Default: None
2025-08-14T21:17:32.0050906Z         in_grad_placements (Tuple[`PlacementType`, ...], optional):
2025-08-14T21:17:32.0051420Z             the placements hint of the :class:`DTensor` s gradient corresponds
2025-08-14T21:17:32.0051953Z             to the flattened input DTensor. This argument is the hint that user
2025-08-14T21:17:32.0052486Z             can give to :meth:`to_local` in case the gradient layout of the
2025-08-14T21:17:32.0053008Z             local tensor input does not match its :class:`DTensor` input layout.
2025-08-14T21:17:32.0053544Z             If not specified, we will assume the gradient layout of the local
2025-08-14T21:17:32.0054090Z             tensor input remains the same as the original :class:`DTensor` input
2025-08-14T21:17:32.0054661Z             and use that for gradient computation. Default: None.
2025-08-14T21:17:32.0055091Z         device_mesh (:class:`DeviceMesh`, optional):
2025-08-14T21:17:32.0055571Z             the device mesh that the output :class:`DTensor` s are placed on. If not
2025-08-14T21:17:32.0056158Z             specified, this will be inferred from the first input :class:`DTensor`'s device
2025-08-14T21:17:32.0056639Z             mesh. Default: None.
2025-08-14T21:17:32.0056915Z     
2025-08-14T21:17:32.0057103Z     Keyword Args:
2025-08-14T21:17:32.0057375Z         redistribute_inputs (bool, optional):
2025-08-14T21:17:32.0057897Z             the bool value indicating whether to reshard the input :class:`DTensor` s when
2025-08-14T21:17:32.0058521Z             their placements are different from the required input placements. If this
2025-08-14T21:17:32.0059122Z             value is ``False`` and some :class:`DTensor` input has a different placement,
2025-08-14T21:17:32.0059619Z             an exception will be raised. Default: False.
2025-08-14T21:17:32.0059960Z     
2025-08-14T21:17:32.0060153Z     Returns:
2025-08-14T21:17:32.0060547Z         A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor`
2025-08-14T21:17:32.0061165Z         and returns a :class:`DTensor` constructed from the return value of ``func``.
2025-08-14T21:17:32.0061600Z     
2025-08-14T21:17:32.0061799Z     Raises:
2025-08-14T21:17:32.0062167Z         AssertionError: For any non-DTensor output, we require its corresponding
2025-08-14T21:17:32.0062780Z             output placement in ``out_placements`` be None. An AssertionError will be raised
2025-08-14T21:17:32.0063268Z             if this is not the case.
2025-08-14T21:17:32.0063557Z     
2025-08-14T21:17:32.0063941Z         ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs
2025-08-14T21:17:32.0064471Z             a redistribution according to ``in_placements``.
2025-08-14T21:17:32.0064821Z     
2025-08-14T21:17:32.0065022Z     Example:
2025-08-14T21:17:32.0065288Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:32.0065712Z         >>> def mm_allreduce_forward(device_mesh, W, X):
2025-08-14T21:17:32.0066090Z         >>>     partial_sum_tensor = torch.mm(W, X)
2025-08-14T21:17:32.0066564Z         >>>     reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh)
2025-08-14T21:17:32.0067040Z         >>>     return reduced_tensor
2025-08-14T21:17:32.0067337Z         >>>
2025-08-14T21:17:32.0067596Z         >>> W = torch.randn(12, 8, requires_grad=False)
2025-08-14T21:17:32.0067957Z         >>> X = torch.randn(8, 16, requires_grad=False)
2025-08-14T21:17:32.0068305Z         >>> Y = torch.mm(W, X)
2025-08-14T21:17:32.0068683Z         >>> row_wise = [Shard(0)]  # row-wise sharding placements on 1-d mesh
2025-08-14T21:17:32.0069169Z         >>> col_wise = [Shard(1)]  # col-wise sharding placements on 1-d mesh
2025-08-14T21:17:32.0069561Z         >>>
2025-08-14T21:17:32.0069967Z         >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion
2025-08-14T21:17:32.0070478Z         >>> local_mm_allreduce_forward = local_map(
2025-08-14T21:17:32.0070837Z         >>>     mm_allreduce_forward,
2025-08-14T21:17:32.0071166Z         >>>     out_placements=[Replicate()],
2025-08-14T21:17:32.0071606Z         >>>     in_placements=[col_wise, row_wise],
2025-08-14T21:17:32.0071944Z         >>>     device_mesh=device_mesh,
2025-08-14T21:17:32.0072245Z         >>> )
2025-08-14T21:17:32.0072464Z         >>>
2025-08-14T21:17:32.0072679Z         >>> W_dt = distribute_tensor(
2025-08-14T21:17:32.0073001Z         ...     W, device_mesh, (col_wise)
2025-08-14T21:17:32.0073335Z         ... )  # col-wisely sharded W tensor
2025-08-14T21:17:32.0073655Z         >>> X_dt = distribute_tensor(
2025-08-14T21:17:32.0073969Z         ...     X, device_mesh, (row_wise)
2025-08-14T21:17:32.0074302Z         ... )  # row-wisely sharded X tensor
2025-08-14T21:17:32.0074631Z         >>> Y_dt = local_mm_allreduce_forward(
2025-08-14T21:17:32.0074965Z         ...     device_mesh, W_dt, X_dt
2025-08-14T21:17:32.0075330Z         ... )  # apply local_mm_allreduce_forward to DTensors
2025-08-14T21:17:32.0075688Z     
2025-08-14T21:17:32.0075994Z     .. note:: This API is currently experimental and subject to change
2025-08-14T21:17:32.0076390Z     
2025-08-14T21:17:32.0076765Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0077210Z     
2025-08-14T21:17:32.0077423Z       warnings.warn(msg)
2025-08-14T21:17:32.0077684Z     
2025-08-14T21:17:32.0078012Z --- Parse Warning: 90 / 146 ---
2025-08-14T21:17:32.0079403Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25.
2025-08-14T21:17:32.0080882Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0081356Z     
2025-08-14T21:17:32.0081746Z     :meth:`register_sharding` is an experimental API that allows users to register sharding
2025-08-14T21:17:32.0082404Z     strategies for an operator when the tensor inputs and outputs are DTensor.
2025-08-14T21:17:32.0083021Z     It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``,
2025-08-14T21:17:32.0083633Z     e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2)
2025-08-14T21:17:32.0084273Z     when users would like to overwrite default sharding strategies of existing operators.
2025-08-14T21:17:32.0084765Z     
2025-08-14T21:17:32.0084970Z     Args:
2025-08-14T21:17:32.0085234Z         op (Union[OpOverload, List[OpOverload]]):
2025-08-14T21:17:32.0085665Z             An op or a list of ops to register the customized sharding function.
2025-08-14T21:17:32.0086055Z     
2025-08-14T21:17:32.0086250Z     Returns:
2025-08-14T21:17:32.0086717Z         A function decorator which can be used to wrap a function that defines the sharding
2025-08-14T21:17:32.0087412Z         strategy for the operator specified in ``op``. The defined sharding strategy will be
2025-08-14T21:17:32.0088116Z         registered to DTensor and will override the default sharding strategy if DTensor has
2025-08-14T21:17:32.0088823Z         already implemented the operator. The customized sharding function takes the same inputs
2025-08-14T21:17:32.0089480Z         as the original op (except that if an arg is a :class:`torch.Tensor`, it will be
2025-08-14T21:17:32.0090120Z         replaced by a tensor-like object that DTensor uses internally). The function should
2025-08-14T21:17:32.0090791Z         return a sequence of 2-tuples, each specifying acceptable output placements and its
2025-08-14T21:17:32.0091305Z         corresponding input placements.
2025-08-14T21:17:32.0091601Z     
2025-08-14T21:17:32.0091801Z     Example:
2025-08-14T21:17:32.0092051Z         >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:32.0092407Z         >>> @register_sharding(aten._softmax.default)
2025-08-14T21:17:32.0092808Z         >>> def custom_softmax_sharding(x, dim, half_to_float):
2025-08-14T21:17:32.0093221Z         >>>     softmax_dim = dim if dim >= 0 else dim + x.ndim
2025-08-14T21:17:32.0093580Z         >>>     acceptable_shardings = []
2025-08-14T21:17:32.0093883Z         >>>
2025-08-14T21:17:32.0094186Z         >>>     all_replicate = ([Replicate()], [Replicate(), None, None])
2025-08-14T21:17:32.0094638Z         >>>     acceptable_shardings.append(all_replicate)
2025-08-14T21:17:32.0094967Z         >>>
2025-08-14T21:17:32.0095216Z         >>>     for sharding_dim in range(x.ndim):
2025-08-14T21:17:32.0095572Z         >>>         if sharding_dim != softmax_dim:
2025-08-14T21:17:32.0095894Z         >>>             all_sharded = (
2025-08-14T21:17:32.0096215Z         >>>                 [Shard(sharding_dim)],
2025-08-14T21:17:32.0096570Z         >>>                 [Shard(sharding_dim), None, None],
2025-08-14T21:17:32.0096895Z         >>>             )
2025-08-14T21:17:32.0097204Z         >>>             acceptable_shardings.append(all_sharded)
2025-08-14T21:17:32.0097550Z         >>>
2025-08-14T21:17:32.0097773Z         >>>     return acceptable_shardings
2025-08-14T21:17:32.0098082Z     
2025-08-14T21:17:32.0098397Z     .. note:: This API is currently experimental and subject to change
2025-08-14T21:17:32.0098792Z     
2025-08-14T21:17:32.0099145Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0099599Z     
2025-08-14T21:17:32.0099809Z       warnings.warn(msg)
2025-08-14T21:17:32.0100053Z     
2025-08-14T21:17:32.0100411Z --- Parse Warning: 91 / 146 ---
2025-08-14T21:17:32.0101678Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428.
2025-08-14T21:17:32.0103087Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0103546Z     
2025-08-14T21:17:32.0104051Z     Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to
2025-08-14T21:17:32.0104898Z     ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``.
2025-08-14T21:17:32.0105412Z     
2025-08-14T21:17:32.0105614Z     Keyword Args:
2025-08-14T21:17:32.0105961Z         input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:32.0106605Z             The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-08-14T21:17:32.0107407Z             DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-08-14T21:17:32.0108003Z             as a placeholder. default: None.
2025-08-14T21:17:32.0108502Z         desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:32.0109466Z             The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:32.0110425Z             have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-08-14T21:17:32.0111070Z         input_kwarg_layouts (Dict[str, Placement]):
2025-08-14T21:17:32.0111768Z             The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-08-14T21:17:32.0112349Z             default: None
2025-08-14T21:17:32.0112683Z         desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-08-14T21:17:32.0113331Z             The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:32.0113966Z             have the desired DTensor layouts. default: None.
2025-08-14T21:17:32.0114352Z         use_local_output (bool, optional):
2025-08-14T21:17:32.0114942Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-08-14T21:17:32.0115510Z     Returns:
2025-08-14T21:17:32.0115945Z         A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs.
2025-08-14T21:17:32.0116463Z     
2025-08-14T21:17:32.0116670Z     Example::
2025-08-14T21:17:32.0116902Z         >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:32.0117434Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput
2025-08-14T21:17:32.0118065Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:32.0118450Z         >>> ...
2025-08-14T21:17:32.0118892Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:32.0119445Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:32.0119773Z         >>>
2025-08-14T21:17:32.0120231Z         >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor
2025-08-14T21:17:32.0120849Z         >>> # and then redistributed to Replicated DTensor.
2025-08-14T21:17:32.0121222Z         >>> parallelize_module(
2025-08-14T21:17:32.0121534Z         >>>     block, # this can be a submodule or module
2025-08-14T21:17:32.0121878Z         >>>     tp_mesh,
2025-08-14T21:17:32.0122148Z         >>>     parallelize_plan={
2025-08-14T21:17:32.0122460Z         >>>         "attn": PrepareModuleInput(
2025-08-14T21:17:32.0122908Z         >>>             input_layouts=(Shard(0), None, None, ...),
2025-08-14T21:17:32.0123336Z         >>>             desired_input_layouts=(Replicate(), None, None, ...)
2025-08-14T21:17:32.0123712Z         >>>         ),
2025-08-14T21:17:32.0123942Z         >>>     }
2025-08-14T21:17:32.0124167Z         >>> )
2025-08-14T21:17:32.0124382Z     
2025-08-14T21:17:32.0124745Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0125206Z     
2025-08-14T21:17:32.0125421Z       warnings.warn(msg)
2025-08-14T21:17:32.0125664Z     
2025-08-14T21:17:32.0126007Z --- Parse Warning: 92 / 146 ---
2025-08-14T21:17:32.0127283Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597.
2025-08-14T21:17:32.0128693Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0129152Z     
2025-08-14T21:17:32.0129663Z     Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to
2025-08-14T21:17:32.0130513Z     ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``.
2025-08-14T21:17:32.0131036Z     
2025-08-14T21:17:32.0131244Z     Keyword Args:
2025-08-14T21:17:32.0131654Z         output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:32.0132307Z             The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-08-14T21:17:32.0133136Z             DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-08-14T21:17:32.0133779Z             ``None`` need to be specified as a placeholder.
2025-08-14T21:17:32.0134240Z         desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:32.0134937Z             The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-08-14T21:17:32.0135578Z             have the desired DTensor layouts.
2025-08-14T21:17:32.0135925Z         use_local_output (bool, optional):
2025-08-14T21:17:32.0136515Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-08-14T21:17:32.0137078Z     Returns:
2025-08-14T21:17:32.0137510Z         A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs.
2025-08-14T21:17:32.0138011Z     
2025-08-14T21:17:32.0138204Z     Example::
2025-08-14T21:17:32.0138456Z         >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:32.0139000Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput
2025-08-14T21:17:32.0139630Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:32.0140014Z         >>> ...
2025-08-14T21:17:32.0140457Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:32.0141017Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:32.0141335Z         >>>
2025-08-14T21:17:32.0141871Z         >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor
2025-08-14T21:17:32.0142531Z         >>> # and then redistributed to Sharded DTensor.
2025-08-14T21:17:32.0142886Z         >>> parallelize_module(
2025-08-14T21:17:32.0143215Z         >>>     block, # this can be a submodule or module
2025-08-14T21:17:32.0143559Z         >>>     tp_mesh,
2025-08-14T21:17:32.0143868Z         >>>     parallelize_plan = PrepareModuleOutput(
2025-08-14T21:17:32.0144229Z         >>>         output_layouts=Replicate(),
2025-08-14T21:17:32.0144578Z         >>>         desired_output_layouts=Shard(0)
2025-08-14T21:17:32.0144896Z         >>>     )
2025-08-14T21:17:32.0145105Z         >>> )
2025-08-14T21:17:32.0145363Z     
2025-08-14T21:17:32.0145732Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0146182Z     
2025-08-14T21:17:32.0146397Z       warnings.warn(msg)
2025-08-14T21:17:32.0146652Z     
2025-08-14T21:17:32.0146960Z --- Parse Warning: 93 / 146 ---
2025-08-14T21:17:32.0148266Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705.
2025-08-14T21:17:32.0149711Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0150186Z     
2025-08-14T21:17:32.0150728Z     Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module
2025-08-14T21:17:32.0151781Z     to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution
2025-08-14T21:17:32.0152709Z     according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of
2025-08-14T21:17:32.0153422Z     :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`.
2025-08-14T21:17:32.0153819Z     
2025-08-14T21:17:32.0154030Z     Keyword Args:
2025-08-14T21:17:32.0154427Z         input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:32.0155122Z             The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-08-14T21:17:32.0155933Z             DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-08-14T21:17:32.0156534Z             as a placeholder. default: None.
2025-08-14T21:17:32.0156995Z         desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-08-14T21:17:32.0157722Z             The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:32.0158612Z             have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-08-14T21:17:32.0159265Z         input_kwarg_layouts (Dict[str, Placement]):
2025-08-14T21:17:32.0159900Z             The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-08-14T21:17:32.0160483Z             default: None
2025-08-14T21:17:32.0160821Z         desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-08-14T21:17:32.0161471Z             The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-08-14T21:17:32.0162097Z             have the desired DTensor layouts. default: None.
2025-08-14T21:17:32.0162479Z         use_local_input (bool, optional):
2025-08-14T21:17:32.0163065Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-08-14T21:17:32.0163708Z         output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:32.0164312Z             The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-08-14T21:17:32.0165150Z             DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-08-14T21:17:32.0165795Z             ``None`` need to be specified as a placeholder.
2025-08-14T21:17:32.0166243Z         desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-08-14T21:17:32.0166948Z             The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-08-14T21:17:32.0167575Z             have the desired DTensor layouts.
2025-08-14T21:17:32.0167922Z         use_local_output (bool, optional):
2025-08-14T21:17:32.0168540Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-08-14T21:17:32.0169113Z     Returns:
2025-08-14T21:17:32.0169617Z         A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs.
2025-08-14T21:17:32.0170172Z     
2025-08-14T21:17:32.0170385Z     Example::
2025-08-14T21:17:32.0170638Z         >>> # xdoctest: +SKIP(failing)
2025-08-14T21:17:32.0171198Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput
2025-08-14T21:17:32.0171844Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-08-14T21:17:32.0172238Z         >>> ...
2025-08-14T21:17:32.0172679Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-08-14T21:17:32.0173224Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-08-14T21:17:32.0173556Z         >>>
2025-08-14T21:17:32.0174020Z         >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor
2025-08-14T21:17:32.0174833Z         >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated
2025-08-14T21:17:32.0175508Z         >>> # as Replicated DTensor and then redistributed to Sharded DTensor.
2025-08-14T21:17:32.0175941Z         >>> parallelize_module(
2025-08-14T21:17:32.0176297Z         >>>     block, # this can be a submodule or module
2025-08-14T21:17:32.0176692Z         >>>     tp_mesh,
2025-08-14T21:17:32.0176966Z         >>>     parallelize_plan={
2025-08-14T21:17:32.0177313Z         >>>         "attn": PrepareModuleInputOutput(
2025-08-14T21:17:32.0177685Z         >>>             input_layouts=(Shard(0), None, None, ...),
2025-08-14T21:17:32.0178111Z         >>>             desired_input_layouts=(Replicate(), None, None, ...),
2025-08-14T21:17:32.0178522Z         >>>             output_layouts=Replicate(),
2025-08-14T21:17:32.0178875Z         >>>             desired_output_layouts=Shard(0),
2025-08-14T21:17:32.0179205Z         >>>         ),
2025-08-14T21:17:32.0179443Z         >>>     }
2025-08-14T21:17:32.0179654Z         >>> )
2025-08-14T21:17:32.0179867Z     
2025-08-14T21:17:32.0180236Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0180676Z     
2025-08-14T21:17:32.0180890Z       warnings.warn(msg)
2025-08-14T21:17:32.0181140Z     
2025-08-14T21:17:32.0181466Z --- Parse Warning: 94 / 146 ---
2025-08-14T21:17:32.0182793Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56.
2025-08-14T21:17:32.0184267Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0184734Z     
2025-08-14T21:17:32.0185138Z     Creates a multivariate normal distribution with covariance matrix having a low-rank form
2025-08-14T21:17:32.0185754Z     parameterized by :attr:`cov_factor` and :attr:`cov_diag`::
2025-08-14T21:17:32.0186134Z     
2025-08-14T21:17:32.0186423Z         covariance_matrix = cov_factor @ cov_factor.T + cov_diag
2025-08-14T21:17:32.0186780Z     
2025-08-14T21:17:32.0186982Z     Example:
2025-08-14T21:17:32.0187258Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-08-14T21:17:32.0187645Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:32.0188026Z         >>> m = LowRankMultivariateNormal(
2025-08-14T21:17:32.0188435Z         ...     torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2)
2025-08-14T21:17:32.0188801Z         ... )
2025-08-14T21:17:32.0189212Z         >>> m.sample()  # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]`
2025-08-14T21:17:32.0189715Z         tensor([-0.2102, -0.5429])
2025-08-14T21:17:32.0189993Z     
2025-08-14T21:17:32.0190180Z     Args:
2025-08-14T21:17:32.0190575Z         loc (Tensor): mean of the distribution with shape `batch_shape + event_shape`
2025-08-14T21:17:32.0191197Z         cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape
2025-08-14T21:17:32.0191768Z             `batch_shape + event_shape + (rank,)`
2025-08-14T21:17:32.0192260Z         cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape
2025-08-14T21:17:32.0192750Z             `batch_shape + event_shape`
2025-08-14T21:17:32.0193035Z     
2025-08-14T21:17:32.0193233Z     Note:
2025-08-14T21:17:32.0193621Z         The computation for determinant and inverse of covariance matrix is avoided when
2025-08-14T21:17:32.0194249Z         `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity
2025-08-14T21:17:32.0194815Z         <https://en.wikipedia.org/wiki/Woodbury_matrix_identity>`_ and
2025-08-14T21:17:32.0195430Z         `matrix determinant lemma <https://en.wikipedia.org/wiki/Matrix_determinant_lemma>`_.
2025-08-14T21:17:32.0196099Z         Thanks to these formulas, we just need to compute the determinant and inverse of
2025-08-14T21:17:32.0196589Z         the small size "capacitance" matrix::
2025-08-14T21:17:32.0196902Z     
2025-08-14T21:17:32.0197200Z             capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor
2025-08-14T21:17:32.0197585Z     
2025-08-14T21:17:32.0197978Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0198456Z     
2025-08-14T21:17:32.0198716Z       warnings.warn(msg)
2025-08-14T21:17:32.0198960Z     
2025-08-14T21:17:32.0199279Z --- Parse Warning: 95 / 146 ---
2025-08-14T21:17:32.0200529Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15.
2025-08-14T21:17:32.0201898Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0202366Z     
2025-08-14T21:17:32.0202706Z     The `MixtureSameFamily` distribution implements a (batch of) mixture
2025-08-14T21:17:32.0203299Z     distribution where all component are from different parameterizations of
2025-08-14T21:17:32.0203868Z     the same distribution type. It is parameterized by a `Categorical`
2025-08-14T21:17:32.0204398Z     "selecting distribution" (over `k` component) and a component
2025-08-14T21:17:32.0204915Z     distribution, i.e., a `Distribution` with a rightmost batch shape
2025-08-14T21:17:32.0205389Z     (equal to `[k]`) which indexes each (batch of) component.
2025-08-14T21:17:32.0205744Z     
2025-08-14T21:17:32.0205949Z     Examples::
2025-08-14T21:17:32.0206155Z     
2025-08-14T21:17:32.0206383Z         >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:32.0206819Z         >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally
2025-08-14T21:17:32.0207256Z         >>> # weighted normal distributions
2025-08-14T21:17:32.0207591Z         >>> mix = D.Categorical(torch.ones(5,))
2025-08-14T21:17:32.0207969Z         >>> comp = D.Normal(torch.randn(5,), torch.rand(5,))
2025-08-14T21:17:32.0208352Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:32.0208658Z     
2025-08-14T21:17:32.0208970Z         >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally
2025-08-14T21:17:32.0209618Z         >>> # weighted bivariate normal distributions
2025-08-14T21:17:32.0209970Z         >>> mix = D.Categorical(torch.ones(5,))
2025-08-14T21:17:32.0210321Z         >>> comp = D.Independent(D.Normal(
2025-08-14T21:17:32.0210673Z         ...          torch.randn(5,2), torch.rand(5,2)), 1)
2025-08-14T21:17:32.0211044Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:32.0211345Z     
2025-08-14T21:17:32.0211642Z         >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each
2025-08-14T21:17:32.0212148Z         >>> # consisting of 5 random weighted bivariate normal distributions
2025-08-14T21:17:32.0212686Z         >>> mix = D.Categorical(torch.rand(3,5))
2025-08-14T21:17:32.0213033Z         >>> comp = D.Independent(D.Normal(
2025-08-14T21:17:32.0213392Z         ...         torch.randn(3,5,2), torch.rand(3,5,2)), 1)
2025-08-14T21:17:32.0213750Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-08-14T21:17:32.0214062Z     
2025-08-14T21:17:32.0214259Z     Args:
2025-08-14T21:17:32.0214574Z         mixture_distribution: `torch.distributions.Categorical`-like
2025-08-14T21:17:32.0215092Z             instance. Manages the probability of selecting component.
2025-08-14T21:17:32.0215564Z             The number of categories must match the rightmost batch
2025-08-14T21:17:32.0216040Z             dimension of the `component_distribution`. Must have either
2025-08-14T21:17:32.0216477Z             scalar `batch_shape` or `batch_shape` matching
2025-08-14T21:17:32.0216872Z             `component_distribution.batch_shape[:-1]`
2025-08-14T21:17:32.0217352Z         component_distribution: `torch.distributions.Distribution`-like
2025-08-14T21:17:32.0217864Z             instance. Right-most batch dimension indexes component.
2025-08-14T21:17:32.0218249Z     
2025-08-14T21:17:32.0218628Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0219086Z     
2025-08-14T21:17:32.0219288Z       warnings.warn(msg)
2025-08-14T21:17:32.0219544Z     
2025-08-14T21:17:32.0219922Z --- Parse Warning: 96 / 146 ---
2025-08-14T21:17:32.0221220Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120.
2025-08-14T21:17:32.0222600Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0223070Z     
2025-08-14T21:17:32.0223366Z     Creates a RelaxedBernoulli distribution, parametrized by
2025-08-14T21:17:32.0223866Z     :attr:`temperature`, and either :attr:`probs` or :attr:`logits`
2025-08-14T21:17:32.0224395Z     (but not both). This is a relaxed version of the `Bernoulli` distribution,
2025-08-14T21:17:32.0224925Z     so the values are in (0, 1), and has reparametrizable samples.
2025-08-14T21:17:32.0225298Z     
2025-08-14T21:17:32.0225505Z     Example::
2025-08-14T21:17:32.0225725Z     
2025-08-14T21:17:32.0225968Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:32.0226360Z         >>> m = RelaxedBernoulli(torch.tensor([2.2]),
2025-08-14T21:17:32.0226736Z         ...                      torch.tensor([0.1, 0.2, 0.3, 0.99]))
2025-08-14T21:17:32.0227060Z         >>> m.sample()
2025-08-14T21:17:32.0227336Z         tensor([ 0.2951,  0.3442,  0.8918,  0.9021])
2025-08-14T21:17:32.0227649Z     
2025-08-14T21:17:32.0227834Z     Args:
2025-08-14T21:17:32.0228097Z         temperature (Tensor): relaxation temperature
2025-08-14T21:17:32.0228528Z         probs (Number, Tensor): the probability of sampling `1`
2025-08-14T21:17:32.0228991Z         logits (Number, Tensor): the log-odds of sampling `1`
2025-08-14T21:17:32.0229338Z     
2025-08-14T21:17:32.0229705Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0230164Z     
2025-08-14T21:17:32.0230365Z       warnings.warn(msg)
2025-08-14T21:17:32.0230617Z     
2025-08-14T21:17:32.0230932Z --- Parse Warning: 97 / 146 ---
2025-08-14T21:17:32.0232284Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109.
2025-08-14T21:17:32.0233719Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0234192Z     
2025-08-14T21:17:32.0234526Z     Creates a RelaxedOneHotCategorical distribution parametrized by
2025-08-14T21:17:32.0235100Z     :attr:`temperature`, and either :attr:`probs` or :attr:`logits`.
2025-08-14T21:17:32.0235656Z     This is a relaxed version of the :class:`OneHotCategorical` distribution, so
2025-08-14T21:17:32.0236181Z     its samples are on simplex, and are reparametrizable.
2025-08-14T21:17:32.0236529Z     
2025-08-14T21:17:32.0236739Z     Example::
2025-08-14T21:17:32.0236957Z     
2025-08-14T21:17:32.0237200Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:32.0237619Z         >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]),
2025-08-14T21:17:32.0238025Z         ...                              torch.tensor([0.1, 0.2, 0.3, 0.4]))
2025-08-14T21:17:32.0238365Z         >>> m.sample()
2025-08-14T21:17:32.0238629Z         tensor([ 0.1294,  0.2324,  0.3859,  0.2523])
2025-08-14T21:17:32.0238944Z     
2025-08-14T21:17:32.0239144Z     Args:
2025-08-14T21:17:32.0239399Z         temperature (Tensor): relaxation temperature
2025-08-14T21:17:32.0239771Z         probs (Tensor): event probabilities
2025-08-14T21:17:32.0240191Z         logits (Tensor): unnormalized log probability for each event
2025-08-14T21:17:32.0240567Z     
2025-08-14T21:17:32.0240934Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0241390Z     
2025-08-14T21:17:32.0241591Z       warnings.warn(msg)
2025-08-14T21:17:32.0241846Z     
2025-08-14T21:17:32.0242159Z --- Parse Warning: 98 / 146 ---
2025-08-14T21:17:32.0243480Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245.
2025-08-14T21:17:32.0244883Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0245462Z     Return a new dict with new, potentially nested, key value pair
2025-08-14T21:17:32.0245850Z     
2025-08-14T21:17:32.0246049Z         >>> purchase = {
2025-08-14T21:17:32.0246319Z         ...     "name": "Alice",
2025-08-14T21:17:32.0246679Z         ...     "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:32.0247095Z         ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:32.0247400Z         ... }
2025-08-14T21:17:32.0247737Z         >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00])  # doctest: +SKIP
2025-08-14T21:17:32.0248176Z         {'credit card': '5555-1234-1234-1234',
2025-08-14T21:17:32.0248481Z          'name': 'Alice',
2025-08-14T21:17:32.0248818Z          'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}}
2025-08-14T21:17:32.0249187Z         
2025-08-14T21:17:32.0249548Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0250000Z     
2025-08-14T21:17:32.0250214Z       warnings.warn(msg)
2025-08-14T21:17:32.0250452Z     
2025-08-14T21:17:32.0250754Z --- Parse Warning: 99 / 146 ---
2025-08-14T21:17:32.0252015Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261.
2025-08-14T21:17:32.0253405Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0253933Z     Update value in a (potentially) nested dictionary
2025-08-14T21:17:32.0254287Z     
2025-08-14T21:17:32.0254494Z         inputs:
2025-08-14T21:17:32.0254742Z         d - dictionary on which to operate
2025-08-14T21:17:32.0255191Z         keys - list or tuple giving the location of the value to be changed in d
2025-08-14T21:17:32.0255659Z         func - function to operate on that value
2025-08-14T21:17:32.0255980Z     
2025-08-14T21:17:32.0256274Z         If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the
2025-08-14T21:17:32.0256820Z         original dictionary with v replaced by func(v), but does not mutate the
2025-08-14T21:17:32.0257314Z         original dictionary.
2025-08-14T21:17:32.0257570Z     
2025-08-14T21:17:32.0257896Z         If k0 is not a key in d, update_in creates nested dictionaries to the depth
2025-08-14T21:17:32.0258461Z         specified by the keys, with the innermost value set to func(default).
2025-08-14T21:17:32.0258868Z     
2025-08-14T21:17:32.0259089Z         >>> inc = lambda x: x + 1
2025-08-14T21:17:32.0259400Z         >>> update_in({"a": 0}, ["a"], inc)
2025-08-14T21:17:32.0259713Z         {'a': 1}
2025-08-14T21:17:32.0259925Z     
2025-08-14T21:17:32.0260139Z         >>> transaction = {
2025-08-14T21:17:32.0260418Z         ...     "name": "Alice",
2025-08-14T21:17:32.0260786Z         ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:32.0261222Z         ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:32.0261543Z         ... }
2025-08-14T21:17:32.0261885Z         >>> update_in(transaction, ["purchase", "costs"], sum)  # doctest: +SKIP
2025-08-14T21:17:32.0262336Z         {'credit card': '5555-1234-1234-1234',
2025-08-14T21:17:32.0262658Z          'name': 'Alice',
2025-08-14T21:17:32.0262985Z          'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}
2025-08-14T21:17:32.0263354Z     
2025-08-14T21:17:32.0263591Z         >>> # updating a value when k0 is not in d
2025-08-14T21:17:32.0263959Z         >>> update_in({}, [1, 2, 3], str, default="bar")
2025-08-14T21:17:32.0264356Z         {1: {2: {3: 'bar'}}}
2025-08-14T21:17:32.0264656Z         >>> update_in({1: "foo"}, [2, 3, 4], inc, 0)
2025-08-14T21:17:32.0265010Z         {1: 'foo', 2: {3: {4: 1}}}
2025-08-14T21:17:32.0265279Z         
2025-08-14T21:17:32.0265649Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0266100Z     
2025-08-14T21:17:32.0266301Z       warnings.warn(msg)
2025-08-14T21:17:32.0266554Z     
2025-08-14T21:17:32.0266858Z --- Parse Warning: 100 / 146 ---
2025-08-14T21:17:32.0268090Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320.
2025-08-14T21:17:32.0269472Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0270032Z     Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys.
2025-08-14T21:17:32.0270398Z     
2025-08-14T21:17:32.0270680Z         If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless
2025-08-14T21:17:32.0271185Z         ``no_default`` is specified, then it raises KeyError or IndexError.
2025-08-14T21:17:32.0271667Z     
2025-08-14T21:17:32.0271983Z         ``get_in`` is a generalization of ``operator.getitem`` for nested data
2025-08-14T21:17:32.0272446Z         structures such as dictionaries and lists.
2025-08-14T21:17:32.0272775Z     
2025-08-14T21:17:32.0272989Z         >>> transaction = {
2025-08-14T21:17:32.0273250Z         ...     "name": "Alice",
2025-08-14T21:17:32.0273630Z         ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-08-14T21:17:32.0274059Z         ...     "credit card": "5555-1234-1234-1234",
2025-08-14T21:17:32.0274364Z         ... }
2025-08-14T21:17:32.0274631Z         >>> get_in(["purchase", "items", 0], transaction)
2025-08-14T21:17:32.0274971Z         'Apple'
2025-08-14T21:17:32.0275078Z         >>> get_in(["name"], transaction)
2025-08-14T21:17:32.0275162Z         'Alice'
2025-08-14T21:17:32.0275307Z         >>> get_in(["purchase", "total"], transaction)
2025-08-14T21:17:32.0275453Z         >>> get_in(["purchase", "items", "apple"], transaction)
2025-08-14T21:17:32.0275597Z         >>> get_in(["purchase", "items", 10], transaction)
2025-08-14T21:17:32.0275730Z         >>> get_in(["purchase", "total"], transaction, 0)
2025-08-14T21:17:32.0275811Z         0
2025-08-14T21:17:32.0275934Z         >>> get_in(["y"], {}, no_default=True)
2025-08-14T21:17:32.0276046Z         Traceback (most recent call last):
2025-08-14T21:17:32.0276178Z             ...
2025-08-14T21:17:32.0276282Z         KeyError: 'y'
2025-08-14T21:17:32.0276361Z     
2025-08-14T21:17:32.0276447Z         See Also:
2025-08-14T21:17:32.0276557Z             itertoolz.get
2025-08-14T21:17:32.0276657Z             operator.getitem
2025-08-14T21:17:32.0276739Z         
2025-08-14T21:17:32.0277009Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0277089Z     
2025-08-14T21:17:32.0277202Z       warnings.warn(msg)
2025-08-14T21:17:32.0277280Z     
2025-08-14T21:17:32.0277475Z --- Parse Warning: 101 / 146 ---
2025-08-14T21:17:32.0278505Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373.
2025-08-14T21:17:32.0278771Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0278884Z     Group a collection by a key function
2025-08-14T21:17:32.0278976Z     
2025-08-14T21:17:32.0279140Z         >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"]
2025-08-14T21:17:32.0279274Z         >>> groupby(len, names)  # doctest: +SKIP
2025-08-14T21:17:32.0279434Z         {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}
2025-08-14T21:17:32.0279591Z     
2025-08-14T21:17:32.0279711Z         >>> iseven = lambda x: x % 2 == 0
2025-08-14T21:17:32.0279911Z         >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8])  # doctest: +SKIP
2025-08-14T21:17:32.0280021Z         {False: [1, 3, 5, 7], True: [2, 4, 6, 8]}
2025-08-14T21:17:32.0280114Z     
2025-08-14T21:17:32.0280257Z         Non-callable keys imply grouping on a member.
2025-08-14T21:17:32.0280337Z     
2025-08-14T21:17:32.0280438Z         >>> groupby(
2025-08-14T21:17:32.0280526Z         ...     "gender",
2025-08-14T21:17:32.0280607Z         ...     [
2025-08-14T21:17:32.0280744Z         ...         {"name": "Alice", "gender": "F"},
2025-08-14T21:17:32.0280857Z         ...         {"name": "Bob", "gender": "M"},
2025-08-14T21:17:32.0280990Z         ...         {"name": "Charlie", "gender": "M"},
2025-08-14T21:17:32.0281072Z         ...     ],
2025-08-14T21:17:32.0281168Z         ... )  # doctest:+SKIP
2025-08-14T21:17:32.0281291Z         {'F': [{'gender': 'F', 'name': 'Alice'}],
2025-08-14T21:17:32.0281402Z          'M': [{'gender': 'M', 'name': 'Bob'},
2025-08-14T21:17:32.0281514Z                {'gender': 'M', 'name': 'Charlie'}]}
2025-08-14T21:17:32.0281604Z     
2025-08-14T21:17:32.0281746Z         Not to be confused with ``itertools.groupby``
2025-08-14T21:17:32.0281827Z     
2025-08-14T21:17:32.0281922Z         See Also:
2025-08-14T21:17:32.0282006Z             countby
2025-08-14T21:17:32.0282086Z         
2025-08-14T21:17:32.0282351Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0282429Z     
2025-08-14T21:17:32.0282537Z       warnings.warn(msg)
2025-08-14T21:17:32.0282616Z     
2025-08-14T21:17:32.0282804Z --- Parse Warning: 102 / 146 ---
2025-08-14T21:17:32.0283659Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142.
2025-08-14T21:17:32.0283920Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0284151Z     Return the recommended gain value for the given nonlinearity function.
2025-08-14T21:17:32.0284240Z     
2025-08-14T21:17:32.0284342Z         The values are as follows:
2025-08-14T21:17:32.0284434Z     
2025-08-14T21:17:32.0284549Z         ================= ====================================================
2025-08-14T21:17:32.0284648Z         nonlinearity      gain
2025-08-14T21:17:32.0284771Z         ================= ====================================================
2025-08-14T21:17:32.0284911Z         Linear / Identity :math:`1`
2025-08-14T21:17:32.0285007Z         Conv{1,2,3}D      :math:`1`
2025-08-14T21:17:32.0285115Z         Sigmoid           :math:`1`
2025-08-14T21:17:32.0285222Z         Tanh              :math:`\frac{5}{3}`
2025-08-14T21:17:32.0285323Z         ReLU              :math:`\sqrt{2}`
2025-08-14T21:17:32.0285525Z         Leaky Relu        :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}`
2025-08-14T21:17:32.0285632Z         SELU              :math:`\frac{3}{4}`
2025-08-14T21:17:32.0285759Z         ================= ====================================================
2025-08-14T21:17:32.0285842Z     
2025-08-14T21:17:32.0285936Z         .. warning::
2025-08-14T21:17:32.0286135Z             In order to implement `Self-Normalizing Neural Networks`_ ,
2025-08-14T21:17:32.0286377Z             you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``.
2025-08-14T21:17:32.0286546Z             This gives the initial weights a variance of ``1 / N``,
2025-08-14T21:17:32.0286785Z             which is necessary to induce a stable fixed point in the forward pass.
2025-08-14T21:17:32.0287010Z             In contrast, the default gain for ``SELU`` sacrifices the normalization
2025-08-14T21:17:32.0287207Z             effect for more stable gradient flow in rectangular layers.
2025-08-14T21:17:32.0287289Z     
2025-08-14T21:17:32.0287371Z         Args:
2025-08-14T21:17:32.0287639Z             nonlinearity: the non-linear function (`nn.functional` name)
2025-08-14T21:17:32.0287833Z             param: optional parameter for the non-linear function
2025-08-14T21:17:32.0287912Z     
2025-08-14T21:17:32.0288010Z         Examples:
2025-08-14T21:17:32.0288126Z             >>> gain = nn.init.calculate_gain(
2025-08-14T21:17:32.0288226Z             ...     "leaky_relu", 0.2
2025-08-14T21:17:32.0288367Z             ... )  # leaky_relu with negative_slope=0.2
2025-08-14T21:17:32.0288447Z     
2025-08-14T21:17:32.0288928Z         .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html
2025-08-14T21:17:32.0289022Z         
2025-08-14T21:17:32.0289273Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0289364Z     
2025-08-14T21:17:32.0289459Z       warnings.warn(msg)
2025-08-14T21:17:32.0289537Z     
2025-08-14T21:17:32.0289740Z --- Parse Warning: 103 / 146 ---
2025-08-14T21:17:32.0290651Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=603.
2025-08-14T21:17:32.0290914Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0291102Z     Applies Batch Normalization over a N-Dimensional input.
2025-08-14T21:17:32.0291183Z     
2025-08-14T21:17:32.0291545Z         The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper
2025-08-14T21:17:32.0291773Z         `Batch Normalization: Accelerating Deep Network Training by Reducing
2025-08-14T21:17:32.0291985Z         Internal Covariate Shift <https://arxiv.org/abs/1502.03167>`__ .
2025-08-14T21:17:32.0292082Z     
2025-08-14T21:17:32.0292170Z         .. math::
2025-08-14T21:17:32.0292250Z     
2025-08-14T21:17:32.0292482Z             y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta
2025-08-14T21:17:32.0292565Z     
2025-08-14T21:17:32.0292792Z         The mean and standard-deviation are calculated per-dimension over all
2025-08-14T21:17:32.0293042Z         mini-batches of the same process groups. :math:`\gamma` and :math:`\beta`
2025-08-14T21:17:32.0293285Z         are learnable parameter vectors of size `C` (where `C` is the input size).
2025-08-14T21:17:32.0293478Z         By default, the elements of :math:`\gamma` are sampled from
2025-08-14T21:17:32.0293717Z         :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0.
2025-08-14T21:17:32.0293979Z         The standard-deviation is calculated via the biased estimator, equivalent to
2025-08-14T21:17:32.0294109Z         `torch.var(input, unbiased=False)`.
2025-08-14T21:17:32.0294191Z     
2025-08-14T21:17:32.0294429Z         Also by default, during training this layer keeps running estimates of its
2025-08-14T21:17:32.0294679Z         computed mean and variance, which are then used for normalization during
2025-08-14T21:17:32.0294926Z         evaluation. The running estimates are kept with a default :attr:`momentum`
2025-08-14T21:17:32.0295026Z         of 0.1.
2025-08-14T21:17:32.0295106Z     
2025-08-14T21:17:32.0295333Z         If :attr:`track_running_stats` is set to ``False``, this layer then does not
2025-08-14T21:17:32.0295569Z         keep running estimates, and batch statistics are instead used during
2025-08-14T21:17:32.0295676Z         evaluation time as well.
2025-08-14T21:17:32.0295758Z     
2025-08-14T21:17:32.0295859Z         .. note::
2025-08-14T21:17:32.0296082Z             This :attr:`momentum` argument is different from one used in optimizer
2025-08-14T21:17:32.0296320Z             classes and the conventional notion of momentum. Mathematically, the
2025-08-14T21:17:32.0296459Z             update rule for running statistics here is
2025-08-14T21:17:32.0296755Z             :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`,
2025-08-14T21:17:32.0296998Z             where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the
2025-08-14T21:17:32.0297141Z             new observed value.
2025-08-14T21:17:32.0297220Z     
2025-08-14T21:17:32.0297537Z         Because the Batch Normalization is done for each channel in the ``C`` dimension, computing
2025-08-14T21:17:32.0297787Z         statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch
2025-08-14T21:17:32.0297982Z         Normalization or Spatio-temporal Batch Normalization.
2025-08-14T21:17:32.0298065Z     
2025-08-14T21:17:32.0298214Z         Currently :class:`SyncBatchNorm` only supports
2025-08-14T21:17:32.0298509Z         :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use
2025-08-14T21:17:32.0298720Z         :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert
2025-08-14T21:17:32.0298929Z         :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping
2025-08-14T21:17:32.0299040Z         Network with DDP.
2025-08-14T21:17:32.0299124Z     
2025-08-14T21:17:32.0299205Z         Args:
2025-08-14T21:17:32.0299384Z             num_features: :math:`C` from an expected input of size
2025-08-14T21:17:32.0299480Z                 :math:`(N, C, +)`
2025-08-14T21:17:32.0299679Z             eps: a value added to the denominator for numerical stability.
2025-08-14T21:17:32.0299775Z                 Default: ``1e-5``
2025-08-14T21:17:32.0299964Z             momentum: the value used for the running_mean and running_var
2025-08-14T21:17:32.0300183Z                 computation. Can be set to ``None`` for cumulative moving average
2025-08-14T21:17:32.0300305Z                 (i.e. simple average). Default: 0.1
2025-08-14T21:17:32.0300507Z             affine: a boolean value that when set to ``True``, this module has
2025-08-14T21:17:32.0300667Z                 learnable affine parameters. Default: ``True``
2025-08-14T21:17:32.0300881Z             track_running_stats: a boolean value that when set to ``True``, this
2025-08-14T21:17:32.0301126Z                 module tracks the running mean and variance, and when set to ``False``,
2025-08-14T21:17:32.0301346Z                 this module does not track such statistics, and initializes statistics
2025-08-14T21:17:32.0301547Z                 buffers :attr:`running_mean` and :attr:`running_var` as ``None``.
2025-08-14T21:17:32.0301784Z                 When these buffers are ``None``, this module always uses batch statistics.
2025-08-14T21:17:32.0301935Z                 in both training and eval modes. Default: ``True``
2025-08-14T21:17:32.0302215Z             process_group: synchronization of stats happen within each process group
2025-08-14T21:17:32.0302452Z                 individually. Default behavior is synchronization across the whole
2025-08-14T21:17:32.0302538Z                 world
2025-08-14T21:17:32.0302631Z     
2025-08-14T21:17:32.0302717Z         Shape:
2025-08-14T21:17:32.0302828Z             - Input: :math:`(N, C, +)`
2025-08-14T21:17:32.0302989Z             - Output: :math:`(N, C, +)` (same shape as input)
2025-08-14T21:17:32.0303071Z     
2025-08-14T21:17:32.0303157Z         .. note::
2025-08-14T21:17:32.0303414Z             Synchronization of batchnorm statistics occurs only while training, i.e.
2025-08-14T21:17:32.0303618Z             synchronization is disabled when ``model.eval()`` is set or if
2025-08-14T21:17:32.0303749Z             ``self.training`` is otherwise ``False``.
2025-08-14T21:17:32.0303841Z     
2025-08-14T21:17:32.0303930Z         Examples::
2025-08-14T21:17:32.0304022Z     
2025-08-14T21:17:32.0304121Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0304231Z             >>> # With Learnable Parameters
2025-08-14T21:17:32.0304350Z             >>> m = nn.SyncBatchNorm(100)
2025-08-14T21:17:32.0304472Z             >>> # creating process group (optional)
2025-08-14T21:17:32.0304609Z             >>> # ranks is a list of int identifying rank ids.
2025-08-14T21:17:32.0304751Z             >>> ranks = list(range(8))
2025-08-14T21:17:32.0304882Z             >>> r1, r2 = ranks[:4], ranks[4:]
2025-08-14T21:17:32.0305053Z             >>> # Note: every rank calls into new_group for every
2025-08-14T21:17:32.0305212Z             >>> # process group created, even if that rank is not
2025-08-14T21:17:32.0305311Z             >>> # part of the group.
2025-08-14T21:17:32.0305571Z             >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-08-14T21:17:32.0305772Z             >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-08-14T21:17:32.0305891Z             >>> # Without Learnable Parameters
2025-08-14T21:17:32.0306107Z             >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group)
2025-08-14T21:17:32.0306229Z             >>> input = torch.randn(20, 100, 35, 45, 10)
2025-08-14T21:17:32.0306328Z             >>> output = m(input)
2025-08-14T21:17:32.0306424Z     
2025-08-14T21:17:32.0306543Z             >>> # network is nn.BatchNorm layer
2025-08-14T21:17:32.0306821Z             >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group)
2025-08-14T21:17:32.0307005Z             >>> # only single gpu per process is currently supported
2025-08-14T21:17:32.0307219Z             >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel(
2025-08-14T21:17:32.0307345Z             >>>                         sync_bn_network,
2025-08-14T21:17:32.0307473Z             >>>                         device_ids=[args.local_rank],
2025-08-14T21:17:32.0307602Z             >>>                         output_device=args.local_rank)
2025-08-14T21:17:32.0307700Z         
2025-08-14T21:17:32.0307955Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0308034Z     
2025-08-14T21:17:32.0308142Z       warnings.warn(msg)
2025-08-14T21:17:32.0308221Z     
2025-08-14T21:17:32.0308428Z --- Parse Warning: 104 / 146 ---
2025-08-14T21:17:32.0309665Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=830.
2025-08-14T21:17:32.0309935Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0310261Z     Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers.
2025-08-14T21:17:32.0310342Z     
2025-08-14T21:17:32.0310427Z             Args:
2025-08-14T21:17:32.0310785Z                 module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers
2025-08-14T21:17:32.0311005Z                 process_group (optional): process group to scope synchronization,
2025-08-14T21:17:32.0311135Z                     default is the whole world
2025-08-14T21:17:32.0311217Z     
2025-08-14T21:17:32.0311302Z             Returns:
2025-08-14T21:17:32.0311640Z                 The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm`
2025-08-14T21:17:32.0311858Z                 layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer,
2025-08-14T21:17:32.0312068Z                 a new :class:`torch.nn.SyncBatchNorm` layer object will be returned
2025-08-14T21:17:32.0312170Z                 instead.
2025-08-14T21:17:32.0312248Z     
2025-08-14T21:17:32.0312339Z             Example::
2025-08-14T21:17:32.0312434Z     
2025-08-14T21:17:32.0312558Z                 >>> # Network with nn.BatchNorm layer
2025-08-14T21:17:32.0312714Z                 >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:32.0312837Z                 >>> module = torch.nn.Sequential(
2025-08-14T21:17:32.0312958Z                 >>>            torch.nn.Linear(20, 100),
2025-08-14T21:17:32.0313096Z                 >>>            torch.nn.BatchNorm1d(100),
2025-08-14T21:17:32.0313191Z                 >>>          ).cuda()
2025-08-14T21:17:32.0313382Z                 >>> # creating process group (optional)
2025-08-14T21:17:32.0313576Z                 >>> # ranks is a list of int identifying rank ids.
2025-08-14T21:17:32.0313727Z                 >>> ranks = list(range(8))
2025-08-14T21:17:32.0313835Z                 >>> r1, r2 = ranks[:4], ranks[4:]
2025-08-14T21:17:32.0313998Z                 >>> # Note: every rank calls into new_group for every
2025-08-14T21:17:32.0314152Z                 >>> # process group created, even if that rank is not
2025-08-14T21:17:32.0314269Z                 >>> # part of the group.
2025-08-14T21:17:32.0314395Z                 >>> # xdoctest: +SKIP("distributed")
2025-08-14T21:17:32.0314648Z                 >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-08-14T21:17:32.0314862Z                 >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-08-14T21:17:32.0315158Z                 >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group)
2025-08-14T21:17:32.0315238Z     
2025-08-14T21:17:32.0315336Z             
2025-08-14T21:17:32.0315590Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0315682Z     
2025-08-14T21:17:32.0315777Z       warnings.warn(msg)
2025-08-14T21:17:32.0315856Z     
2025-08-14T21:17:32.0316075Z --- Parse Warning: 105 / 146 ---
2025-08-14T21:17:32.0316954Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=66.
2025-08-14T21:17:32.0317218Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0317309Z     
2025-08-14T21:17:32.0317620Z     Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`.
2025-08-14T21:17:32.0317712Z     
2025-08-14T21:17:32.0317983Z     * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can
2025-08-14T21:17:32.0318208Z       be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively.
2025-08-14T21:17:32.0318304Z     
2025-08-14T21:17:32.0318617Z     * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be
2025-08-14T21:17:32.0318867Z       a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input;  a `NamedShape`
2025-08-14T21:17:32.0319047Z       (tuple of `(name, size)` tuples) for `NamedTensor` input.
2025-08-14T21:17:32.0319126Z     
2025-08-14T21:17:32.0319209Z     Shape:
2025-08-14T21:17:32.0319468Z         - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at
2025-08-14T21:17:32.0319716Z           dimension :attr:`dim` and :math:`*` means any number of dimensions including none.
2025-08-14T21:17:32.0319945Z         - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and
2025-08-14T21:17:32.0320075Z           :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`.
2025-08-14T21:17:32.0320156Z     
2025-08-14T21:17:32.0320251Z     Args:
2025-08-14T21:17:32.0320403Z         dim (Union[int, str]): Dimension to be unflattened
2025-08-14T21:17:32.0320748Z         unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension
2025-08-14T21:17:32.0320843Z     
2025-08-14T21:17:32.0320932Z     Examples:
2025-08-14T21:17:32.0321053Z         >>> input = torch.randn(2, 50)
2025-08-14T21:17:32.0321153Z         >>> # With tuple of ints
2025-08-14T21:17:32.0321251Z         >>> m = nn.Sequential(
2025-08-14T21:17:32.0321360Z         >>>     nn.Linear(50, 50),
2025-08-14T21:17:32.0321467Z         >>>     nn.Unflatten(1, (2, 5, 5))
2025-08-14T21:17:32.0321547Z         >>> )
2025-08-14T21:17:32.0321653Z         >>> output = m(input)
2025-08-14T21:17:32.0321746Z         >>> output.size()
2025-08-14T21:17:32.0321841Z         torch.Size([2, 2, 5, 5])
2025-08-14T21:17:32.0321947Z         >>> # With torch.Size
2025-08-14T21:17:32.0322072Z         >>> m = nn.Sequential(
2025-08-14T21:17:32.0322212Z         >>>     nn.Linear(50, 50),
2025-08-14T21:17:32.0322373Z         >>>     nn.Unflatten(1, torch.Size([2, 5, 5]))
2025-08-14T21:17:32.0322455Z         >>> )
2025-08-14T21:17:32.0322561Z         >>> output = m(input)
2025-08-14T21:17:32.0322655Z         >>> output.size()
2025-08-14T21:17:32.0322763Z         torch.Size([2, 2, 5, 5])
2025-08-14T21:17:32.0322900Z         >>> # With namedshape (tuple of tuples)
2025-08-14T21:17:32.0323052Z         >>> input = torch.randn(2, 50, names=("N", "features"))
2025-08-14T21:17:32.0323259Z         >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5)))
2025-08-14T21:17:32.0323382Z         >>> output = unflatten(input)
2025-08-14T21:17:32.0323477Z         >>> output.size()
2025-08-14T21:17:32.0323578Z         torch.Size([2, 2, 5, 5])
2025-08-14T21:17:32.0323670Z     
2025-08-14T21:17:32.0323924Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0324023Z     
2025-08-14T21:17:32.0324123Z       warnings.warn(msg)
2025-08-14T21:17:32.0324208Z     
2025-08-14T21:17:32.0324415Z --- Parse Warning: 106 / 146 ---
2025-08-14T21:17:32.0325404Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1798.
2025-08-14T21:17:32.0325668Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0325884Z     Creates a criterion that measures the triplet loss given input
2025-08-14T21:17:32.0326077Z         tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor,
2025-08-14T21:17:32.0326304Z         positive, and negative examples, respectively), and a nonnegative,
2025-08-14T21:17:32.0326554Z         real-valued function ("distance function") used to compute the relationship
2025-08-14T21:17:32.0326777Z         between the anchor and positive example ("positive distance") and the
2025-08-14T21:17:32.0326949Z         anchor and negative example ("negative distance").
2025-08-14T21:17:32.0327036Z     
2025-08-14T21:17:32.0327241Z         The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``)
2025-08-14T21:17:32.0327357Z         can be described as:
2025-08-14T21:17:32.0327437Z     
2025-08-14T21:17:32.0327528Z         .. math::
2025-08-14T21:17:32.0327680Z             \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad
2025-08-14T21:17:32.0327833Z             l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\}
2025-08-14T21:17:32.0327961Z     
2025-08-14T21:17:32.0328209Z         where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function
2025-08-14T21:17:32.0328500Z         quantifying the closeness of two tensors, referred to as the :attr:`distance_function`;
2025-08-14T21:17:32.0328758Z         and :math:`margin` is a nonnegative margin representing the minimum difference
2025-08-14T21:17:32.0329008Z         between the positive and negative distances that is required for the loss to
2025-08-14T21:17:32.0329239Z         be 0.  The input tensors have :math:`N` elements each and can be of any shape
2025-08-14T21:17:32.0329377Z         that the distance function can handle.
2025-08-14T21:17:32.0329459Z     
2025-08-14T21:17:32.0329586Z         If :attr:`reduction` is not ``'none'``
2025-08-14T21:17:32.0329690Z         (default ``'mean'``), then:
2025-08-14T21:17:32.0329771Z     
2025-08-14T21:17:32.0329869Z         .. math::
2025-08-14T21:17:32.0329957Z             \ell(x, y) =
2025-08-14T21:17:32.0330051Z             \begin{cases}
2025-08-14T21:17:32.0330264Z                 \operatorname{mean}(L), &  \text{if reduction} = \text{`mean';}\\
2025-08-14T21:17:32.0330455Z                 \operatorname{sum}(L),  &  \text{if reduction} = \text{`sum'.}
2025-08-14T21:17:32.0330542Z             \end{cases}
2025-08-14T21:17:32.0330630Z     
2025-08-14T21:17:32.0330891Z         See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet
2025-08-14T21:17:32.0331175Z         loss for input tensors using the :math:`l_p` distance as the distance function.
2025-08-14T21:17:32.0331281Z     
2025-08-14T21:17:32.0331362Z         Args:
2025-08-14T21:17:32.0331643Z             distance_function (Callable, optional): A nonnegative, real-valued function that
2025-08-14T21:17:32.0331831Z                 quantifies the closeness of two tensors. If not specified,
2025-08-14T21:17:32.0331996Z                 `nn.PairwiseDistance` will be used.  Default: ``None``
2025-08-14T21:17:32.0332278Z             margin (float, optional): A nonnegative margin representing the minimum difference
2025-08-14T21:17:32.0332546Z                 between the positive and negative distances required for the loss to be 0. Larger
2025-08-14T21:17:32.0332844Z                 margins penalize cases where the negative examples are not distant enough from the
2025-08-14T21:17:32.0333021Z                 anchors, relative to the positives. Default: :math:`1`.
2025-08-14T21:17:32.0333266Z             swap (bool, optional): Whether to use the distance swap described in the paper
2025-08-14T21:17:32.0333539Z                 `Learning shallow convolutional feature descriptors with triplet losses` by
2025-08-14T21:17:32.0333771Z                 V. Balntas, E. Riba et al. If True, and if the positive example is closer to the
2025-08-14T21:17:32.0334036Z                 negative example than the anchor is, swaps the positive example and the anchor in
2025-08-14T21:17:32.0334183Z                 the loss computation. Default: ``False``.
2025-08-14T21:17:32.0334460Z             reduction (str, optional): Specifies the (optional) reduction to apply to the output:
2025-08-14T21:17:32.0334652Z                 ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-08-14T21:17:32.0334832Z                 ``'mean'``: the sum of the output will be divided by the number of
2025-08-14T21:17:32.0335071Z                 elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'``
2025-08-14T21:17:32.0335173Z     
2025-08-14T21:17:32.0335255Z     
2025-08-14T21:17:32.0335343Z         Shape:
2025-08-14T21:17:32.0335594Z             - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions
2025-08-14T21:17:32.0335725Z               as supported by the distance function.
2025-08-14T21:17:32.0335990Z             - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar
2025-08-14T21:17:32.0336081Z               otherwise.
2025-08-14T21:17:32.0336160Z     
2025-08-14T21:17:32.0336324Z         Examples:
2025-08-14T21:17:32.0336407Z     
2025-08-14T21:17:32.0336510Z         >>> # Initialize embeddings
2025-08-14T21:17:32.0336641Z         >>> embedding = nn.Embedding(1000, 128)
2025-08-14T21:17:32.0336770Z         >>> anchor_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:32.0336899Z         >>> positive_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:32.0337038Z         >>> negative_ids = torch.randint(0, 1000, (1,))
2025-08-14T21:17:32.0337153Z         >>> anchor = embedding(anchor_ids)
2025-08-14T21:17:32.0337286Z         >>> positive = embedding(positive_ids)
2025-08-14T21:17:32.0337402Z         >>> negative = embedding(negative_ids)
2025-08-14T21:17:32.0337484Z         >>>
2025-08-14T21:17:32.0337603Z         >>> # Built-in Distance Function
2025-08-14T21:17:32.0337699Z         >>> triplet_loss = \
2025-08-14T21:17:32.0337976Z         >>>     nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance())
2025-08-14T21:17:32.0338141Z         >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:32.0338240Z         >>> output.backward()
2025-08-14T21:17:32.0338321Z         >>>
2025-08-14T21:17:32.0338439Z         >>> # Custom Distance Function
2025-08-14T21:17:32.0338540Z         >>> def l_infinity(x1, x2):
2025-08-14T21:17:32.0338708Z         >>>     return torch.max(torch.abs(x1 - x2), dim=1).values
2025-08-14T21:17:32.0338836Z         >>>
2025-08-14T21:17:32.0339049Z         >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time")
2025-08-14T21:17:32.0339186Z         >>> triplet_loss = (
2025-08-14T21:17:32.0339467Z         >>>     nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5))
2025-08-14T21:17:32.0339620Z         >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:32.0339735Z         >>> output.backward()
2025-08-14T21:17:32.0339814Z         >>>
2025-08-14T21:17:32.0339935Z         >>> # Custom Distance Function (Lambda)
2025-08-14T21:17:32.0340046Z         >>> triplet_loss = (
2025-08-14T21:17:32.0340178Z         >>>     nn.TripletMarginWithDistanceLoss(
2025-08-14T21:17:32.0340410Z         >>>         distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y)))
2025-08-14T21:17:32.0340562Z         >>> output = triplet_loss(anchor, positive, negative)
2025-08-14T21:17:32.0340660Z         >>> output.backward()
2025-08-14T21:17:32.0340751Z     
2025-08-14T21:17:32.0340838Z         Reference:
2025-08-14T21:17:32.0341141Z             V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses:
2025-08-14T21:17:32.0341378Z             https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html
2025-08-14T21:17:32.0341458Z         
2025-08-14T21:17:32.0341713Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17))
2025-08-14T21:17:32.0341805Z     
2025-08-14T21:17:32.0341902Z       warnings.warn(msg)
2025-08-14T21:17:32.0341981Z     
2025-08-14T21:17:32.0342195Z --- Parse Warning: 107 / 146 ---
2025-08-14T21:17:32.0343053Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1933.
2025-08-14T21:17:32.0343329Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0343477Z     The Connectionist Temporal Classification loss.
2025-08-14T21:17:32.0343558Z     
2025-08-14T21:17:32.0343956Z         Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the
2025-08-14T21:17:32.0344312Z         probability of possible alignments of input to target, producing a loss value which is differentiable
2025-08-14T21:17:32.0344665Z         with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which
2025-08-14T21:17:32.0344963Z         limits the length of the target sequence such that it must be :math:`\leq` the input length.
2025-08-14T21:17:32.0345091Z     
2025-08-14T21:17:32.0345189Z         Args:
2025-08-14T21:17:32.0345353Z             blank (int, optional): blank label. Default :math:`0`.
2025-08-14T21:17:32.0345591Z             reduction (str, optional): Specifies the reduction to apply to the output:
2025-08-14T21:17:32.0345789Z                 ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-08-14T21:17:32.0345994Z                 ``'mean'``: the output losses will be divided by the target lengths and
2025-08-14T21:17:32.0346255Z                 then the mean over the batch is taken, ``'sum'``: the output losses will be summed.
2025-08-14T21:17:32.0346353Z                 Default: ``'mean'``
2025-08-14T21:17:32.0346467Z             zero_infinity (bool, optional):
2025-08-14T21:17:32.0346676Z                 Whether to zero infinite losses and the associated gradients.
2025-08-14T21:17:32.0346774Z                 Default: ``False``
2025-08-14T21:17:32.0346962Z                 Infinite losses mainly occur when the inputs are too short
2025-08-14T21:17:32.0347089Z                 to be aligned to the targets.
2025-08-14T21:17:32.0347169Z     
2025-08-14T21:17:32.0347256Z         Shape:
2025-08-14T21:17:32.0347457Z             - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`,
2025-08-14T21:17:32.0347580Z               where :math:`T = \text{input length}`,
2025-08-14T21:17:32.0347764Z               :math:`N = \text{batch size}`, and
2025-08-14T21:17:32.0347945Z               :math:`C = \text{number of classes (including blank)}`.
2025-08-14T21:17:32.0348169Z               The logarithmized probabilities of the outputs (e.g. obtained with
2025-08-14T21:17:32.0348314Z               :func:`torch.nn.functional.log_softmax`).
2025-08-14T21:17:32.0348442Z             - Targets: Tensor of size :math:`(N, S)` or
2025-08-14T21:17:32.0348599Z               :math:`(\operatorname{sum}(\text{target\_lengths}))`,
2025-08-14T21:17:32.0348734Z               where :math:`N = \text{batch size}` and
2025-08-14T21:17:32.0348901Z               :math:`S = \text{max target length, if shape is } (N, S)`.
2025-08-14T21:17:32.0349108Z               It represents the target sequences. Each element in the target
2025-08-14T21:17:32.0349347Z               sequence is a class index. And the target index cannot be blank (default=0).
2025-08-14T21:17:32.0349503Z               In the :math:`(N, S)` form, targets are padded to the
2025-08-14T21:17:32.0349656Z               length of the longest sequence, and stacked.
2025-08-14T21:17:32.0349849Z               In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form,
2025-08-14T21:17:32.0349986Z               the targets are assumed to be un-padded and
2025-08-14T21:17:32.0350116Z               concatenated within 1 dimension.
2025-08-14T21:17:32.0350320Z             - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-08-14T21:17:32.0350531Z               where :math:`N = \text{batch size}`. It represents the lengths of the
2025-08-14T21:17:32.0350733Z               inputs (must each be :math:`\leq T`). And the lengths are specified
2025-08-14T21:17:32.0350964Z               for each sequence to achieve masking under the assumption that sequences
2025-08-14T21:17:32.0351088Z               are padded to equal lengths.
2025-08-14T21:17:32.0351296Z             - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-08-14T21:17:32.0351620Z               where :math:`N = \text{batch size}`. It represents lengths of the targets.
2025-08-14T21:17:32.0351856Z               Lengths are specified for each sequence to achieve masking under the
2025-08-14T21:17:32.0352101Z               assumption that sequences are padded to equal lengths. If target shape is
2025-08-14T21:17:32.0352285Z               :math:`(N,S)`, target_lengths are effectively the stop index
2025-08-14T21:17:32.0352540Z               :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for
2025-08-14T21:17:32.0352758Z               each target in a batch. Lengths must each be :math:`\leq S`
2025-08-14T21:17:32.0353014Z               If the targets are given as a 1d tensor that is the concatenation of individual
2025-08-14T21:17:32.0353249Z               targets, the target_lengths must add up to the total length of the tensor.
2025-08-14T21:17:32.0353455Z             - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or
2025-08-14T21:17:32.0353691Z               ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or
2025-08-14T21:17:32.0353889Z               :math:`()` if input is unbatched, where :math:`N = \text{batch size}`.
2025-08-14T21:17:32.0353982Z     
2025-08-14T21:17:32.0354067Z         Examples:
2025-08-14T21:17:32.0354145Z     
2025-08-14T21:17:32.0354265Z             >>> # Target are to be padded
2025-08-14T21:17:32.0354378Z             >>> T = 50  # Input sequence length
2025-08-14T21:17:32.0354514Z             >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:32.0354623Z             >>> N = 16  # Batch size
2025-08-14T21:17:32.0354851Z             >>> S = 30  # Target sequence length of longest target in batch (padding length)
2025-08-14T21:17:32.0355049Z             >>> S_min = 10  # Minimum target length, for demonstration purposes
2025-08-14T21:17:32.0355132Z             >>>
2025-08-14T21:17:32.0355356Z             >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-08-14T21:17:32.0355602Z             >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-08-14T21:17:32.0355712Z             >>>
2025-08-14T21:17:32.0355906Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:32.0356131Z             >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long)
2025-08-14T21:17:32.0356215Z             >>>
2025-08-14T21:17:32.0356447Z             >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-08-14T21:17:32.0356567Z             >>> target_lengths = torch.randint(
2025-08-14T21:17:32.0356661Z             ...     low=S_min,
2025-08-14T21:17:32.0356763Z             ...     high=S,
2025-08-14T21:17:32.0356856Z             ...     size=(N,),
2025-08-14T21:17:32.0356960Z             ...     dtype=torch.long,
2025-08-14T21:17:32.0357060Z             ... )
2025-08-14T21:17:32.0357164Z             >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:32.0357350Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:32.0357465Z             >>> loss.backward()
2025-08-14T21:17:32.0357548Z             >>>
2025-08-14T21:17:32.0357642Z             >>>
2025-08-14T21:17:32.0357755Z             >>> # Target are to be un-padded
2025-08-14T21:17:32.0357868Z             >>> T = 50  # Input sequence length
2025-08-14T21:17:32.0358017Z             >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:32.0358113Z             >>> N = 16  # Batch size
2025-08-14T21:17:32.0367913Z             >>>
2025-08-14T21:17:32.0368254Z             >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-08-14T21:17:32.0368473Z             >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-08-14T21:17:32.0368712Z             >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-08-14T21:17:32.0368798Z             >>>
2025-08-14T21:17:32.0369000Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:32.0369263Z             >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long)
2025-08-14T21:17:32.0369374Z             >>> target = torch.randint(
2025-08-14T21:17:32.0369481Z             ...     low=1,
2025-08-14T21:17:32.0369570Z             ...     high=C,
2025-08-14T21:17:32.0369687Z             ...     size=(sum(target_lengths),),
2025-08-14T21:17:32.0369804Z             ...     dtype=torch.long,
2025-08-14T21:17:32.0369887Z             ... )
2025-08-14T21:17:32.0369991Z             >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:32.0370319Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:32.0370420Z             >>> loss.backward()
2025-08-14T21:17:32.0370505Z             >>>
2025-08-14T21:17:32.0370605Z             >>>
2025-08-14T21:17:32.0370793Z             >>> # Target are to be un-padded and unbatched (effectively N=1)
2025-08-14T21:17:32.0370928Z             >>> T = 50  # Input sequence length
2025-08-14T21:17:32.0371069Z             >>> C = 20  # Number of classes (including blank)
2025-08-14T21:17:32.0371153Z             >>>
2025-08-14T21:17:32.0371362Z             >>> # Initialize random batch of input vectors, for *size = (T,C)
2025-08-14T21:17:32.0371499Z             >>> # xdoctest: +SKIP("FIXME: error in doctest")
2025-08-14T21:17:32.0371699Z             >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_()
2025-08-14T21:17:32.0371870Z             >>> input_lengths = torch.tensor(T, dtype=torch.long)
2025-08-14T21:17:32.0371956Z             >>>
2025-08-14T21:17:32.0372165Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-08-14T21:17:32.0372399Z             >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long)
2025-08-14T21:17:32.0372506Z             >>> target = torch.randint(
2025-08-14T21:17:32.0372611Z             ...     low=1,
2025-08-14T21:17:32.0372741Z             ...     high=C,
2025-08-14T21:17:32.0372877Z             ...     size=(target_lengths,),
2025-08-14T21:17:32.0373028Z             ...     dtype=torch.long,
2025-08-14T21:17:32.0373108Z             ... )
2025-08-14T21:17:32.0373211Z             >>> ctc_loss = nn.CTCLoss()
2025-08-14T21:17:32.0373412Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-08-14T21:17:32.0373509Z             >>> loss.backward()
2025-08-14T21:17:32.0373606Z     
2025-08-14T21:17:32.0373695Z         Reference:
2025-08-14T21:17:32.0373871Z             A. Graves et al.: Connectionist Temporal Classification:
2025-08-14T21:17:32.0374118Z             Labelling Unsegmented Sequence Data with Recurrent Neural Networks:
2025-08-14T21:17:32.0374290Z             https://www.cs.toronto.edu/~graves/icml_2006.pdf
2025-08-14T21:17:32.0374369Z     
2025-08-14T21:17:32.0374469Z         Note:
2025-08-14T21:17:32.0374711Z             In order to use CuDNN, the following must be satisfied: :attr:`targets` must be
2025-08-14T21:17:32.0374966Z             in concatenated format, all :attr:`input_lengths` must be `T`.  :math:`blank=0`,
2025-08-14T21:17:32.0375203Z             :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of
2025-08-14T21:17:32.0375308Z             dtype :attr:`torch.int32`.
2025-08-14T21:17:32.0375403Z     
2025-08-14T21:17:32.0375673Z             The regular implementation uses the (more common in PyTorch) `torch.long` dtype.
2025-08-14T21:17:32.0375755Z     
2025-08-14T21:17:32.0375848Z     
2025-08-14T21:17:32.0375931Z         Note:
2025-08-14T21:17:32.0376177Z             In some circumstances when using the CUDA backend with CuDNN, this operator
2025-08-14T21:17:32.0376442Z             may select a nondeterministic algorithm to increase performance. If this is
2025-08-14T21:17:32.0376683Z             undesirable, you can try to make the operation deterministic (potentially at
2025-08-14T21:17:32.0376914Z             a performance cost) by setting ``torch.backends.cudnn.deterministic =
2025-08-14T21:17:32.0377016Z             True``.
2025-08-14T21:17:32.0377213Z             Please see the notes on :doc:`/notes/randomness` for background.
2025-08-14T21:17:32.0377308Z         
2025-08-14T21:17:32.0377560Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0377641Z     
2025-08-14T21:17:32.0377751Z       warnings.warn(msg)
2025-08-14T21:17:32.0377830Z     
2025-08-14T21:17:32.0378095Z --- Parse Warning: 108 / 146 ---
2025-08-14T21:17:32.0379044Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=410.
2025-08-14T21:17:32.0379310Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0379477Z     Computes a partial inverse of :class:`MaxPool2d`.
2025-08-14T21:17:32.0379558Z     
2025-08-14T21:17:32.0379822Z         :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost.
2025-08-14T21:17:32.0379917Z     
2025-08-14T21:17:32.0380144Z         :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d`
2025-08-14T21:17:32.0380387Z         including the indices of the maximal values and computes a partial inverse
2025-08-14T21:17:32.0380546Z         in which all non-maximal values are set to zero.
2025-08-14T21:17:32.0380625Z     
2025-08-14T21:17:32.0380709Z         Note:
2025-08-14T21:17:32.0381040Z             This operation may behave nondeterministically when the input indices has repeat values.
2025-08-14T21:17:32.0381420Z             See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information.
2025-08-14T21:17:32.0381516Z     
2025-08-14T21:17:32.0381759Z         .. note:: :class:`MaxPool2d` can map several input sizes to the same output
2025-08-14T21:17:32.0381934Z                   sizes. Hence, the inversion process can get ambiguous.
2025-08-14T21:17:32.0382189Z                   To accommodate this, you can provide the needed output size
2025-08-14T21:17:32.0382438Z                   as an additional argument :attr:`output_size` in the forward call.
2025-08-14T21:17:32.0382561Z                   See the Inputs and Example below.
2025-08-14T21:17:32.0382656Z     
2025-08-14T21:17:32.0382741Z         Args:
2025-08-14T21:17:32.0382938Z             kernel_size (int or tuple): Size of the max pooling window.
2025-08-14T21:17:32.0383111Z             stride (int or tuple): Stride of the max pooling window.
2025-08-14T21:17:32.0383248Z                 It is set to :attr:`kernel_size` by default.
2025-08-14T21:17:32.0383443Z             padding (int or tuple): Padding that was added to the input
2025-08-14T21:17:32.0383523Z     
2025-08-14T21:17:32.0383606Z         Inputs:
2025-08-14T21:17:32.0383745Z             - `input`: the input Tensor to invert
2025-08-14T21:17:32.0383949Z             - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d`
2025-08-14T21:17:32.0384107Z             - `output_size` (optional): the targeted output size
2025-08-14T21:17:32.0384205Z     
2025-08-14T21:17:32.0384291Z         Shape:
2025-08-14T21:17:32.0384489Z             - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`.
2025-08-14T21:17:32.0384701Z             - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where
2025-08-14T21:17:32.0384783Z     
2025-08-14T21:17:32.0384887Z               .. math::
2025-08-14T21:17:32.0385161Z                 H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]}
2025-08-14T21:17:32.0385240Z     
2025-08-14T21:17:32.0385342Z               .. math::
2025-08-14T21:17:32.0385594Z                 W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]}
2025-08-14T21:17:32.0385688Z     
2025-08-14T21:17:32.0385851Z               or as given by :attr:`output_size` in the call operator
2025-08-14T21:17:32.0385938Z     
2025-08-14T21:17:32.0386038Z         Example::
2025-08-14T21:17:32.0386118Z     
2025-08-14T21:17:32.0386281Z             >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True)
2025-08-14T21:17:32.0386420Z             >>> unpool = nn.MaxUnpool2d(2, stride=2)
2025-08-14T21:17:32.0386551Z             >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.],
2025-08-14T21:17:32.0386662Z                                         [ 5.,  6.,  7.,  8.],
2025-08-14T21:17:32.0386780Z                                         [ 9., 10., 11., 12.],
2025-08-14T21:17:32.0386917Z                                         [13., 14., 15., 16.]]]])
2025-08-14T21:17:32.0387048Z             >>> output, indices = pool(input)
2025-08-14T21:17:32.0387155Z             >>> unpool(output, indices)
2025-08-14T21:17:32.0387259Z             tensor([[[[  0.,   0.,   0.,   0.],
2025-08-14T21:17:32.0387372Z                       [  0.,   6.,   0.,   8.],
2025-08-14T21:17:32.0387470Z                       [  0.,   0.,   0.,   0.],
2025-08-14T21:17:32.0387571Z                       [  0.,  14.,   0.,  16.]]]])
2025-08-14T21:17:32.0387797Z             >>> # Now using output_size to resolve an ambiguous size for the inverse
2025-08-14T21:17:32.0387937Z             >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.,  5.],
2025-08-14T21:17:32.0388049Z                                         [ 6.,  7.,  8.,  9., 10.],
2025-08-14T21:17:32.0388170Z                                         [11., 12., 13., 14., 15.],
2025-08-14T21:17:32.0388282Z                                         [16., 17., 18., 19., 20.]]]])
2025-08-14T21:17:32.0388416Z             >>> output, indices = pool(input)
2025-08-14T21:17:32.0388588Z             >>> # This call will not work without specifying output_size
2025-08-14T21:17:32.0388743Z             >>> unpool(output, indices, output_size=input.size())
2025-08-14T21:17:32.0388865Z             tensor([[[[ 0.,  0.,  0.,  0.,  0.],
2025-08-14T21:17:32.0388962Z                       [ 0.,  7.,  0.,  9.,  0.],
2025-08-14T21:17:32.0389114Z                       [ 0.,  0.,  0.,  0.,  0.],
2025-08-14T21:17:32.0389255Z                       [ 0., 17.,  0., 19.,  0.]]]])
2025-08-14T21:17:32.0389336Z     
2025-08-14T21:17:32.0389429Z     
2025-08-14T21:17:32.0389510Z         
2025-08-14T21:17:32.0389765Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0389859Z     
2025-08-14T21:17:32.0389952Z       warnings.warn(msg)
2025-08-14T21:17:32.0390031Z     
2025-08-14T21:17:32.0390245Z --- Parse Warning: 109 / 146 ---
2025-08-14T21:17:32.0391148Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272.
2025-08-14T21:17:32.0391519Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0391855Z     Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings.
2025-08-14T21:17:32.0391937Z     
2025-08-14T21:17:32.0392273Z         For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`,
2025-08-14T21:17:32.0392381Z         and with 2D inputs, this class
2025-08-14T21:17:32.0392463Z     
2025-08-14T21:17:32.0392782Z             * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``,
2025-08-14T21:17:32.0393092Z             * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``,
2025-08-14T21:17:32.0393390Z             * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``.
2025-08-14T21:17:32.0393485Z     
2025-08-14T21:17:32.0393838Z         However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these
2025-08-14T21:17:32.0393940Z         operations.
2025-08-14T21:17:32.0394020Z     
2025-08-14T21:17:32.0394283Z         EmbeddingBag also supports per-sample weights as an argument to the forward
2025-08-14T21:17:32.0394534Z         pass. This scales the output of the Embedding before performing a weighted
2025-08-14T21:17:32.0394783Z         reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the
2025-08-14T21:17:32.0395018Z         only supported ``mode`` is ``"sum"``, which computes a weighted sum according to
2025-08-14T21:17:32.0395139Z         :attr:`per_sample_weights`.
2025-08-14T21:17:32.0395226Z     
2025-08-14T21:17:32.0395325Z         Args:
2025-08-14T21:17:32.0395551Z             num_embeddings (int): size of the dictionary of embeddings
2025-08-14T21:17:32.0395721Z             embedding_dim (int): the size of each embedding vector
2025-08-14T21:17:32.0396054Z             max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm`
2025-08-14T21:17:32.0396208Z                                         is renormalized to have norm :attr:`max_norm`.
2025-08-14T21:17:32.0396549Z             norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``.
2025-08-14T21:17:32.0396891Z             scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of
2025-08-14T21:17:32.0397053Z                                                     the words in the mini-batch. Default ``False``.
2025-08-14T21:17:32.0397250Z                                                     Note: this option is not supported when ``mode="max"``.
2025-08-14T21:17:32.0397501Z             mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag.
2025-08-14T21:17:32.0397719Z                                      ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights`
2025-08-14T21:17:32.0397951Z                                      into consideration. ``"mean"`` computes the average of the values
2025-08-14T21:17:32.0398154Z                                      in the bag, ``"max"`` computes the max value over each bag.
2025-08-14T21:17:32.0398331Z                                      Default: ``"mean"``
2025-08-14T21:17:32.0398652Z             sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See
2025-08-14T21:17:32.0398904Z                                      Notes for more details regarding sparse gradients. Note: this option is not
2025-08-14T21:17:32.0399048Z                                      supported when ``mode="max"``.
2025-08-14T21:17:32.0399422Z             include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element
2025-08-14T21:17:32.0399658Z                                           is equivalent to the size of `indices`. This matches the CSR format.
2025-08-14T21:17:32.0399988Z             padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the
2025-08-14T21:17:32.0400262Z                                          gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated
2025-08-14T21:17:32.0400524Z                                          during training, i.e. it remains as a fixed "pad". For a newly constructed
2025-08-14T21:17:32.0400795Z                                          EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all
2025-08-14T21:17:32.0401053Z                                          zeros, but can be updated to another value to be used as the padding vector.
2025-08-14T21:17:32.0401300Z                                          Note that the embedding vector at :attr:`padding_idx` is excluded from the
2025-08-14T21:17:32.0401409Z                                          reduction.
2025-08-14T21:17:32.0401503Z     
2025-08-14T21:17:32.0401590Z         Attributes:
2025-08-14T21:17:32.0401906Z             weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)`
2025-08-14T21:17:32.0402067Z                              initialized from :math:`\mathcal{N}(0, 1)`.
2025-08-14T21:17:32.0402149Z     
2025-08-14T21:17:32.0402249Z         Examples::
2025-08-14T21:17:32.0402345Z     
2025-08-14T21:17:32.0402515Z             >>> # an EmbeddingBag module containing 10 tensors of size 3
2025-08-14T21:17:32.0402690Z             >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum')
2025-08-14T21:17:32.0402818Z             >>> # a batch of 2 samples of 4 indices each
2025-08-14T21:17:32.0403004Z             >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long)
2025-08-14T21:17:32.0403194Z             >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-08-14T21:17:32.0403340Z             >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:32.0403457Z             >>> embedding_sum(input, offsets)
2025-08-14T21:17:32.0403580Z             tensor([[-0.8861, -5.4350, -0.0523],
2025-08-14T21:17:32.0403685Z                     [ 1.1306, -2.5798, -1.0044]])
2025-08-14T21:17:32.0403769Z     
2025-08-14T21:17:32.0403891Z             >>> # Example with padding_idx
2025-08-14T21:17:32.0404100Z             >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2)
2025-08-14T21:17:32.0404295Z             >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long)
2025-08-14T21:17:32.0404443Z             >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-08-14T21:17:32.0404559Z             >>> embedding_sum(input, offsets)
2025-08-14T21:17:32.0404675Z             tensor([[ 0.0000,  0.0000,  0.0000],
2025-08-14T21:17:32.0404779Z                     [-0.7082,  3.2145, -2.6251]])
2025-08-14T21:17:32.0404861Z     
2025-08-14T21:17:32.0405053Z             >>> # An EmbeddingBag can be loaded from an Embedding like so
2025-08-14T21:17:32.0405200Z             >>> embedding = nn.Embedding(10, 3, padding_idx=2)
2025-08-14T21:17:32.0405374Z             >>> embedding_sum = nn.EmbeddingBag.from_pretrained(
2025-08-14T21:17:32.0405507Z                     embedding.weight,
2025-08-14T21:17:32.0405663Z                     padding_idx=embedding.padding_idx,
2025-08-14T21:17:32.0405800Z                     mode='sum')
2025-08-14T21:17:32.0405885Z         
2025-08-14T21:17:32.0406139Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0406234Z     
2025-08-14T21:17:32.0406333Z       warnings.warn(msg)
2025-08-14T21:17:32.0406414Z     
2025-08-14T21:17:32.0406645Z --- Parse Warning: 110 / 146 ---
2025-08-14T21:17:32.0407604Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186.
2025-08-14T21:17:32.0407882Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0408032Z     Take in and process masked source/target sequences.
2025-08-14T21:17:32.0408114Z     
2025-08-14T21:17:32.0408222Z             .. note::
2025-08-14T21:17:32.0408303Z     
2025-08-14T21:17:32.0408695Z                 If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are
2025-08-14T21:17:32.0408852Z                 not allowed to participate in the attention,
2025-08-14T21:17:32.0409274Z                 which is the opposite of the definition for :attr:`attn_mask`
2025-08-14T21:17:32.0409478Z                 in :func:`torch.nn.functional.scaled_dot_product_attention`.
2025-08-14T21:17:32.0409558Z     
2025-08-14T21:17:32.0409646Z             Args:
2025-08-14T21:17:32.0409800Z                 src: the sequence to the encoder (required).
2025-08-14T21:17:32.0409935Z                 tgt: the sequence to the decoder (required).
2025-08-14T21:17:32.0410117Z                 src_mask: the additive mask for the src sequence (optional).
2025-08-14T21:17:32.0410311Z                 tgt_mask: the additive mask for the tgt sequence (optional).
2025-08-14T21:17:32.0410520Z                 memory_mask: the additive mask for the encoder output (optional).
2025-08-14T21:17:32.0410765Z                 src_key_padding_mask: the Tensor mask for src keys per batch (optional).
2025-08-14T21:17:32.0410990Z                 tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional).
2025-08-14T21:17:32.0411241Z                 memory_key_padding_mask: the Tensor mask for memory keys per batch (optional).
2025-08-14T21:17:32.0411460Z                 src_is_causal: If specified, applies a causal mask as ``src_mask``.
2025-08-14T21:17:32.0411733Z                     Default: ``None``; try to detect a causal mask.
2025-08-14T21:17:32.0411832Z                     Warning:
2025-08-14T21:17:32.0412023Z                     ``src_is_causal`` provides a hint that ``src_mask`` is
2025-08-14T21:17:32.0412200Z                     the causal mask. Providing incorrect hints can result in
2025-08-14T21:17:32.0412381Z                     incorrect execution, including forward and backward
2025-08-14T21:17:32.0412487Z                     compatibility.
2025-08-14T21:17:32.0412695Z                 tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``.
2025-08-14T21:17:32.0412852Z                     Default: ``None``; try to detect a causal mask.
2025-08-14T21:17:32.0412944Z                     Warning:
2025-08-14T21:17:32.0413101Z                     ``tgt_is_causal`` provides a hint that ``tgt_mask`` is
2025-08-14T21:17:32.0413290Z                     the causal mask. Providing incorrect hints can result in
2025-08-14T21:17:32.0413455Z                     incorrect execution, including forward and backward
2025-08-14T21:17:32.0413572Z                     compatibility.
2025-08-14T21:17:32.0413748Z                 memory_is_causal: If specified, applies a causal mask as
2025-08-14T21:17:32.0413848Z                     ``memory_mask``.
2025-08-14T21:17:32.0413963Z                     Default: ``False``.
2025-08-14T21:17:32.0414054Z                     Warning:
2025-08-14T21:17:32.0414236Z                     ``memory_is_causal`` provides a hint that
2025-08-14T21:17:32.0414504Z                     ``memory_mask`` is the causal mask. Providing incorrect
2025-08-14T21:17:32.0414662Z                     hints can result in incorrect execution, including
2025-08-14T21:17:32.0414789Z                     forward and backward compatibility.
2025-08-14T21:17:32.0414883Z     
2025-08-14T21:17:32.0414969Z             Shape:
2025-08-14T21:17:32.0415232Z                 - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or
2025-08-14T21:17:32.0415354Z                   `(N, S, E)` if `batch_first=True`.
2025-08-14T21:17:32.0415594Z                 - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-08-14T21:17:32.0415726Z                   `(N, T, E)` if `batch_first=True`.
2025-08-14T21:17:32.0415915Z                 - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`.
2025-08-14T21:17:32.0416102Z                 - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`.
2025-08-14T21:17:32.0416237Z                 - memory_mask: :math:`(T, S)`.
2025-08-14T21:17:32.0416478Z                 - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-08-14T21:17:32.0416729Z                 - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`.
2025-08-14T21:17:32.0416988Z                 - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-08-14T21:17:32.0417069Z     
2025-08-14T21:17:32.0417393Z                 Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked
2025-08-14T21:17:32.0417605Z                 positions. If a BoolTensor is provided, positions with ``True``
2025-08-14T21:17:32.0417869Z                 are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor
2025-08-14T21:17:32.0418055Z                 is provided, it will be added to the attention weight.
2025-08-14T21:17:32.0418362Z                 [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by
2025-08-14T21:17:32.0418592Z                 the attention. If a BoolTensor is provided, the positions with the
2025-08-14T21:17:32.0418902Z                 value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged.
2025-08-14T21:17:32.0418982Z     
2025-08-14T21:17:32.0419253Z                 - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-08-14T21:17:32.0419403Z                   `(N, T, E)` if `batch_first=True`.
2025-08-14T21:17:32.0419484Z     
2025-08-14T21:17:32.0419740Z                 Note: Due to the multi-head attention architecture in the transformer model,
2025-08-14T21:17:32.0419978Z                 the output sequence length of a transformer is same as the input sequence
2025-08-14T21:17:32.0420117Z                 (i.e. target) length of the decoder.
2025-08-14T21:17:32.0420198Z     
2025-08-14T21:17:32.0420522Z                 where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the
2025-08-14T21:17:32.0420678Z                 batch size, :math:`E` is the feature number
2025-08-14T21:17:32.0420757Z     
2025-08-14T21:17:32.0420848Z             Examples:
2025-08-14T21:17:32.0420966Z                 >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0421081Z                 >>> output = transformer_model(
2025-08-14T21:17:32.0421243Z                 ...     src, tgt, src_mask=src_mask, tgt_mask=tgt_mask
2025-08-14T21:17:32.0421332Z                 ... )
2025-08-14T21:17:32.0421416Z             
2025-08-14T21:17:32.0421682Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0421763Z     
2025-08-14T21:17:32.0421857Z       warnings.warn(msg)
2025-08-14T21:17:32.0421952Z     
2025-08-14T21:17:32.0422168Z --- Parse Warning: 111 / 146 ---
2025-08-14T21:17:32.0423257Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766.
2025-08-14T21:17:32.0423565Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0423647Z     
2025-08-14T21:17:32.0423895Z     Context manager for training with uneven inputs across processes in DDP.
2025-08-14T21:17:32.0423978Z     
2025-08-14T21:17:32.0424206Z     This context manager will keep track of already-joined DDP processes,
2025-08-14T21:17:32.0424428Z     and "shadow" the forward and backward passes by inserting collective
2025-08-14T21:17:32.0424661Z     communication operations to match with the ones created by non-joined
2025-08-14T21:17:32.0424897Z     DDP processes. This will ensure each collective call has a corresponding
2025-08-14T21:17:32.0425132Z     call by already-joined DDP processes, preventing hangs or errors that
2025-08-14T21:17:32.0425334Z     would otherwise happen when training with uneven inputs across
2025-08-14T21:17:32.0425586Z     processes. Alternatively, if the flag ``throw_on_early_termination`` is
2025-08-14T21:17:32.0425795Z     specified to be ``True``, all trainers will throw an error once one rank
2025-08-14T21:17:32.0425994Z     runs out of inputs, allowing these errors to be caught and handled
2025-08-14T21:17:32.0426122Z     according to application logic.
2025-08-14T21:17:32.0426203Z     
2025-08-14T21:17:32.0426421Z     Once all DDP processes have joined, the context manager will broadcast
2025-08-14T21:17:32.0426657Z     the model corresponding to the last joined process to all processes to
2025-08-14T21:17:32.0426807Z     ensure the model is the same across all processes
2025-08-14T21:17:32.0426927Z     (which is guaranteed by DDP).
2025-08-14T21:17:32.0427006Z     
2025-08-14T21:17:32.0427207Z     To use this to enable training with uneven inputs across processes,
2025-08-14T21:17:32.0427444Z     simply wrap this context manager around your training loop. No further
2025-08-14T21:17:32.0427619Z     modifications to the model or data loading is required.
2025-08-14T21:17:32.0427699Z     
2025-08-14T21:17:32.0427811Z     .. warning::
2025-08-14T21:17:32.0428017Z         If the model or training loop this context manager is wrapped around
2025-08-14T21:17:32.0428202Z         has additional distributed collective operations, such as
2025-08-14T21:17:32.0428401Z         ``SyncBatchNorm`` in the model's forward pass, then the flag
2025-08-14T21:17:32.0428636Z         ``throw_on_early_termination`` must be enabled. This is because this
2025-08-14T21:17:32.0428861Z         context manager is not aware of non-DDP collective communication.
2025-08-14T21:17:32.0429031Z         This flag will cause all ranks to throw when any one rank
2025-08-14T21:17:32.0429244Z         exhausts inputs, allowing these errors to be caught and recovered
2025-08-14T21:17:32.0429363Z         from across all ranks.
2025-08-14T21:17:32.0429445Z     
2025-08-14T21:17:32.0429529Z     Args:
2025-08-14T21:17:32.0429725Z         divide_by_initial_world_size (bool): If ``True``, will divide
2025-08-14T21:17:32.0429928Z             gradients by the initial ``world_size`` DDP training was launched
2025-08-14T21:17:32.0430095Z             with. If ``False``, will compute the effective world size
2025-08-14T21:17:32.0430293Z             (number of ranks that have not depleted their inputs yet) and
2025-08-14T21:17:32.0430441Z             divide gradients by that during allreduce. Set
2025-08-14T21:17:32.0430637Z             ``divide_by_initial_world_size=True`` to ensure every input
2025-08-14T21:17:32.0430844Z             sample including the uneven inputs have equal weight in terms of
2025-08-14T21:17:32.0431017Z             how much they contribute to the global gradient. This is
2025-08-14T21:17:32.0431212Z             achieved by always dividing the gradient by the initial
2025-08-14T21:17:32.0431524Z             ``world_size`` even when we encounter uneven inputs. If you set
2025-08-14T21:17:32.0431752Z             this to ``False``, we divide the gradient by the remaining
2025-08-14T21:17:32.0431960Z             number of nodes. This ensures parity with training on a smaller
2025-08-14T21:17:32.0432142Z             ``world_size`` although it also means the uneven inputs would
2025-08-14T21:17:32.0432335Z             contribute more towards the global gradient. Typically, you
2025-08-14T21:17:32.0432536Z             would want to set this to ``True`` for cases where the last few
2025-08-14T21:17:32.0432733Z             inputs of your training job are uneven. In extreme cases, where
2025-08-14T21:17:32.0432931Z             there is a large discrepancy in the number of inputs, setting
2025-08-14T21:17:32.0433076Z             this to ``False`` might provide better results.
2025-08-14T21:17:32.0433283Z         enable (bool): Whether to enable uneven input detection or not. Pass
2025-08-14T21:17:32.0433468Z             in ``enable=False`` to disable in cases where you know that
2025-08-14T21:17:32.0433656Z             inputs are even across participating processes. Default is
2025-08-14T21:17:32.0433741Z             ``True``.
2025-08-14T21:17:32.0433934Z         throw_on_early_termination (bool): Whether to throw an error
2025-08-14T21:17:32.0434110Z             or continue training when at least one rank has exhausted
2025-08-14T21:17:32.0434305Z             inputs. If ``True``, will throw upon the first rank reaching end
2025-08-14T21:17:32.0434476Z             of data. If ``False``, will continue training with a smaller
2025-08-14T21:17:32.0434669Z             effective world size until all ranks are joined. Note that if
2025-08-14T21:17:32.0434804Z             this flag is specified, then the flag
2025-08-14T21:17:32.0434977Z             ``divide_by_initial_world_size`` would be ignored. Default
2025-08-14T21:17:32.0435069Z             is ``False``.
2025-08-14T21:17:32.0435162Z     
2025-08-14T21:17:32.0435244Z     
2025-08-14T21:17:32.0435335Z     Example::
2025-08-14T21:17:32.0435429Z     
2025-08-14T21:17:32.0435546Z         >>> # xdoctest: +SKIP("Distributed")
2025-08-14T21:17:32.0435649Z         >>> import torch
2025-08-14T21:17:32.0435766Z         >>> import torch.distributed as dist
2025-08-14T21:17:32.0435853Z         >>> import os
2025-08-14T21:17:32.0435987Z         >>> import torch.multiprocessing as mp
2025-08-14T21:17:32.0436087Z         >>> import torch.nn as nn
2025-08-14T21:17:32.0436188Z         >>> # On each spawned worker
2025-08-14T21:17:32.0436295Z         >>> def worker(rank):
2025-08-14T21:17:32.0436503Z         >>>     dist.init_process_group("nccl", rank=rank, world_size=2)
2025-08-14T21:17:32.0436616Z         >>>     torch.cuda.set_device(rank)
2025-08-14T21:17:32.0436761Z         >>>     model = nn.Linear(1, 1, bias=False).to(rank)
2025-08-14T21:17:32.0436932Z         >>>     model = torch.nn.parallel.DistributedDataParallel(
2025-08-14T21:17:32.0437085Z         >>>         model, device_ids=[rank], output_device=rank
2025-08-14T21:17:32.0437169Z         >>>     )
2025-08-14T21:17:32.0437297Z         >>>     # Rank 1 gets one more input than rank 0.
2025-08-14T21:17:32.0437494Z         >>>     inputs = [torch.tensor([1]).float() for _ in range(10 + rank)]
2025-08-14T21:17:32.0437593Z         >>>     with model.join():
2025-08-14T21:17:32.0437692Z         >>>         for _ in range(5):
2025-08-14T21:17:32.0437807Z         >>>             for inp in inputs:
2025-08-14T21:17:32.0437920Z         >>>                 loss = model(inp).sum()
2025-08-14T21:17:32.0438025Z         >>>                 loss.backward()
2025-08-14T21:17:32.0438225Z         >>>     # Without the join() API, the below synchronization will hang
2025-08-14T21:17:32.0438365Z         >>>     # blocking for rank 1's allreduce to complete.
2025-08-14T21:17:32.0438504Z         >>>     torch.cuda.synchronize(device=rank)
2025-08-14T21:17:32.0438585Z     
2025-08-14T21:17:32.0438866Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0438984Z     
2025-08-14T21:17:32.0439109Z       warnings.warn(msg)
2025-08-14T21:17:32.0439188Z     
2025-08-14T21:17:32.0439415Z --- Parse Warning: 112 / 146 ---
2025-08-14T21:17:32.0440501Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057.
2025-08-14T21:17:32.0440779Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0440858Z     
2025-08-14T21:17:32.0441164Z     Register an optimizer in DDP to optimize parameter immediately after its gradient reduction.
2025-08-14T21:17:32.0441258Z     
2025-08-14T21:17:32.0441465Z     Registers an optimizer with DDP such that the optimization for a
2025-08-14T21:17:32.0441673Z     parameter will run immediately when that parameter's gradient is
2025-08-14T21:17:32.0441889Z     finished with reduction, instead of waiting for all parameters'
2025-08-14T21:17:32.0442105Z     gradients to finish reduction. This can result in a training speedup
2025-08-14T21:17:32.0442322Z     depending on your workload since the optimizer can run while gradient
2025-08-14T21:17:32.0442563Z     reduction for other parameters are still ongoing. In addition, this has
2025-08-14T21:17:32.0442784Z     the potential to reduce peak memory consumption during training, as it
2025-08-14T21:17:32.0442992Z     only needs to load the per-parameter optimizer states of a single
2025-08-14T21:17:32.0443204Z     parameter at a time, instead of loading all per-parameter optimizer
2025-08-14T21:17:32.0443294Z     states at once.
2025-08-14T21:17:32.0443386Z     
2025-08-14T21:17:32.0443467Z     Args:
2025-08-14T21:17:32.0443660Z         optim (Type): a ``torch.optim.Optimizer`` class to be registered
2025-08-14T21:17:32.0443772Z         as a fused optimizer.
2025-08-14T21:17:32.0443940Z         *args (Sequence[Any]): Arguments to forward to `optim`.
2025-08-14T21:17:32.0444165Z         optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters
2025-08-14T21:17:32.0444388Z         to optimize, similar to `params` argument of traditional `torch.optim`
2025-08-14T21:17:32.0444592Z         Optimizers. If this is omitted, all DDP model parameters will be
2025-08-14T21:17:32.0444692Z         optimized.
2025-08-14T21:17:32.0444888Z         **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`.
2025-08-14T21:17:32.0444967Z     
2025-08-14T21:17:32.0445070Z     .. warning ::
2025-08-14T21:17:32.0445316Z         _register_fused_optim should only be called once on a DDP instance,
2025-08-14T21:17:32.0445528Z         and registering multiple fused optimizers for the same DDP model
2025-08-14T21:17:32.0445669Z         is not currently supported. Please ping
2025-08-14T21:17:32.0445907Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:32.0446019Z         for your use case.
2025-08-14T21:17:32.0446097Z     
2025-08-14T21:17:32.0446186Z     .. warning ::
2025-08-14T21:17:32.0446392Z         _register_fused_optim and register_comm_hook currently do not
2025-08-14T21:17:32.0446606Z         compose together, meaning that custom DDP communication hooks are
2025-08-14T21:17:32.0446777Z         not supported with overlapped optimizers. Please ping
2025-08-14T21:17:32.0447017Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:32.0447112Z         for your use case.
2025-08-14T21:17:32.0447190Z     
2025-08-14T21:17:32.0447292Z     .. warning ::
2025-08-14T21:17:32.0447519Z         Gradient accumulation and DDP `no_sync` are currently not supported
2025-08-14T21:17:32.0447657Z         with overlapped optimizer. Please ping
2025-08-14T21:17:32.0447879Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-08-14T21:17:32.0447973Z         for your use case.
2025-08-14T21:17:32.0448135Z     
2025-08-14T21:17:32.0448225Z     Example::
2025-08-14T21:17:32.0448333Z     
2025-08-14T21:17:32.0448478Z         >>> # xdoctest: +SKIP("No rendezvous handler")
2025-08-14T21:17:32.0448777Z         >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...')
2025-08-14T21:17:32.0448972Z         >>> net = torch.nn.parallel.DistributedDataParallel(model, pg)
2025-08-14T21:17:32.0449074Z         >>> lr = 1e-2
2025-08-14T21:17:32.0449166Z         >>> betas = (0.9, 0.99)
2025-08-14T21:17:32.0449268Z         >>> eps = 1e-6
2025-08-14T21:17:32.0449492Z         >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps)
2025-08-14T21:17:32.0449612Z         >>> # Example with subset of parameters
2025-08-14T21:17:32.0449760Z         >>> params_to_opt = [list(net.parameters())[0]]
2025-08-14T21:17:32.0449867Z         >>> net._register_fused_optim(
2025-08-14T21:17:32.0450099Z         ...   torch.optim.Adam, lr, optim_params=params_to_opt,  betas=betas, eps=eps
2025-08-14T21:17:32.0450194Z         ... )
2025-08-14T21:17:32.0450274Z     
2025-08-14T21:17:32.0450528Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0450619Z     
2025-08-14T21:17:32.0450714Z       warnings.warn(msg)
2025-08-14T21:17:32.0450805Z     
2025-08-14T21:17:32.0451001Z --- Parse Warning: 113 / 146 ---
2025-08-14T21:17:32.0452001Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14.
2025-08-14T21:17:32.0452276Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0452492Z     Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``.
2025-08-14T21:17:32.0452572Z     
2025-08-14T21:17:32.0452862Z         The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-08-14T21:17:32.0453134Z         Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-08-14T21:17:32.0453405Z         This function is used to facilitate the computation to adopt NHWC kernels, which
2025-08-14T21:17:32.0453712Z         provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-08-14T21:17:32.0453794Z     
2025-08-14T21:17:32.0453892Z         .. note::
2025-08-14T21:17:32.0454124Z             Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive
2025-08-14T21:17:32.0454378Z             than the utility function ``convert_conv2d_weight_memory_format``. Any
2025-08-14T21:17:32.0454600Z             layer with 4d weight will be affected by ``model.to``, which does not
2025-08-14T21:17:32.0454824Z             necessarily benefit from conversion to specified ``memory_format``.
2025-08-14T21:17:32.0455059Z             One place we are confident in is that NHWC(channels_last) conversion for
2025-08-14T21:17:32.0455279Z             convolution in cuDNN, as it is beneficial to run convolution in NHWC,
2025-08-14T21:17:32.0455480Z             even in cases where we have to apply permutation to input tensors.
2025-08-14T21:17:32.0455571Z     
2025-08-14T21:17:32.0455796Z             Hence our strategy here is to convert only the weight of convolution to
2025-08-14T21:17:32.0455913Z             channels_last. This ensures that;
2025-08-14T21:17:32.0456140Z             1. Fast convolution kernels will be used, the benefit of which could
2025-08-14T21:17:32.0456376Z             outweigh overhead of permutation (if input is not in the same format).
2025-08-14T21:17:32.0456620Z             2. No unnecessary permutations are applied on layers that do not benefit
2025-08-14T21:17:32.0456735Z             from memory_format conversion.
2025-08-14T21:17:32.0456813Z     
2025-08-14T21:17:32.0457050Z             The optimal case is that, layers between convolution layers are channels
2025-08-14T21:17:32.0457346Z             last compatible. Input tensor would be permuted to channels last when it
2025-08-14T21:17:32.0457601Z             encounters the first convolution layer and stay in that memory format.
2025-08-14T21:17:32.0457851Z             Hence following convolutions will not need to permute its input tensor.
2025-08-14T21:17:32.0457931Z     
2025-08-14T21:17:32.0458166Z             In case where a channels last incompatible layer is between convolution
2025-08-14T21:17:32.0458377Z             layers, we need to permute the input tensor back to contiguous format
2025-08-14T21:17:32.0458599Z             for that layer. The input tensor will go through the remaining layers in
2025-08-14T21:17:32.0458836Z             contiguous format and be permuted to channels last when it encounters
2025-08-14T21:17:32.0459045Z             another convolution layer. There's no point in propagating that
2025-08-14T21:17:32.0459263Z             permutation to an earlier layer, as most layers are quite agnostic to
2025-08-14T21:17:32.0459378Z             ``memory_format``.
2025-08-14T21:17:32.0459461Z     
2025-08-14T21:17:32.0459701Z             This claim might change when PyTorch supports fusion of permutation, as
2025-08-14T21:17:32.0459919Z             there might have been a better spot to fuse the permutation other than
2025-08-14T21:17:32.0460040Z             immediately before a convolution.
2025-08-14T21:17:32.0460135Z     
2025-08-14T21:17:32.0460218Z         Args:
2025-08-14T21:17:32.0460431Z             module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container
2025-08-14T21:17:32.0460549Z                                 ``nn.Module``
2025-08-14T21:17:32.0460700Z             memory_format: user specified ``memory_format``,
2025-08-14T21:17:32.0460893Z                 e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-08-14T21:17:32.0460973Z     
2025-08-14T21:17:32.0461057Z         Returns:
2025-08-14T21:17:32.0461213Z             The original module with updated ``nn.Conv2d``
2025-08-14T21:17:32.0461297Z     
2025-08-14T21:17:32.0461383Z         Example:
2025-08-14T21:17:32.0461537Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:32.0461693Z             >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-08-14T21:17:32.0461800Z             >>> input = torch.randint(
2025-08-14T21:17:32.0461962Z             ...     1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda"
2025-08-14T21:17:32.0462047Z             ... )
2025-08-14T21:17:32.0462151Z             >>> model = nn.Sequential(
2025-08-14T21:17:32.0462314Z             >>>     nn.Conv2d(8, 4, 3)).cuda().half()
2025-08-14T21:17:32.0462418Z             >>> # This is identical to:
2025-08-14T21:17:32.0462676Z             >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last)
2025-08-14T21:17:32.0462842Z             >>> model = nn.utils.convert_conv2d_weight_memory_format(
2025-08-14T21:17:32.0462958Z             ...     model, torch.channels_last
2025-08-14T21:17:32.0463058Z             ... )
2025-08-14T21:17:32.0463159Z             >>> out = model(input)
2025-08-14T21:17:32.0463242Z         
2025-08-14T21:17:32.0463511Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0463592Z     
2025-08-14T21:17:32.0463689Z       warnings.warn(msg)
2025-08-14T21:17:32.0463782Z     
2025-08-14T21:17:32.0463977Z --- Parse Warning: 114 / 146 ---
2025-08-14T21:17:32.0464994Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93.
2025-08-14T21:17:32.0465256Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0465468Z     Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format``
2025-08-14T21:17:32.0465792Z         The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-08-14T21:17:32.0466092Z         Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-08-14T21:17:32.0466393Z         This function is used to facilitate the computation to adopt NHWC kernels, which
2025-08-14T21:17:32.0466701Z         provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-08-14T21:17:32.0466781Z     
2025-08-14T21:17:32.0466880Z         .. note::
2025-08-14T21:17:32.0467122Z             Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive
2025-08-14T21:17:32.0467347Z             than the utility function ``convert_conv3d_weight_memory_format``. Any
2025-08-14T21:17:32.0467570Z             layer with 4d weight will be affected by ``model.to``, which does not
2025-08-14T21:17:32.0467795Z             necessarily benefit from conversion to specified ``memory_format``.
2025-08-14T21:17:32.0468046Z             One place we are confident in is that NDHWC(channels_last_3d) conversion for
2025-08-14T21:17:32.0468266Z             convolution in cuDNN, as it is beneficial to run convolution in NDHWC,
2025-08-14T21:17:32.0468468Z             even in cases where we have to apply permutation to input tensors.
2025-08-14T21:17:32.0468559Z     
2025-08-14T21:17:32.0468784Z             Hence our strategy here is to convert only the weight of convolution to
2025-08-14T21:17:32.0468905Z             channels_last_3d. This ensures that;
2025-08-14T21:17:32.0469133Z             1. Fast convolution kernels will be used, the benefit of which could
2025-08-14T21:17:32.0469367Z             outweigh overhead of permutation (if input is not in the same format).
2025-08-14T21:17:32.0469616Z             2. No unnecessary permutations are applied on layers that do not benefit
2025-08-14T21:17:32.0469728Z             from memory_format conversion.
2025-08-14T21:17:32.0469806Z     
2025-08-14T21:17:32.0470045Z             The optimal case is that, layers between convolution layers are channels
2025-08-14T21:17:32.0470282Z             last compatible. Input tensor would be permuted to channels last when it
2025-08-14T21:17:32.0470509Z             encounters the first convolution layer and stay in that memory format.
2025-08-14T21:17:32.0470756Z             Hence following convolutions will not need to permute its input tensor.
2025-08-14T21:17:32.0470835Z     
2025-08-14T21:17:32.0471069Z             In case where a channels last incompatible layer is between convolution
2025-08-14T21:17:32.0471278Z             layers, we need to permute the input tensor back to contiguous format
2025-08-14T21:17:32.0471655Z             for that layer. The input tensor will go through the remaining layers in
2025-08-14T21:17:32.0471896Z             contiguous format and be permuted to channels last when it encounters
2025-08-14T21:17:32.0472103Z             another convolution layer. There's no point in propagating that
2025-08-14T21:17:32.0472320Z             permutation to an earlier layer, as most layers are quite agnostic to
2025-08-14T21:17:32.0472433Z             ``memory_format``.
2025-08-14T21:17:32.0472514Z     
2025-08-14T21:17:32.0472758Z             This claim might change when PyTorch supports fusion of permutation, as
2025-08-14T21:17:32.0472975Z             there might have been a better spot to fuse the permutation other than
2025-08-14T21:17:32.0473094Z             immediately before a convolution.
2025-08-14T21:17:32.0473188Z     
2025-08-14T21:17:32.0473270Z         Args:
2025-08-14T21:17:32.0473483Z             module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container
2025-08-14T21:17:32.0473601Z                                 ``nn.Module``
2025-08-14T21:17:32.0473752Z             memory_format: user specified ``memory_format``,
2025-08-14T21:17:32.0473929Z                 e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-08-14T21:17:32.0474023Z     
2025-08-14T21:17:32.0474108Z         Returns:
2025-08-14T21:17:32.0474293Z             The original module with updated ``nn.Conv3d``
2025-08-14T21:17:32.0474398Z     
2025-08-14T21:17:32.0474485Z         Example:
2025-08-14T21:17:32.0474702Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-08-14T21:17:32.0474857Z             >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-08-14T21:17:32.0474964Z             >>> input = torch.randint(
2025-08-14T21:17:32.0475128Z             ...     1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda"
2025-08-14T21:17:32.0475211Z             ... )
2025-08-14T21:17:32.0475314Z             >>> model = nn.Sequential(
2025-08-14T21:17:32.0475441Z             >>>     nn.Conv3d(8, 4, 3)).cuda().half()
2025-08-14T21:17:32.0475544Z             >>> # This is identical to:
2025-08-14T21:17:32.0475811Z             >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d)
2025-08-14T21:17:32.0475974Z             >>> model = nn.utils.convert_conv3d_weight_memory_format(
2025-08-14T21:17:32.0476094Z             ...     model, torch.channels_last_3d
2025-08-14T21:17:32.0476188Z             ... )
2025-08-14T21:17:32.0476286Z             >>> out = model(input)
2025-08-14T21:17:32.0476370Z         
2025-08-14T21:17:32.0476633Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0476712Z     
2025-08-14T21:17:32.0476808Z       warnings.warn(msg)
2025-08-14T21:17:32.0476900Z     
2025-08-14T21:17:32.0477114Z --- Parse Warning: 115 / 146 ---
2025-08-14T21:17:32.0478100Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424.
2025-08-14T21:17:32.0478363Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0478520Z     Register a parametrization to a tensor in a module.
2025-08-14T21:17:32.0478614Z     
2025-08-14T21:17:32.0478892Z         Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``,
2025-08-14T21:17:32.0479178Z         the module will return the parametrized version ``parametrization(module.weight)``.
2025-08-14T21:17:32.0479454Z         If the original tensor requires a gradient, the backward pass will differentiate
2025-08-14T21:17:32.0479743Z         through :attr:`parametrization`, and the optimizer will update the tensor accordingly.
2025-08-14T21:17:32.0479839Z     
2025-08-14T21:17:32.0480150Z         The first time that a module registers a parametrization, this function will add an attribute
2025-08-14T21:17:32.0480439Z         ``parametrizations`` to the module of type :class:`~ParametrizationList`.
2025-08-14T21:17:32.0480532Z     
2025-08-14T21:17:32.0480784Z         The list of parametrizations on the tensor ``weight`` will be accessible under
2025-08-14T21:17:32.0480912Z         ``module.parametrizations.weight``.
2025-08-14T21:17:32.0481006Z     
2025-08-14T21:17:32.0481145Z         The original tensor will be accessible under
2025-08-14T21:17:32.0481309Z         ``module.parametrizations.weight.original``.
2025-08-14T21:17:32.0481389Z     
2025-08-14T21:17:32.0481657Z         Parametrizations may be concatenated by registering several parametrizations
2025-08-14T21:17:32.0481769Z         on the same attribute.
2025-08-14T21:17:32.0481846Z     
2025-08-14T21:17:32.0482087Z         The training mode of a registered parametrization is updated on registration
2025-08-14T21:17:32.0482237Z         to match the training mode of the host module
2025-08-14T21:17:32.0482317Z     
2025-08-14T21:17:32.0482623Z         Parametrized parameters and buffers have an inbuilt caching system that can be activated
2025-08-14T21:17:32.0482760Z         using the context manager :func:`cached`.
2025-08-14T21:17:32.0482839Z     
2025-08-14T21:17:32.0483085Z         A :attr:`parametrization` may optionally implement a method with signature
2025-08-14T21:17:32.0483180Z     
2025-08-14T21:17:32.0483284Z         .. code-block:: python
2025-08-14T21:17:32.0483461Z     
2025-08-14T21:17:32.0483679Z             def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]]
2025-08-14T21:17:32.0483783Z     
2025-08-14T21:17:32.0484060Z         This method is called on the unparametrized tensor when the first parametrization
2025-08-14T21:17:32.0484267Z         is registered to compute the initial value of the original tensor.
2025-08-14T21:17:32.0484575Z         If this method is not implemented, the original tensor will be just the unparametrized tensor.
2025-08-14T21:17:32.0484667Z     
2025-08-14T21:17:32.0484981Z         If all the parametrizations registered on a tensor implement `right_inverse` it is possible
2025-08-14T21:17:32.0485281Z         to initialize a parametrized tensor by assigning to it, as shown in the example below.
2025-08-14T21:17:32.0485364Z     
2025-08-14T21:17:32.0485588Z         It is possible for the first parametrization to depend on several inputs.
2025-08-14T21:17:32.0485848Z         This may be implemented returning a tuple of tensors from ``right_inverse``
2025-08-14T21:17:32.0486086Z         (see the example implementation of a ``RankOne`` parametrization below).
2025-08-14T21:17:32.0486166Z     
2025-08-14T21:17:32.0486517Z         In this case, the unconstrained tensors are also located under ``module.parametrizations.weight``
2025-08-14T21:17:32.0486647Z         with names ``original0``, ``original1``,...
2025-08-14T21:17:32.0486741Z     
2025-08-14T21:17:32.0486827Z         .. note::
2025-08-14T21:17:32.0486906Z     
2025-08-14T21:17:32.0487185Z             If unsafe=False (default) both the forward and right_inverse methods will be called
2025-08-14T21:17:32.0487334Z             once to perform a number of consistency checks.
2025-08-14T21:17:32.0487603Z             If unsafe=True, then right_inverse will be called if the tensor is not parametrized,
2025-08-14T21:17:32.0487735Z             and nothing will be called otherwise.
2025-08-14T21:17:32.0487815Z     
2025-08-14T21:17:32.0487901Z         .. note::
2025-08-14T21:17:32.0487994Z     
2025-08-14T21:17:32.0488197Z             In most situations, ``right_inverse`` will be a function such that
2025-08-14T21:17:32.0488331Z             ``forward(right_inverse(X)) == X`` (see
2025-08-14T21:17:32.0488614Z             `right inverse <https://en.wikipedia.org/wiki/Inverse_function#Right_inverses>`_).
2025-08-14T21:17:32.0488865Z             Sometimes, when the parametrization is not surjective, it may be reasonable
2025-08-14T21:17:32.0488971Z             to relax this.
2025-08-14T21:17:32.0489054Z     
2025-08-14T21:17:32.0489144Z         .. warning::
2025-08-14T21:17:32.0489275Z     
2025-08-14T21:17:32.0489552Z             If a parametrization depends on several inputs, :func:`~register_parametrization`
2025-08-14T21:17:32.0489810Z             will register a number of new parameters. If such parametrization is registered
2025-08-14T21:17:32.0490090Z             after the optimizer is created, these new parameters will need to be added manually
2025-08-14T21:17:32.0490292Z             to the optimizer. See :meth:`torch.Optimizer.add_param_group`.
2025-08-14T21:17:32.0490384Z     
2025-08-14T21:17:32.0490465Z         Args:
2025-08-14T21:17:32.0490676Z             module (nn.Module): module on which to register the parametrization
2025-08-14T21:17:32.0490902Z             tensor_name (str): name of the parameter or buffer on which to register
2025-08-14T21:17:32.0491008Z                 the parametrization
2025-08-14T21:17:32.0491212Z             parametrization (nn.Module): the parametrization to register
2025-08-14T21:17:32.0491325Z         Keyword args:
2025-08-14T21:17:32.0491543Z             unsafe (bool): a boolean flag that denotes whether the parametrization
2025-08-14T21:17:32.0491736Z                 may change the dtype and shape of the tensor. Default: `False`
2025-08-14T21:17:32.0492019Z                 Warning: the parametrization is not checked for consistency upon registration.
2025-08-14T21:17:32.0492170Z                 Enable this flag at your own risk.
2025-08-14T21:17:32.0492288Z     
2025-08-14T21:17:32.0492370Z         Raises:
2025-08-14T21:17:32.0492684Z             ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name`
2025-08-14T21:17:32.0492777Z     
2025-08-14T21:17:32.0492866Z         Examples:
2025-08-14T21:17:32.0493018Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-08-14T21:17:32.0493126Z             >>> import torch
2025-08-14T21:17:32.0493230Z             >>> import torch.nn as nn
2025-08-14T21:17:32.0493369Z             >>> import torch.nn.utils.parametrize as P
2025-08-14T21:17:32.0493464Z             >>>
2025-08-14T21:17:32.0493575Z             >>> class Symmetric(nn.Module):
2025-08-14T21:17:32.0493680Z             >>>     def forward(self, X):
2025-08-14T21:17:32.0493874Z             >>>         return X.triu() + X.triu(1).T  # Return a symmetric matrix
2025-08-14T21:17:32.0493973Z             >>>
2025-08-14T21:17:32.0494086Z             >>>     def right_inverse(self, A):
2025-08-14T21:17:32.0494202Z             >>>         return A.triu()
2025-08-14T21:17:32.0494287Z             >>>
2025-08-14T21:17:32.0494387Z             >>> m = nn.Linear(5, 5)
2025-08-14T21:17:32.0494570Z             >>> P.register_parametrization(m, "weight", Symmetric())
2025-08-14T21:17:32.0494810Z             >>> print(torch.allclose(m.weight, m.weight.T))  # m.weight is now symmetric
2025-08-14T21:17:32.0494894Z             True
2025-08-14T21:17:32.0495008Z             >>> A = torch.rand(5, 5)
2025-08-14T21:17:32.0495120Z             >>> A = A + A.T  # A is now symmetric
2025-08-14T21:17:32.0495338Z             >>> m.weight = A  # Initialize the weight to be the symmetric matrix A
2025-08-14T21:17:32.0495462Z             >>> print(torch.allclose(m.weight, A))
2025-08-14T21:17:32.0495545Z             True
2025-08-14T21:17:32.0495639Z     
2025-08-14T21:17:32.0495749Z             >>> class RankOne(nn.Module):
2025-08-14T21:17:32.0495859Z             >>>     def forward(self, x, y):
2025-08-14T21:17:32.0496019Z             >>> # Form a rank 1 matrix multiplying two vectors
2025-08-14T21:17:32.0496157Z             >>>         return x.unsqueeze(-1) @ y.unsqueeze(-2)
2025-08-14T21:17:32.0496243Z             >>>
2025-08-14T21:17:32.0496373Z             >>>     def right_inverse(self, Z):
2025-08-14T21:17:32.0496494Z             >>> # Project Z onto the rank 1 matrices
2025-08-14T21:17:32.0496660Z             >>>         U, S, Vh = torch.linalg.svd(Z, full_matrices=False)
2025-08-14T21:17:32.0496782Z             >>> # Return rescaled singular vectors
2025-08-14T21:17:32.0496935Z             >>>         s0_sqrt = S[0].sqrt().unsqueeze(-1)
2025-08-14T21:17:32.0497100Z             >>>         return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt
2025-08-14T21:17:32.0497186Z             >>>
2025-08-14T21:17:32.0497336Z             >>> linear_rank_one = P.register_parametrization(
2025-08-14T21:17:32.0497475Z             ...     nn.Linear(4, 4), "weight", RankOne()
2025-08-14T21:17:32.0497560Z             ... )
2025-08-14T21:17:32.0497780Z             >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item())
2025-08-14T21:17:32.0497865Z             1
2025-08-14T21:17:32.0497944Z     
2025-08-14T21:17:32.0498037Z         
2025-08-14T21:17:32.0498290Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0498369Z     
2025-08-14T21:17:32.0498481Z       warnings.warn(msg)
2025-08-14T21:17:32.0498561Z     
2025-08-14T21:17:32.0498770Z --- Parse Warning: 116 / 146 ---
2025-08-14T21:17:32.0499666Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979.
2025-08-14T21:17:32.0499927Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0500247Z     Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension.
2025-08-14T21:17:32.0500386Z     
2025-08-14T21:17:32.0500618Z         Prunes tensor corresponding to parameter called ``name`` in ``module``
2025-08-14T21:17:32.0500875Z         by removing the specified ``amount`` of (currently unpruned) channels
2025-08-14T21:17:32.0501053Z         along the specified ``dim`` with the lowest L\ ``n``-norm.
2025-08-14T21:17:32.0501246Z         Modifies module in place (and also return the modified module)
2025-08-14T21:17:32.0501341Z         by:
2025-08-14T21:17:32.0501418Z     
2025-08-14T21:17:32.0501625Z         1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:32.0501855Z            binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:32.0502063Z         2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:32.0502278Z            original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:32.0502372Z            ``name+'_orig'``.
2025-08-14T21:17:32.0502453Z     
2025-08-14T21:17:32.0502550Z         Args:
2025-08-14T21:17:32.0502733Z             module (nn.Module): module containing the tensor to prune
2025-08-14T21:17:32.0502913Z             name (str): parameter name within ``module`` on which pruning
2025-08-14T21:17:32.0503018Z                     will act.
2025-08-14T21:17:32.0503187Z             amount (int or float): quantity of parameters to prune.
2025-08-14T21:17:32.0503372Z                 If ``float``, should be between 0.0 and 1.0 and represent the
2025-08-14T21:17:32.0503571Z                 fraction of parameters to prune. If ``int``, it represents the
2025-08-14T21:17:32.0503704Z                 absolute number of parameters to prune.
2025-08-14T21:17:32.0503905Z             n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid
2025-08-14T21:17:32.0504057Z                 entries for argument ``p`` in :func:`torch.norm`.
2025-08-14T21:17:32.0504257Z             dim (int): index of the dim along which we define channels to prune.
2025-08-14T21:17:32.0504506Z             importance_scores (torch.Tensor): tensor of importance scores (of same
2025-08-14T21:17:32.0504696Z                 shape as module parameter) used to compute mask for pruning.
2025-08-14T21:17:32.0504929Z                 The values in this tensor indicate the importance of the corresponding
2025-08-14T21:17:32.0505060Z                 elements in the parameter being pruned.
2025-08-14T21:17:32.0505282Z                 If unspecified or None, the module parameter will be used in its place.
2025-08-14T21:17:32.0505378Z     
2025-08-14T21:17:32.0505465Z         Returns:
2025-08-14T21:17:32.0505714Z             module (nn.Module): modified (i.e. pruned) version of the input module
2025-08-14T21:17:32.0505807Z     
2025-08-14T21:17:32.0505897Z         Examples:
2025-08-14T21:17:32.0506019Z             >>> from torch.nn.utils import prune
2025-08-14T21:17:32.0506141Z             >>> m = prune.ln_structured(
2025-08-14T21:17:32.0506325Z             ...     nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf")
2025-08-14T21:17:32.0506424Z             ... )
2025-08-14T21:17:32.0506505Z         
2025-08-14T21:17:32.0506754Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0506846Z     
2025-08-14T21:17:32.0506942Z       warnings.warn(msg)
2025-08-14T21:17:32.0507021Z     
2025-08-14T21:17:32.0507226Z --- Parse Warning: 117 / 146 ---
2025-08-14T21:17:32.0508135Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026.
2025-08-14T21:17:32.0508405Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0508488Z     
2025-08-14T21:17:32.0508921Z     Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``.
2025-08-14T21:17:32.0509409Z     
2025-08-14T21:17:32.0509523Z     Modifies modules in place by:
2025-08-14T21:17:32.0509659Z     
2025-08-14T21:17:32.0509883Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:32.0510101Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:32.0510313Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:32.0510535Z        original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:32.0510631Z        ``name+'_orig'``.
2025-08-14T21:17:32.0510726Z     
2025-08-14T21:17:32.0510814Z     Args:
2025-08-14T21:17:32.0511018Z         parameters (Iterable of (module, name) tuples): parameters of
2025-08-14T21:17:32.0511224Z             the model to prune in a global fashion, i.e. by aggregating all
2025-08-14T21:17:32.0511502Z             weights prior to deciding which ones to prune. module must be of
2025-08-14T21:17:32.0511662Z             type :class:`nn.Module`, and name must be a string.
2025-08-14T21:17:32.0511900Z         pruning_method (function): a valid pruning function from this module,
2025-08-14T21:17:32.0512078Z             or a custom one implemented by the user that satisfies the
2025-08-14T21:17:32.0512321Z             implementation guidelines and has ``PRUNING_TYPE='unstructured'``.
2025-08-14T21:17:32.0512549Z         importance_scores (dict): a dictionary mapping (module, name) tuples to
2025-08-14T21:17:32.0512773Z             the corresponding parameter's importance scores tensor. The tensor
2025-08-14T21:17:32.0512999Z             should be the same shape as the parameter, and is used for computing
2025-08-14T21:17:32.0513098Z             mask for pruning.
2025-08-14T21:17:32.0513306Z             If unspecified or None, the parameter will be used in place of its
2025-08-14T21:17:32.0513423Z             importance scores.
2025-08-14T21:17:32.0513549Z         kwargs: other keyword arguments such as:
2025-08-14T21:17:32.0513746Z             amount (int or float): quantity of parameters to prune across the
2025-08-14T21:17:32.0513867Z             specified parameters.
2025-08-14T21:17:32.0514038Z             If ``float``, should be between 0.0 and 1.0 and represent the
2025-08-14T21:17:32.0514247Z             fraction of parameters to prune. If ``int``, it represents the
2025-08-14T21:17:32.0514375Z             absolute number of parameters to prune.
2025-08-14T21:17:32.0514455Z     
2025-08-14T21:17:32.0514550Z     Raises:
2025-08-14T21:17:32.0514701Z         TypeError: if ``PRUNING_TYPE != 'unstructured'``
2025-08-14T21:17:32.0514780Z     
2025-08-14T21:17:32.0514922Z     Note:
2025-08-14T21:17:32.0515134Z         Since global structured pruning doesn't make much sense unless the
2025-08-14T21:17:32.0515331Z         norm is normalized by the size of the parameter, we now limit the
2025-08-14T21:17:32.0515493Z         scope of global pruning to unstructured methods.
2025-08-14T21:17:32.0515574Z     
2025-08-14T21:17:32.0515672Z     Examples:
2025-08-14T21:17:32.0515793Z         >>> from torch.nn.utils import prune
2025-08-14T21:17:32.0515915Z         >>> from collections import OrderedDict
2025-08-14T21:17:32.0516030Z         >>> net = nn.Sequential(
2025-08-14T21:17:32.0516125Z         ...     OrderedDict(
2025-08-14T21:17:32.0516208Z         ...         [
2025-08-14T21:17:32.0516340Z         ...             ("first", nn.Linear(10, 4)),
2025-08-14T21:17:32.0516455Z         ...             ("second", nn.Linear(4, 1)),
2025-08-14T21:17:32.0516538Z         ...         ]
2025-08-14T21:17:32.0516633Z         ...     )
2025-08-14T21:17:32.0516714Z         ... )
2025-08-14T21:17:32.0516820Z         >>> parameters_to_prune = (
2025-08-14T21:17:32.0516932Z         ...     (net.first, "weight"),
2025-08-14T21:17:32.0517033Z         ...     (net.second, "weight"),
2025-08-14T21:17:32.0517125Z         ... )
2025-08-14T21:17:32.0517232Z         >>> prune.global_unstructured(
2025-08-14T21:17:32.0517333Z         ...     parameters_to_prune,
2025-08-14T21:17:32.0517501Z         ...     pruning_method=prune.L1Unstructured,
2025-08-14T21:17:32.0517653Z         ...     amount=10,
2025-08-14T21:17:32.0517734Z         ... )
2025-08-14T21:17:32.0517967Z         >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0))
2025-08-14T21:17:32.0518051Z         tensor(10)
2025-08-14T21:17:32.0518130Z     
2025-08-14T21:17:32.0518220Z     
2025-08-14T21:17:32.0518473Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0518564Z     
2025-08-14T21:17:32.0518658Z       warnings.warn(msg)
2025-08-14T21:17:32.0518736Z     
2025-08-14T21:17:32.0518970Z --- Parse Warning: 118 / 146 ---
2025-08-14T21:17:32.0519854Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149.
2025-08-14T21:17:32.0520116Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0520521Z     Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``.
2025-08-14T21:17:32.0520604Z     
2025-08-14T21:17:32.0520828Z         Modifies module in place (and also return the modified module) by:
2025-08-14T21:17:32.0520907Z     
2025-08-14T21:17:32.0521117Z         1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-08-14T21:17:32.0521349Z            binary mask applied to the parameter ``name`` by the pruning method.
2025-08-14T21:17:32.0521560Z         2) replacing the parameter ``name`` by its pruned version, while the
2025-08-14T21:17:32.0521766Z            original (unpruned) parameter is stored in a new parameter named
2025-08-14T21:17:32.0521873Z            ``name+'_orig'``.
2025-08-14T21:17:32.0521952Z     
2025-08-14T21:17:32.0522034Z         Args:
2025-08-14T21:17:32.0522223Z             module (nn.Module): module containing the tensor to prune
2025-08-14T21:17:32.0522407Z             name (str): parameter name within ``module`` on which pruning
2025-08-14T21:17:32.0522512Z                 will act.
2025-08-14T21:17:32.0522687Z             mask (Tensor): binary mask to be applied to the parameter.
2025-08-14T21:17:32.0522766Z     
2025-08-14T21:17:32.0522861Z         Returns:
2025-08-14T21:17:32.0523077Z             module (nn.Module): modified (i.e. pruned) version of the input module
2025-08-14T21:17:32.0523155Z     
2025-08-14T21:17:32.0523256Z         Examples:
2025-08-14T21:17:32.0523375Z             >>> from torch.nn.utils import prune
2025-08-14T21:17:32.0523518Z             >>> m = prune.custom_from_mask(
2025-08-14T21:17:32.0523701Z             ...     nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0])
2025-08-14T21:17:32.0523783Z             ... )
2025-08-14T21:17:32.0523894Z             >>> print(m.bias_mask)
2025-08-14T21:17:32.0523987Z             tensor([0., 1., 0.])
2025-08-14T21:17:32.0524067Z     
2025-08-14T21:17:32.0524162Z         
2025-08-14T21:17:32.0524416Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0524499Z     
2025-08-14T21:17:32.0524606Z       warnings.warn(msg)
2025-08-14T21:17:32.0524686Z     
2025-08-14T21:17:32.0524875Z --- Parse Warning: 119 / 146 ---
2025-08-14T21:17:32.0525779Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=350.
2025-08-14T21:17:32.0526042Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0526203Z     Pad a packed batch of variable length sequences.
2025-08-14T21:17:32.0526283Z     
2025-08-14T21:17:32.0526458Z         It is an inverse operation to :func:`pack_padded_sequence`.
2025-08-14T21:17:32.0526552Z     
2025-08-14T21:17:32.0526861Z         The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``)
2025-08-14T21:17:32.0527124Z         or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest
2025-08-14T21:17:32.0527278Z         sequence and ``B`` is the batch size.
2025-08-14T21:17:32.0527358Z     
2025-08-14T21:17:32.0527444Z         Example:
2025-08-14T21:17:32.0527698Z             >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
2025-08-14T21:17:32.0527846Z             >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]])
2025-08-14T21:17:32.0527955Z             >>> lens = [2, 1, 3]
2025-08-14T21:17:32.0528076Z             >>> packed = pack_padded_sequence(
2025-08-14T21:17:32.0528231Z             ...     seq, lens, batch_first=True, enforce_sorted=False
2025-08-14T21:17:32.0528330Z             ... )
2025-08-14T21:17:32.0528420Z             >>> packed
2025-08-14T21:17:32.0528662Z             PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]),
2025-08-14T21:17:32.0528897Z                            sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0]))
2025-08-14T21:17:32.0529147Z             >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True)
2025-08-14T21:17:32.0529255Z             >>> seq_unpacked
2025-08-14T21:17:32.0529352Z             tensor([[1, 2, 0],
2025-08-14T21:17:32.0529442Z                     [3, 0, 0],
2025-08-14T21:17:32.0529545Z                     [4, 5, 6]])
2025-08-14T21:17:32.0529639Z             >>> lens_unpacked
2025-08-14T21:17:32.0529732Z             tensor([2, 1, 3])
2025-08-14T21:17:32.0529826Z     
2025-08-14T21:17:32.0529925Z         .. note::
2025-08-14T21:17:32.0530069Z             :attr:`total_length` is useful to implement the
2025-08-14T21:17:32.0530306Z             ``pack sequence -> recurrent network -> unpack sequence`` pattern in a
2025-08-14T21:17:32.0530521Z             :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`.
2025-08-14T21:17:32.0530772Z             See :ref:`this FAQ section <pack-rnn-unpack-with-data-parallelism>` for
2025-08-14T21:17:32.0530861Z             details.
2025-08-14T21:17:32.0530944Z     
2025-08-14T21:17:32.0531039Z         Args:
2025-08-14T21:17:32.0531168Z             sequence (PackedSequence): batch to pad
2025-08-14T21:17:32.0531404Z             batch_first (bool, optional): if ``True``, the output will be in ``B x T x *``
2025-08-14T21:17:32.0531531Z                 format, ``T x B x *`` otherwise.
2025-08-14T21:17:32.0531723Z             padding_value (float, optional): values for padded elements.
2025-08-14T21:17:32.0531979Z             total_length (int, optional): if not ``None``, the output will be padded to
2025-08-14T21:17:32.0532228Z                 have length :attr:`total_length`. This method will throw :class:`ValueError`
2025-08-14T21:17:32.0532414Z                 if :attr:`total_length` is less than the max sequence length in
2025-08-14T21:17:32.0532523Z                 :attr:`sequence`.
2025-08-14T21:17:32.0532600Z     
2025-08-14T21:17:32.0532687Z         Returns:
2025-08-14T21:17:32.0532885Z             Tuple of Tensor containing the padded sequence, and a Tensor
2025-08-14T21:17:32.0533081Z             containing the list of lengths of each sequence in the batch.
2025-08-14T21:17:32.0533303Z             Batch elements will be re-ordered as they were ordered originally when
2025-08-14T21:17:32.0533527Z             the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``.
2025-08-14T21:17:32.0533606Z         
2025-08-14T21:17:32.0533867Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0533948Z     
2025-08-14T21:17:32.0534043Z       warnings.warn(msg)
2025-08-14T21:17:32.0534133Z     
2025-08-14T21:17:32.0534323Z --- Parse Warning: 120 / 146 ---
2025-08-14T21:17:32.0535248Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808.
2025-08-14T21:17:32.0535566Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0535891Z     Contains a list of schedulers expected to be called sequentially during the optimization process.
2025-08-14T21:17:32.0535971Z     
2025-08-14T21:17:32.0536353Z         Specifically, the schedulers will be called according to the milestone points, which should provide exact
2025-08-14T21:17:32.0536571Z         intervals by which each scheduler should be called at a given epoch.
2025-08-14T21:17:32.0536663Z     
2025-08-14T21:17:32.0536746Z         Args:
2025-08-14T21:17:32.0536883Z             optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:32.0537041Z             schedulers (list): List of chained schedulers.
2025-08-14T21:17:32.0537256Z             milestones (list): List of integers that reflects milestone points.
2025-08-14T21:17:32.0537424Z             last_epoch (int): The index of last epoch. Default: -1.
2025-08-14T21:17:32.0537519Z     
2025-08-14T21:17:32.0537603Z         Example:
2025-08-14T21:17:32.0537719Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0537870Z             >>> # Assuming optimizer uses lr = 0.05 for all groups
2025-08-14T21:17:32.0537978Z             >>> # lr = 0.005     if epoch == 0
2025-08-14T21:17:32.0538094Z             >>> # lr = 0.005     if epoch == 1
2025-08-14T21:17:32.0538195Z             >>> # lr = 0.005     if epoch == 2
2025-08-14T21:17:32.0538281Z             >>> # ...
2025-08-14T21:17:32.0538396Z             >>> # lr = 0.05      if epoch == 20
2025-08-14T21:17:32.0538500Z             >>> # lr = 0.045     if epoch == 21
2025-08-14T21:17:32.0538602Z             >>> # lr = 0.0405    if epoch == 22
2025-08-14T21:17:32.0538813Z             >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20)
2025-08-14T21:17:32.0538969Z             >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9)
2025-08-14T21:17:32.0539091Z             >>> scheduler = SequentialLR(
2025-08-14T21:17:32.0539188Z             ...     optimizer,
2025-08-14T21:17:32.0539321Z             ...     schedulers=[scheduler1, scheduler2],
2025-08-14T21:17:32.0539433Z             ...     milestones=[20],
2025-08-14T21:17:32.0539515Z             ... )
2025-08-14T21:17:32.0539620Z             >>> for epoch in range(100):
2025-08-14T21:17:32.0539723Z             >>>     train(...)
2025-08-14T21:17:32.0539820Z             >>>     validate(...)
2025-08-14T21:17:32.0539919Z             >>>     scheduler.step()
2025-08-14T21:17:32.0540010Z     
2025-08-14T21:17:32.0540217Z         .. image:: ../scripts/lr_scheduler_images/SequentialLR.png
2025-08-14T21:17:32.0540301Z         
2025-08-14T21:17:32.0540565Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0540644Z     
2025-08-14T21:17:32.0540753Z       warnings.warn(msg)
2025-08-14T21:17:32.0540832Z     
2025-08-14T21:17:32.0541018Z --- Parse Warning: 121 / 146 ---
2025-08-14T21:17:32.0541965Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233.
2025-08-14T21:17:32.0542214Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-08-14T21:17:32.0542396Z     Reduce learning rate when a metric has stopped improving.
2025-08-14T21:17:32.0542487Z     
2025-08-14T21:17:32.0542687Z         Models often benefit from reducing the learning rate by a factor
2025-08-14T21:17:32.0542891Z         of 2-10 once learning stagnates. This scheduler reads a metrics
2025-08-14T21:17:32.0543084Z         quantity and if no improvement is seen for a 'patience' number
2025-08-14T21:17:32.0543206Z         of epochs, the learning rate is reduced.
2025-08-14T21:17:32.0543296Z     
2025-08-14T21:17:32.0543377Z         Args:
2025-08-14T21:17:32.0543511Z             optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:32.0543749Z             mode (str): One of `min`, `max`. In `min` mode, lr will
2025-08-14T21:17:32.0543929Z                 be reduced when the quantity monitored has stopped
2025-08-14T21:17:32.0544100Z                 decreasing; in `max` mode it will be reduced when the
2025-08-14T21:17:32.0544290Z                 quantity monitored has stopped increasing. Default: 'min'.
2025-08-14T21:17:32.0544460Z             factor (float): Factor by which the learning rate will be
2025-08-14T21:17:32.0544608Z                 reduced. new_lr = lr * factor. Default: 0.1.
2025-08-14T21:17:32.0544831Z             patience (int): The number of allowed epochs with no improvement after
2025-08-14T21:17:32.0544960Z                 which the learning rate will be reduced.
2025-08-14T21:17:32.0545203Z                 For example, consider the case of having no patience (`patience = 0`).
2025-08-14T21:17:32.0545567Z                 In the first epoch, a baseline is established and is always considered good as there's no previous baseline.
2025-08-14T21:17:32.0545791Z                 In the second epoch, if the performance is worse than the baseline,
2025-08-14T21:17:32.0545943Z                 we have what is considered an intolerable epoch.
2025-08-14T21:17:32.0546207Z                 Since the count of intolerable epochs (1) is greater than the patience level (0),
2025-08-14T21:17:32.0546389Z                 the learning rate is reduced at the end of this epoch.
2025-08-14T21:17:32.0546711Z                 From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch
2025-08-14T21:17:32.0547035Z                 if the performance is worse than the baseline. If the performance improves or remains the same,
2025-08-14T21:17:32.0547169Z                 the learning rate is not adjusted.
2025-08-14T21:17:32.0547263Z                 Default: 10.
2025-08-14T21:17:32.0547465Z             threshold (float): Threshold for measuring the new optimum,
2025-08-14T21:17:32.0547625Z                 to only focus on significant changes. Default: 1e-4.
2025-08-14T21:17:32.0547799Z             threshold_mode (str): One of `rel`, `abs`. In `rel` mode,
2025-08-14T21:17:32.0547968Z                 dynamic_threshold = best * ( 1 + threshold ) in 'max'
2025-08-14T21:17:32.0548108Z                 mode or best * ( 1 - threshold ) in `min` mode.
2025-08-14T21:17:32.0548264Z                 In `abs` mode, dynamic_threshold = best + threshold in
2025-08-14T21:17:32.0548452Z                 `max` mode or best - threshold in `min` mode. Default: 'rel'.
2025-08-14T21:17:32.0548649Z             cooldown (int): Number of epochs to wait before resuming
2025-08-14T21:17:32.0548835Z                 normal operation after lr has been reduced. Default: 0.
2025-08-14T21:17:32.0548996Z             min_lr (float or list): A scalar or a list of scalars. A
2025-08-14T21:17:32.0549155Z                 lower bound on the learning rate of all param groups
2025-08-14T21:17:32.0549299Z                 or each group respectively. Default: 0.
2025-08-14T21:17:32.0549477Z             eps (float): Minimal decay applied to lr. If the difference
2025-08-14T21:17:32.0549655Z                 between new and old lr is smaller than eps, the update is
2025-08-14T21:17:32.0549771Z                 ignored. Default: 1e-8.
2025-08-14T21:17:32.0549851Z     
2025-08-14T21:17:32.0549952Z         Example:
2025-08-14T21:17:32.0550051Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0550276Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-08-14T21:17:32.0550445Z             >>> scheduler = ReduceLROnPlateau(optimizer, "min")
2025-08-14T21:17:32.0550548Z             >>> for epoch in range(10):
2025-08-14T21:17:32.0550641Z             >>>     train(...)
2025-08-14T21:17:32.0550759Z             >>>     val_loss = validate(...)
2025-08-14T21:17:32.0550910Z             >>> # Note that step should be called after validate()
2025-08-14T21:17:32.0551022Z             >>>     scheduler.step(val_loss)
2025-08-14T21:17:32.0551166Z     
2025-08-14T21:17:32.0551362Z         .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png
2025-08-14T21:17:32.0551578Z         
2025-08-14T21:17:32.0551992Z     Original Error: IndentationError('unexpected indent', ('<source_block>', 8, 4, '    scheduler.step(val_loss)\n', 8, -1))
2025-08-14T21:17:32.0552071Z     
2025-08-14T21:17:32.0552190Z         scheduler.step(val_loss)
2025-08-14T21:17:32.0552270Z        ^
2025-08-14T21:17:32.0552364Z       warnings.warn(msg)
2025-08-14T21:17:32.0552457Z     
2025-08-14T21:17:32.0552659Z --- Parse Warning: 122 / 146 ---
2025-08-14T21:17:32.0553543Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430.
2025-08-14T21:17:32.0553820Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0554147Z     Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR).
2025-08-14T21:17:32.0554247Z     
2025-08-14T21:17:32.0554527Z         The policy cycles the learning rate between two boundaries with a constant frequency,
2025-08-14T21:17:32.0554783Z         as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_.
2025-08-14T21:17:32.0555027Z         The distance between the two boundaries can be scaled on a per-iteration
2025-08-14T21:17:32.0555128Z         or per-cycle basis.
2025-08-14T21:17:32.0555206Z     
2025-08-14T21:17:32.0555467Z         Cyclical learning rate policy changes the learning rate after every batch.
2025-08-14T21:17:32.0555662Z         `step` should be called after a batch has been used for training.
2025-08-14T21:17:32.0555757Z     
2025-08-14T21:17:32.0555963Z         This class has three built-in policies, as put forth in the paper:
2025-08-14T21:17:32.0556044Z     
2025-08-14T21:17:32.0556260Z         * "triangular": A basic triangular cycle without amplitude scaling.
2025-08-14T21:17:32.0556561Z         * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle.
2025-08-14T21:17:32.0556884Z         * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}`
2025-08-14T21:17:32.0556998Z           at each cycle iteration.
2025-08-14T21:17:32.0557077Z     
2025-08-14T21:17:32.0557328Z         This implementation was adapted from the github repo: `bckenstler/CLR`_
2025-08-14T21:17:32.0557418Z     
2025-08-14T21:17:32.0557502Z         Args:
2025-08-14T21:17:32.0557683Z             optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:32.0557862Z             base_lr (float or list): Initial learning rate which is the
2025-08-14T21:17:32.0558028Z                 lower boundary in the cycle for each parameter group.
2025-08-14T21:17:32.0558243Z             max_lr (float or list): Upper learning rate boundaries in the cycle
2025-08-14T21:17:32.0558377Z                 for each parameter group. Functionally,
2025-08-14T21:17:32.0558535Z                 it defines the cycle amplitude (max_lr - base_lr).
2025-08-14T21:17:32.0558677Z                 The lr at any cycle is the sum of base_lr
2025-08-14T21:17:32.0558817Z                 and some scaling of the amplitude; therefore
2025-08-14T21:17:32.0558978Z                 max_lr may not actually be reached depending on
2025-08-14T21:17:32.0559081Z                 scaling function.
2025-08-14T21:17:32.0559249Z             step_size_up (int): Number of training iterations in the
2025-08-14T21:17:32.0559395Z                 increasing half of a cycle. Default: 2000
2025-08-14T21:17:32.0559575Z             step_size_down (int): Number of training iterations in the
2025-08-14T21:17:32.0559745Z                 decreasing half of a cycle. If step_size_down is None,
2025-08-14T21:17:32.0559891Z                 it is set to step_size_up. Default: None
2025-08-14T21:17:32.0560088Z             mode (str): One of {triangular, triangular2, exp_range}.
2025-08-14T21:17:32.0560274Z                 Values correspond to policies detailed above.
2025-08-14T21:17:32.0560453Z                 If scale_fn is not None, this argument is ignored.
2025-08-14T21:17:32.0560558Z                 Default: 'triangular'
2025-08-14T21:17:32.0560738Z             gamma (float): Constant in 'exp_range' scaling function:
2025-08-14T21:17:32.0560848Z                 gamma**(cycle iterations)
2025-08-14T21:17:32.0560943Z                 Default: 1.0
2025-08-14T21:17:32.0561148Z             scale_fn (function): Custom scaling policy defined by a single
2025-08-14T21:17:32.0561270Z                 argument lambda function, where
2025-08-14T21:17:32.0561401Z                 0 <= scale_fn(x) <= 1 for all x >= 0.
2025-08-14T21:17:32.0561526Z                 If specified, then 'mode' is ignored.
2025-08-14T21:17:32.0561621Z                 Default: None
2025-08-14T21:17:32.0561765Z             scale_mode (str): {'cycle', 'iterations'}.
2025-08-14T21:17:32.0561898Z                 Defines whether scale_fn is evaluated on
2025-08-14T21:17:32.0562035Z                 cycle number or cycle iterations (training
2025-08-14T21:17:32.0562170Z                 iterations since start of cycle).
2025-08-14T21:17:32.0562271Z                 Default: 'cycle'
2025-08-14T21:17:32.0562466Z             cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-08-14T21:17:32.0562667Z                 to learning rate between 'base_momentum' and 'max_momentum'.
2025-08-14T21:17:32.0562763Z                 Default: True
2025-08-14T21:17:32.0562999Z             base_momentum (float or list): Lower momentum boundaries in the cycle
2025-08-14T21:17:32.0563202Z                 for each parameter group. Note that momentum is cycled inversely
2025-08-14T21:17:32.0563360Z                 to learning rate; at the peak of a cycle, momentum is
2025-08-14T21:17:32.0563512Z                 'base_momentum' and learning rate is 'max_lr'.
2025-08-14T21:17:32.0563609Z                 Default: 0.8
2025-08-14T21:17:32.0563824Z             max_momentum (float or list): Upper momentum boundaries in the cycle
2025-08-14T21:17:32.0563971Z                 for each parameter group. Functionally,
2025-08-14T21:17:32.0564160Z                 it defines the cycle amplitude (max_momentum - base_momentum).
2025-08-14T21:17:32.0564352Z                 The momentum at any cycle is the difference of max_momentum
2025-08-14T21:17:32.0564488Z                 and some scaling of the amplitude; therefore
2025-08-14T21:17:32.0564656Z                 base_momentum may not actually be reached depending on
2025-08-14T21:17:32.0564872Z                 scaling function. Note that momentum is cycled inversely
2025-08-14T21:17:32.0565082Z                 to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-08-14T21:17:32.0565196Z                 and learning rate is 'base_lr'
2025-08-14T21:17:32.0565304Z                 Default: 0.9
2025-08-14T21:17:32.0565525Z             last_epoch (int): The index of the last batch. This parameter is used when
2025-08-14T21:17:32.0565753Z                 resuming a training job. Since `step()` should be invoked after each
2025-08-14T21:17:32.0565967Z                 batch instead of after each epoch, this number represents the total
2025-08-14T21:17:32.0566186Z                 number of *batches* computed, not the total number of epochs computed.
2025-08-14T21:17:32.0566389Z                 When last_epoch=-1, the schedule is started from the beginning.
2025-08-14T21:17:32.0566484Z                 Default: -1
2025-08-14T21:17:32.0566562Z     
2025-08-14T21:17:32.0566659Z         Example:
2025-08-14T21:17:32.0566757Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0566986Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-08-14T21:17:32.0567155Z             >>> scheduler = torch.optim.lr_scheduler.CyclicLR(
2025-08-14T21:17:32.0567248Z             ...     optimizer,
2025-08-14T21:17:32.0567359Z             ...     base_lr=0.01,
2025-08-14T21:17:32.0567499Z             ...     max_lr=0.1,
2025-08-14T21:17:32.0567598Z             ...     step_size_up=10,
2025-08-14T21:17:32.0567721Z             ... )
2025-08-14T21:17:32.0567870Z             >>> data_loader = torch.utils.data.DataLoader(...)
2025-08-14T21:17:32.0567972Z             >>> for epoch in range(10):
2025-08-14T21:17:32.0568095Z             >>>     for batch in data_loader:
2025-08-14T21:17:32.0568196Z             >>>         train_batch(...)
2025-08-14T21:17:32.0568298Z             >>>         scheduler.step()
2025-08-14T21:17:32.0568392Z     
2025-08-14T21:17:32.0568553Z         .. image:: ../scripts/lr_scheduler_images/CyclicLR.png
2025-08-14T21:17:32.0568643Z     
2025-08-14T21:17:32.0568947Z         .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186
2025-08-14T21:17:32.0569110Z         .. _bckenstler/CLR: https://github.com/bckenstler/CLR
2025-08-14T21:17:32.0569204Z         
2025-08-14T21:17:32.0569455Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0569536Z     
2025-08-14T21:17:32.0569645Z       warnings.warn(msg)
2025-08-14T21:17:32.0569723Z     
2025-08-14T21:17:32.0569920Z --- Parse Warning: 123 / 146 ---
2025-08-14T21:17:32.0570924Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1722.
2025-08-14T21:17:32.0571187Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0571455Z     Set the learning rate of each parameter group using a cosine annealing schedule.
2025-08-14T21:17:32.0571535Z     
2025-08-14T21:17:32.0571715Z         The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}`
2025-08-14T21:17:32.0571962Z         is the number of epochs since the last restart and :math:`T_{i}` is the number
2025-08-14T21:17:32.0572099Z         of epochs between two warm restarts in SGDR:
2025-08-14T21:17:32.0572185Z     
2025-08-14T21:17:32.0572287Z         .. math::
2025-08-14T21:17:32.0572466Z             \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 +
2025-08-14T21:17:32.0572621Z             \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right)
2025-08-14T21:17:32.0572700Z     
2025-08-14T21:17:32.0572867Z         When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`.
2025-08-14T21:17:32.0573065Z         When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`.
2025-08-14T21:17:32.0573146Z     
2025-08-14T21:17:32.0573277Z         It has been proposed in
2025-08-14T21:17:32.0573461Z         `SGDR: Stochastic Gradient Descent with Warm Restarts`_.
2025-08-14T21:17:32.0573542Z     
2025-08-14T21:17:32.0573625Z         Args:
2025-08-14T21:17:32.0573774Z             optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:32.0573933Z             T_0 (int): Number of iterations until the first restart.
2025-08-14T21:17:32.0574233Z             T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1.
2025-08-14T21:17:32.0574419Z             eta_min (float, optional): Minimum learning rate. Default: 0.
2025-08-14T21:17:32.0574628Z             last_epoch (int, optional): The index of the last epoch. Default: -1.
2025-08-14T21:17:32.0574721Z     
2025-08-14T21:17:32.0574887Z         .. _SGDR\: Stochastic Gradient Descent with Warm Restarts:
2025-08-14T21:17:32.0575008Z             https://arxiv.org/abs/1608.03983
2025-08-14T21:17:32.0575101Z     
2025-08-14T21:17:32.0575185Z         Example:
2025-08-14T21:17:32.0575284Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0575478Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05)
2025-08-14T21:17:32.0575704Z             >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts(
2025-08-14T21:17:32.0575820Z             ...     optimizer, T_0=20
2025-08-14T21:17:32.0575901Z             ... )
2025-08-14T21:17:32.0576074Z             >>> for epoch in range(100):
2025-08-14T21:17:32.0576203Z             >>>     train(...)
2025-08-14T21:17:32.0576295Z             >>>     validate(...)
2025-08-14T21:17:32.0576396Z             >>>     scheduler.step()
2025-08-14T21:17:32.0576487Z     
2025-08-14T21:17:32.0576718Z         .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png
2025-08-14T21:17:32.0576798Z         
2025-08-14T21:17:32.0577064Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0577144Z     
2025-08-14T21:17:32.0577260Z       warnings.warn(msg)
2025-08-14T21:17:32.0577341Z     
2025-08-14T21:17:32.0577533Z --- Parse Warning: 124 / 146 ---
2025-08-14T21:17:32.0578436Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1872.
2025-08-14T21:17:32.0578700Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0579003Z     Sets the learning rate of each parameter group according to the 1cycle learning rate policy.
2025-08-14T21:17:32.0579094Z     
2025-08-14T21:17:32.0579387Z         The 1cycle policy anneals the learning rate from an initial learning rate to some maximum
2025-08-14T21:17:32.0579693Z         learning rate and then from that maximum learning rate to some minimum learning rate much
2025-08-14T21:17:32.0579811Z         lower than the initial learning rate.
2025-08-14T21:17:32.0580036Z         This policy was initially described in the paper `Super-Convergence:
2025-08-14T21:17:32.0580259Z         Very Fast Training of Neural Networks Using Large Learning Rates`_.
2025-08-14T21:17:32.0580336Z     
2025-08-14T21:17:32.0580580Z         The 1cycle learning rate policy changes the learning rate after every batch.
2025-08-14T21:17:32.0580788Z         `step` should be called after a batch has been used for training.
2025-08-14T21:17:32.0580871Z     
2025-08-14T21:17:32.0580995Z         This scheduler is not chainable.
2025-08-14T21:17:32.0581074Z     
2025-08-14T21:17:32.0581313Z         Note also that the total number of steps in the cycle can be determined in one
2025-08-14T21:17:32.0581462Z         of two ways (listed in order of precedence):
2025-08-14T21:17:32.0581540Z     
2025-08-14T21:17:32.0581690Z         #. A value for total_steps is explicitly provided.
2025-08-14T21:17:32.0581884Z         #. A number of epochs (epochs) and a number of steps per epoch
2025-08-14T21:17:32.0582027Z            (steps_per_epoch) are provided.
2025-08-14T21:17:32.0582189Z            In this case, the number of total steps is inferred by
2025-08-14T21:17:32.0582322Z            total_steps = epochs * steps_per_epoch
2025-08-14T21:17:32.0582402Z     
2025-08-14T21:17:32.0582652Z         You must either provide a value for total_steps or provide a value for both
2025-08-14T21:17:32.0582762Z         epochs and steps_per_epoch.
2025-08-14T21:17:32.0582843Z     
2025-08-14T21:17:32.0583160Z         The default behaviour of this scheduler follows the fastai implementation of 1cycle, which
2025-08-14T21:17:32.0583456Z         claims that "unpublished work has shown even better results by using only two phases". To
2025-08-14T21:17:32.0583699Z         mimic the behaviour of the original paper instead, set ``three_phase=True``.
2025-08-14T21:17:32.0583795Z     
2025-08-14T21:17:32.0583878Z         Args:
2025-08-14T21:17:32.0584016Z             optimizer (Optimizer): Wrapped optimizer.
2025-08-14T21:17:32.0584229Z             max_lr (float or list): Upper learning rate boundaries in the cycle
2025-08-14T21:17:32.0584342Z                 for each parameter group.
2025-08-14T21:17:32.0584566Z             total_steps (int): The total number of steps in the cycle. Note that
2025-08-14T21:17:32.0584781Z                 if a value is not provided here, then it must be inferred by providing
2025-08-14T21:17:32.0584938Z                 a value for epochs and steps_per_epoch.
2025-08-14T21:17:32.0585072Z                 Default: None
2025-08-14T21:17:32.0585302Z             epochs (int): The number of epochs to train for. This is used along
2025-08-14T21:17:32.0585545Z                 with steps_per_epoch in order to infer the total number of steps in the cycle
2025-08-14T21:17:32.0585693Z                 if a value for total_steps is not provided.
2025-08-14T21:17:32.0585788Z                 Default: None
2025-08-14T21:17:32.0586022Z             steps_per_epoch (int): The number of steps per epoch to train for. This is
2025-08-14T21:17:32.0586252Z                 used along with epochs in order to infer the total number of steps in the
2025-08-14T21:17:32.0586401Z                 cycle if a value for total_steps is not provided.
2025-08-14T21:17:32.0586503Z                 Default: None
2025-08-14T21:17:32.0586731Z             pct_start (float): The percentage of the cycle (in number of steps) spent
2025-08-14T21:17:32.0586848Z                 increasing the learning rate.
2025-08-14T21:17:32.0586957Z                 Default: 0.3
2025-08-14T21:17:32.0587083Z             anneal_strategy (str): {'cos', 'linear'}
2025-08-14T21:17:32.0587344Z                 Specifies the annealing strategy: "cos" for cosine annealing, "linear" for
2025-08-14T21:17:32.0587442Z                 linear annealing.
2025-08-14T21:17:32.0587536Z                 Default: 'cos'
2025-08-14T21:17:32.0587742Z             cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-08-14T21:17:32.0587929Z                 to learning rate between 'base_momentum' and 'max_momentum'.
2025-08-14T21:17:32.0588024Z                 Default: True
2025-08-14T21:17:32.0588251Z             base_momentum (float or list): Lower momentum boundaries in the cycle
2025-08-14T21:17:32.0588456Z                 for each parameter group. Note that momentum is cycled inversely
2025-08-14T21:17:32.0588632Z                 to learning rate; at the peak of a cycle, momentum is
2025-08-14T21:17:32.0588780Z                 'base_momentum' and learning rate is 'max_lr'.
2025-08-14T21:17:32.0588880Z                 Default: 0.85
2025-08-14T21:17:32.0589104Z             max_momentum (float or list): Upper momentum boundaries in the cycle
2025-08-14T21:17:32.0589236Z                 for each parameter group. Functionally,
2025-08-14T21:17:32.0589428Z                 it defines the cycle amplitude (max_momentum - base_momentum).
2025-08-14T21:17:32.0589568Z                 Note that momentum is cycled inversely
2025-08-14T21:17:32.0589825Z                 to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-08-14T21:17:32.0589955Z                 and learning rate is 'base_lr'
2025-08-14T21:17:32.0590050Z                 Default: 0.95
2025-08-14T21:17:32.0590235Z             div_factor (float): Determines the initial learning rate via
2025-08-14T21:17:32.0590361Z                 initial_lr = max_lr/div_factor
2025-08-14T21:17:32.0590454Z                 Default: 25
2025-08-14T21:17:32.0590663Z             final_div_factor (float): Determines the minimum learning rate via
2025-08-14T21:17:32.0590803Z                 min_lr = initial_lr/final_div_factor
2025-08-14T21:17:32.0590899Z                 Default: 1e4
2025-08-14T21:17:32.0591143Z             three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the
2025-08-14T21:17:32.0591482Z                 learning rate according to 'final_div_factor' instead of modifying the second
2025-08-14T21:17:32.0591723Z                 phase (the first two phases will be symmetrical about the step indicated by
2025-08-14T21:17:32.0591835Z                 'pct_start').
2025-08-14T21:17:32.0592057Z             last_epoch (int): The index of the last batch. This parameter is used when
2025-08-14T21:17:32.0592274Z                 resuming a training job. Since `step()` should be invoked after each
2025-08-14T21:17:32.0592507Z                 batch instead of after each epoch, this number represents the total
2025-08-14T21:17:32.0592765Z                 number of *batches* computed, not the total number of epochs computed.
2025-08-14T21:17:32.0593022Z                 When last_epoch=-1, the schedule is started from the beginning.
2025-08-14T21:17:32.0593119Z                 Default: -1
2025-08-14T21:17:32.0593198Z     
2025-08-14T21:17:32.0593300Z         Example:
2025-08-14T21:17:32.0593401Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0593554Z             >>> data_loader = torch.utils.data.DataLoader(...)
2025-08-14T21:17:32.0593799Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
2025-08-14T21:17:32.0593962Z             >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(
2025-08-14T21:17:32.0594172Z             ...     optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10
2025-08-14T21:17:32.0594270Z             ... )
2025-08-14T21:17:32.0594376Z             >>> for epoch in range(10):
2025-08-14T21:17:32.0594500Z             >>>     for batch in data_loader:
2025-08-14T21:17:32.0594604Z             >>>         train_batch(...)
2025-08-14T21:17:32.0594710Z             >>>         optimizer.step()
2025-08-14T21:17:32.0594821Z             >>>         scheduler.step()
2025-08-14T21:17:32.0594900Z     
2025-08-14T21:17:32.0595067Z         .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png
2025-08-14T21:17:32.0595160Z     
2025-08-14T21:17:32.0595446Z         .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates:
2025-08-14T21:17:32.0595567Z             https://arxiv.org/abs/1708.07120
2025-08-14T21:17:32.0595661Z         
2025-08-14T21:17:32.0595913Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0596002Z     
2025-08-14T21:17:32.0596098Z       warnings.warn(msg)
2025-08-14T21:17:32.0596176Z     
2025-08-14T21:17:32.0596398Z --- Parse Warning: 125 / 146 ---
2025-08-14T21:17:32.0597333Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867.
2025-08-14T21:17:32.0597595Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0597711Z     Load the optimizer state.
2025-08-14T21:17:32.0597789Z     
2025-08-14T21:17:32.0597870Z             Args:
2025-08-14T21:17:32.0598077Z                 state_dict (dict): optimizer state. Should be an object returned
2025-08-14T21:17:32.0598199Z                     from a call to :meth:`state_dict`.
2025-08-14T21:17:32.0598326Z     
2025-08-14T21:17:32.0598419Z             .. warning::
2025-08-14T21:17:32.0598753Z                 Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`,
2025-08-14T21:17:32.0598975Z                 as calling it beforehand will overwrite the loaded learning rates.
2025-08-14T21:17:32.0599054Z     
2025-08-14T21:17:32.0599144Z             .. note::
2025-08-14T21:17:32.0599445Z                 The names of the parameters (if they exist under the "param_names" key of each param group
2025-08-14T21:17:32.0599622Z                 in :meth:`state_dict`) will not affect the loading process.
2025-08-14T21:17:32.0599958Z                 To use the parameters' names for custom cases (such as when the parameters in the loaded state dict
2025-08-14T21:17:32.0600112Z                 differ from those initialized in the optimizer),
2025-08-14T21:17:32.0600414Z                 a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict
2025-08-14T21:17:32.0600525Z                 accordingly.
2025-08-14T21:17:32.0600814Z                 If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override
2025-08-14T21:17:32.0601133Z                 the current names, if present, in the optimizer state. If they do not exist in loaded state dict,
2025-08-14T21:17:32.0601341Z                 the optimizer ``param_names`` will remain unchanged.
2025-08-14T21:17:32.0601444Z     
2025-08-14T21:17:32.0601573Z             Example:
2025-08-14T21:17:32.0601675Z                 >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0601795Z                 >>> model = torch.nn.Linear(10, 10)
2025-08-14T21:17:32.0601973Z                 >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4)
2025-08-14T21:17:32.0602131Z                 >>> scheduler1 = torch.optim.lr_scheduler.LinearLR(
2025-08-14T21:17:32.0602222Z                 ...     optim,
2025-08-14T21:17:32.0602336Z                 ...     start_factor=0.1,
2025-08-14T21:17:32.0602435Z                 ...     end_factor=1,
2025-08-14T21:17:32.0602531Z                 ...     total_iters=20,
2025-08-14T21:17:32.0602628Z                 ... )
2025-08-14T21:17:32.0602816Z                 >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR(
2025-08-14T21:17:32.0602919Z                 ...     optim,
2025-08-14T21:17:32.0603010Z                 ...     T_max=80,
2025-08-14T21:17:32.0603111Z                 ...     eta_min=3e-5,
2025-08-14T21:17:32.0603208Z                 ... )
2025-08-14T21:17:32.0603353Z                 >>> lr = torch.optim.lr_scheduler.SequentialLR(
2025-08-14T21:17:32.0603444Z                 ...     optim,
2025-08-14T21:17:32.0603587Z                 ...     schedulers=[scheduler1, scheduler2],
2025-08-14T21:17:32.0603688Z                 ...     milestones=[20],
2025-08-14T21:17:32.0603771Z                 ... )
2025-08-14T21:17:32.0603931Z                 >>> lr.load_state_dict(torch.load("./save_seq.pt"))
2025-08-14T21:17:32.0604135Z                 >>> # now load the optimizer checkpoint after loading the LRScheduler
2025-08-14T21:17:32.0604313Z                 >>> optim.load_state_dict(torch.load("./save_optim.pt"))
2025-08-14T21:17:32.0604393Z     
2025-08-14T21:17:32.0604476Z             
2025-08-14T21:17:32.0604739Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0604818Z     
2025-08-14T21:17:32.0604917Z       warnings.warn(msg)
2025-08-14T21:17:32.0605007Z     
2025-08-14T21:17:32.0605199Z --- Parse Warning: 126 / 146 ---
2025-08-14T21:17:32.0606083Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120.
2025-08-14T21:17:32.0606356Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0606764Z     Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA).
2025-08-14T21:17:32.0606861Z     
2025-08-14T21:17:32.0607104Z         Stochastic Weight Averaging was proposed in `Averaging Weights Leads to
2025-08-14T21:17:32.0607322Z         Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii
2025-08-14T21:17:32.0607557Z         Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson
2025-08-14T21:17:32.0607647Z         (UAI 2018).
2025-08-14T21:17:32.0607724Z     
2025-08-14T21:17:32.0607954Z         Exponential Moving Average is a variation of `Polyak averaging`_,
2025-08-14T21:17:32.0608193Z         but using exponential weights instead of equal weights across iterations.
2025-08-14T21:17:32.0608284Z     
2025-08-14T21:17:32.0608520Z         AveragedModel class creates a copy of the provided module :attr:`model`
2025-08-14T21:17:32.0608743Z         on the device :attr:`device` and allows to compute running averages of the
2025-08-14T21:17:32.0608868Z         parameters of the :attr:`model`.
2025-08-14T21:17:32.0608948Z     
2025-08-14T21:17:32.0609220Z         Args:
2025-08-14T21:17:32.0609393Z             model (torch.nn.Module): model to use with SWA/EMA
2025-08-14T21:17:32.0609628Z             device (torch.device, optional): if provided, the averaged model will be
2025-08-14T21:17:32.0609740Z                 stored on the :attr:`device`
2025-08-14T21:17:32.0610048Z             avg_fn (function, optional): the averaging function used to update
2025-08-14T21:17:32.0610328Z                 parameters; the function must take in the current value of the
2025-08-14T21:17:32.0610600Z                 :class:`AveragedModel` parameter, the current value of :attr:`model`
2025-08-14T21:17:32.0610794Z                 parameter, and the number of models already averaged; if None,
2025-08-14T21:17:32.0610953Z                 an equally weighted average is used (default: None)
2025-08-14T21:17:32.0611198Z             multi_avg_fn (function, optional): the averaging function used to update
2025-08-14T21:17:32.0611439Z                 parameters inplace; the function must take in the current values of the
2025-08-14T21:17:32.0611718Z                 :class:`AveragedModel` parameters as a list, the current values of :attr:`model`
2025-08-14T21:17:32.0611944Z                 parameters as a list, and the number of models already averaged; if None,
2025-08-14T21:17:32.0612105Z                 an equally weighted average is used (default: None)
2025-08-14T21:17:32.0612323Z             use_buffers (bool): if ``True``, it will compute running averages for
2025-08-14T21:17:32.0612548Z                 both the parameters and the buffers of the model. (default: ``False``)
2025-08-14T21:17:32.0612629Z     
2025-08-14T21:17:32.0612728Z         Example:
2025-08-14T21:17:32.0612859Z             >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:32.0612996Z             >>> loader, optimizer, model, loss_fn = ...
2025-08-14T21:17:32.0613167Z             >>> swa_model = torch.optim.swa_utils.AveragedModel(model)
2025-08-14T21:17:32.0613389Z             >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer,
2025-08-14T21:17:32.0613512Z             >>>                                     T_max=300)
2025-08-14T21:17:32.0613606Z             >>> swa_start = 160
2025-08-14T21:17:32.0613747Z             >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05)
2025-08-14T21:17:32.0613858Z             >>> for i in range(300):
2025-08-14T21:17:32.0613977Z             >>>      for input, target in loader:
2025-08-14T21:17:32.0614089Z             >>>          optimizer.zero_grad()
2025-08-14T21:17:32.0614234Z             >>>          loss_fn(model(input), target).backward()
2025-08-14T21:17:32.0614338Z             >>>          optimizer.step()
2025-08-14T21:17:32.0614450Z             >>>      if i > swa_start:
2025-08-14T21:17:32.0614578Z             >>>          swa_model.update_parameters(model)
2025-08-14T21:17:32.0614689Z             >>>          swa_scheduler.step()
2025-08-14T21:17:32.0614787Z             >>>      else:
2025-08-14T21:17:32.0614927Z             >>>          scheduler.step()
2025-08-14T21:17:32.0615011Z             >>>
2025-08-14T21:17:32.0615176Z             >>> # Update bn statistics for the swa_model at the end
2025-08-14T21:17:32.0615337Z             >>> torch.optim.swa_utils.update_bn(loader, swa_model)
2025-08-14T21:17:32.0615415Z     
2025-08-14T21:17:32.0615728Z         You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters.
2025-08-14T21:17:32.0615926Z         If no averaging function is provided, the default is to compute
2025-08-14T21:17:32.0616087Z         equally-weighted average of the weights (SWA).
2025-08-14T21:17:32.0616170Z     
2025-08-14T21:17:32.0616253Z         Example:
2025-08-14T21:17:32.0616395Z             >>> # xdoctest: +SKIP("undefined variables")
2025-08-14T21:17:32.0616600Z             >>> # Compute exponential moving averages of the weights and buffers
2025-08-14T21:17:32.0616769Z             >>> ema_model = torch.optim.swa_utils.AveragedModel(model,
2025-08-14T21:17:32.0617002Z             >>>             torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True)
2025-08-14T21:17:32.0617081Z     
2025-08-14T21:17:32.0617182Z         .. note::
2025-08-14T21:17:32.0617401Z             When using SWA/EMA with models containing Batch Normalization you may
2025-08-14T21:17:32.0617664Z             need to update the activation statistics for Batch Normalization.
2025-08-14T21:17:32.0617934Z             This can be done either by using the :meth:`torch.optim.swa_utils.update_bn`
2025-08-14T21:17:32.0618187Z             or by setting :attr:`use_buffers` to `True`. The first approach updates the
2025-08-14T21:17:32.0618423Z             statistics in a post-training step by passing data through the model. The
2025-08-14T21:17:32.0618670Z             second does it during the parameter update phase by averaging all buffers.
2025-08-14T21:17:32.0618913Z             Empirical evidence has shown that updating the statistics in normalization
2025-08-14T21:17:32.0619150Z             layers increases accuracy, but you may wish to empirically test which
2025-08-14T21:17:32.0619304Z             approach yields the best results in your problem.
2025-08-14T21:17:32.0619385Z     
2025-08-14T21:17:32.0619485Z         .. note::
2025-08-14T21:17:32.0619735Z             :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model.
2025-08-14T21:17:32.0619819Z     
2025-08-14T21:17:32.0619914Z         .. note::
2025-08-14T21:17:32.0620113Z             When :meth:`update_parameters` is called for the first time (i.e.
2025-08-14T21:17:32.0620309Z             :attr:`n_averaged` is `0`) the parameters of `model` are copied
2025-08-14T21:17:32.0620522Z             to the parameters of :class:`AveragedModel`. For every subsequent
2025-08-14T21:17:32.0620707Z             call of :meth:`update_parameters` the function `avg_fn` is used
2025-08-14T21:17:32.0620830Z             to update the parameters.
2025-08-14T21:17:32.0620911Z     
2025-08-14T21:17:32.0621135Z         .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-08-14T21:17:32.0621272Z             https://arxiv.org/abs/1803.05407
2025-08-14T21:17:32.0621507Z         .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should
2025-08-14T21:17:32.0621594Z             Average:
2025-08-14T21:17:32.0621727Z             https://arxiv.org/abs/1806.05594
2025-08-14T21:17:32.0621931Z         .. _SWALP: Stochastic Weight Averaging in Low-Precision Training:
2025-08-14T21:17:32.0622061Z             https://arxiv.org/abs/1904.11943
2025-08-14T21:17:32.0622284Z         .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That
2025-08-14T21:17:32.0622385Z             Generalizes Well:
2025-08-14T21:17:32.0622516Z             https://arxiv.org/abs/2001.02312
2025-08-14T21:17:32.0622616Z         .. _Polyak averaging:
2025-08-14T21:17:32.0622786Z             https://paperswithcode.com/method/polyak-averaging
2025-08-14T21:17:32.0622885Z         
2025-08-14T21:17:32.0623166Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0623248Z     
2025-08-14T21:17:32.0623362Z       warnings.warn(msg)
2025-08-14T21:17:32.0623444Z     
2025-08-14T21:17:32.0623657Z --- Parse Warning: 127 / 146 ---
2025-08-14T21:17:32.0624520Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375.
2025-08-14T21:17:32.0624790Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0625020Z     Anneals the learning rate in each parameter group to a fixed value.
2025-08-14T21:17:32.0625102Z     
2025-08-14T21:17:32.0625334Z         This learning rate scheduler is meant to be used with Stochastic Weight
2025-08-14T21:17:32.0625561Z         Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`).
2025-08-14T21:17:32.0625643Z     
2025-08-14T21:17:32.0625740Z         Args:
2025-08-14T21:17:32.0625912Z             optimizer (torch.optim.Optimizer): wrapped optimizer
2025-08-14T21:17:32.0626117Z             swa_lrs (float or list): the learning rate value for all param groups
2025-08-14T21:17:32.0626263Z                 together or separately for each group.
2025-08-14T21:17:32.0626495Z             annealing_epochs (int): number of epochs in the annealing phase
2025-08-14T21:17:32.0626611Z                 (default: 10)
2025-08-14T21:17:32.0626858Z             annealing_strategy (str): "cos" or "linear"; specifies the annealing
2025-08-14T21:17:32.0627065Z                 strategy: "cos" for cosine annealing, "linear" for linear annealing
2025-08-14T21:17:32.0627163Z                 (default: "cos")
2025-08-14T21:17:32.0627359Z             last_epoch (int): the index of the last epoch (default: -1)
2025-08-14T21:17:32.0627440Z     
2025-08-14T21:17:32.0627631Z         The :class:`SWALR` scheduler can be used together with other
2025-08-14T21:17:32.0627849Z         schedulers to switch to a constant learning rate late in the training
2025-08-14T21:17:32.0627952Z         as in the example below.
2025-08-14T21:17:32.0628041Z     
2025-08-14T21:17:32.0628124Z         Example:
2025-08-14T21:17:32.0628252Z             >>> # xdoctest: +SKIP("Undefined variables")
2025-08-14T21:17:32.0628377Z             >>> loader, optimizer, model = ...
2025-08-14T21:17:32.0628493Z             >>> lr_lambda = lambda epoch: 0.9
2025-08-14T21:17:32.0628715Z             >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer,
2025-08-14T21:17:32.0628836Z             >>>        lr_lambda=lr_lambda)
2025-08-14T21:17:32.0629005Z             >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer,
2025-08-14T21:17:32.0629192Z             >>>        anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05)
2025-08-14T21:17:32.0629286Z             >>> swa_start = 160
2025-08-14T21:17:32.0629382Z             >>> for i in range(300):
2025-08-14T21:17:32.0629509Z             >>>      for input, target in loader:
2025-08-14T21:17:32.0629621Z             >>>          optimizer.zero_grad()
2025-08-14T21:17:32.0629754Z             >>>          loss_fn(model(input), target).backward()
2025-08-14T21:17:32.0629870Z             >>>          optimizer.step()
2025-08-14T21:17:32.0629967Z             >>>      if i > swa_start:
2025-08-14T21:17:32.0630087Z             >>>          swa_scheduler.step()
2025-08-14T21:17:32.0630178Z             >>>      else:
2025-08-14T21:17:32.0630284Z             >>>          scheduler.step()
2025-08-14T21:17:32.0630374Z     
2025-08-14T21:17:32.0630595Z         .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-08-14T21:17:32.0630715Z             https://arxiv.org/abs/1803.05407
2025-08-14T21:17:32.0630811Z         
2025-08-14T21:17:32.0631061Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0631141Z     
2025-08-14T21:17:32.0631252Z       warnings.warn(msg)
2025-08-14T21:17:32.0631357Z     
2025-08-14T21:17:32.0631657Z --- Parse Warning: 128 / 146 ---
2025-08-14T21:17:32.0632574Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331.
2025-08-14T21:17:32.0632839Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0633007Z     Asserts that ``actual`` and ``expected`` are close.
2025-08-14T21:17:32.0633087Z     
2025-08-14T21:17:32.0633453Z         If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if
2025-08-14T21:17:32.0633542Z     
2025-08-14T21:17:32.0633632Z         .. math::
2025-08-14T21:17:32.0633712Z     
2025-08-14T21:17:32.0634084Z             \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert
2025-08-14T21:17:32.0634167Z     
2025-08-14T21:17:32.0634518Z         Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are
2025-08-14T21:17:32.0634724Z         only considered equal to each other if ``equal_nan`` is ``True``.
2025-08-14T21:17:32.0634802Z     
2025-08-14T21:17:32.0635047Z         In addition, they are only considered close if they have the same
2025-08-14T21:17:32.0635149Z     
2025-08-14T21:17:32.0635342Z         - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``),
2025-08-14T21:17:32.0635522Z         - ``dtype`` (if ``check_dtype`` is ``True``),
2025-08-14T21:17:32.0635665Z         - ``layout`` (if ``check_layout`` is ``True``), and
2025-08-14T21:17:32.0635799Z         - stride (if ``check_stride`` is ``True``).
2025-08-14T21:17:32.0635879Z     
2025-08-14T21:17:32.0636177Z         If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed.
2025-08-14T21:17:32.0636270Z     
2025-08-14T21:17:32.0636628Z         If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are
2025-08-14T21:17:32.0637002Z         checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR,
2025-08-14T21:17:32.0637241Z         or ``ccol_indices``  and ``row_indices`` for CSC and BSC layouts, respectively,
2025-08-14T21:17:32.0637627Z         are always checked for equality whereas the values are checked for closeness according to the definition above.
2025-08-14T21:17:32.0637725Z     
2025-08-14T21:17:32.0638003Z         If ``actual`` and ``expected`` are quantized, they are considered close if they have the same
2025-08-14T21:17:32.0638355Z         :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the
2025-08-14T21:17:32.0638468Z         definition above.
2025-08-14T21:17:32.0638550Z     
2025-08-14T21:17:32.0638853Z         ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which
2025-08-14T21:17:32.0639235Z         :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types
2025-08-14T21:17:32.0639595Z         have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s
2025-08-14T21:17:32.0639986Z         or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all
2025-08-14T21:17:32.0640218Z         their elements are considered close according to the above definition.
2025-08-14T21:17:32.0640297Z     
2025-08-14T21:17:32.0640397Z         .. note::
2025-08-14T21:17:32.0640474Z     
2025-08-14T21:17:32.0640801Z             Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e.
2025-08-14T21:17:32.0641164Z             :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus,
2025-08-14T21:17:32.0641444Z             Python scalars of different types can be checked, but require ``check_dtype=False``.
2025-08-14T21:17:32.0641537Z     
2025-08-14T21:17:32.0641617Z         Args:
2025-08-14T21:17:32.0641726Z             actual (Any): Actual input.
2025-08-14T21:17:32.0641851Z             expected (Any): Expected input.
2025-08-14T21:17:32.0642209Z             allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types
2025-08-14T21:17:32.0642370Z                 are allowed. Otherwise type equality is required.
2025-08-14T21:17:32.0642747Z             rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default
2025-08-14T21:17:32.0643009Z                 values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-08-14T21:17:32.0643382Z             atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default
2025-08-14T21:17:32.0643639Z                 values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-08-14T21:17:32.0643884Z             equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal.
2025-08-14T21:17:32.0644209Z             check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same
2025-08-14T21:17:32.0644482Z                 :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different
2025-08-14T21:17:32.0644754Z                 :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared.
2025-08-14T21:17:32.0645098Z             check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this
2025-08-14T21:17:32.0645439Z                 check is disabled, tensors with different ``dtype``'s are promoted  to a common ``dtype`` (according to
2025-08-14T21:17:32.0645615Z                 :func:`torch.promote_types`) before being compared.
2025-08-14T21:17:32.0645970Z             check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this
2025-08-14T21:17:32.0646315Z                 check is disabled, tensors with different ``layout``'s are converted to strided tensors before being
2025-08-14T21:17:32.0646406Z                 compared.
2025-08-14T21:17:32.0646766Z             check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride.
2025-08-14T21:17:32.0647131Z             msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during
2025-08-14T21:17:32.0647486Z                 the comparison. Can also passed as callable in which case it will be called with the generated message and
2025-08-14T21:17:32.0647599Z                 should return the new message.
2025-08-14T21:17:32.0647689Z     
2025-08-14T21:17:32.0647774Z         Raises:
2025-08-14T21:17:32.0648018Z             ValueError: If no :class:`torch.Tensor` can be constructed from an input.
2025-08-14T21:17:32.0648182Z             ValueError: If only ``rtol`` or ``atol`` is specified.
2025-08-14T21:17:32.0648507Z             AssertionError: If corresponding inputs are not Python scalars and are not directly related.
2025-08-14T21:17:32.0648879Z             AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have
2025-08-14T21:17:32.0648982Z                 different types.
2025-08-14T21:17:32.0649342Z             AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match.
2025-08-14T21:17:32.0649714Z             AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match.
2025-08-14T21:17:32.0650031Z             AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`.
2025-08-14T21:17:32.0650367Z             AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same
2025-08-14T21:17:32.0650486Z                 :attr:`~torch.Tensor.layout`.
2025-08-14T21:17:32.0650706Z             AssertionError: If only one of corresponding tensors is quantized.
2025-08-14T21:17:32.0651103Z             AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s.
2025-08-14T21:17:32.0651397Z             AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same
2025-08-14T21:17:32.0651530Z                 :attr:`~torch.Tensor.device`.
2025-08-14T21:17:32.0651863Z             AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``.
2025-08-14T21:17:32.0652219Z             AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride.
2025-08-14T21:17:32.0652594Z             AssertionError: If the values of corresponding tensors are not close according to the definition above.
2025-08-14T21:17:32.0652676Z     
2025-08-14T21:17:32.0653037Z         The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching
2025-08-14T21:17:32.0653199Z         ``dtype``'s, the maximum of both tolerances is used.
2025-08-14T21:17:32.0653280Z     
2025-08-14T21:17:32.0653452Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0653603Z         | ``dtype``                 | ``rtol``   | ``atol`` |
2025-08-14T21:17:32.0653736Z         +===========================+============+==========+
2025-08-14T21:17:32.0653885Z         | :attr:`~torch.float16`    | ``1e-3``   | ``1e-5`` |
2025-08-14T21:17:32.0654010Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0654145Z         | :attr:`~torch.bfloat16`   | ``1.6e-2`` | ``1e-5`` |
2025-08-14T21:17:32.0654279Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0654417Z         | :attr:`~torch.float32`    | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0654549Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0654682Z         | :attr:`~torch.float64`    | ``1e-7``   | ``1e-7`` |
2025-08-14T21:17:32.0654802Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0654947Z         | :attr:`~torch.complex32`  | ``1e-3``   | ``1e-5`` |
2025-08-14T21:17:32.0655069Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0655206Z         | :attr:`~torch.complex64`  | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0655336Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0655471Z         | :attr:`~torch.complex128` | ``1e-7``   | ``1e-7`` |
2025-08-14T21:17:32.0655605Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0655735Z         | :attr:`~torch.quint8`     | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0655856Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0655999Z         | :attr:`~torch.quint2x4`   | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0656118Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0656251Z         | :attr:`~torch.quint4x2`   | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0656381Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0656513Z         | :attr:`~torch.qint8`      | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0656651Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0656781Z         | :attr:`~torch.qint32`     | ``1.3e-6`` | ``1e-5`` |
2025-08-14T21:17:32.0656902Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0657035Z         | other                     | ``0.0``    | ``0.0``  |
2025-08-14T21:17:32.0657156Z         +---------------------------+------------+----------+
2025-08-14T21:17:32.0657239Z     
2025-08-14T21:17:32.0657341Z         .. note::
2025-08-14T21:17:32.0657452Z     
2025-08-14T21:17:32.0657835Z             :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged
2025-08-14T21:17:32.0658199Z             to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might
2025-08-14T21:17:32.0658461Z             define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default:
2025-08-14T21:17:32.0658558Z     
2025-08-14T21:17:32.0658660Z             >>> import functools
2025-08-14T21:17:32.0658918Z             >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0)
2025-08-14T21:17:32.0659040Z             >>> assert_equal(1e-9, 1e-10)
2025-08-14T21:17:32.0659158Z             Traceback (most recent call last):
2025-08-14T21:17:32.0659242Z             ...
2025-08-14T21:17:32.0659384Z             AssertionError: Scalars are not equal!
2025-08-14T21:17:32.0659474Z             <BLANKLINE>
2025-08-14T21:17:32.0659600Z             Expected 1e-10 but got 1e-09.
2025-08-14T21:17:32.0659726Z             Absolute difference: 9.000000000000001e-10
2025-08-14T21:17:32.0659833Z             Relative difference: 9.0
2025-08-14T21:17:32.0659931Z     
2025-08-14T21:17:32.0660020Z         Examples:
2025-08-14T21:17:32.0660134Z             >>> # tensor to tensor comparison
2025-08-14T21:17:32.0668554Z             >>> expected = torch.tensor([1e0, 1e-1, 1e-2])
2025-08-14T21:17:32.0668816Z             >>> actual = torch.acos(torch.cos(expected))
2025-08-14T21:17:32.0669010Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0669093Z     
2025-08-14T21:17:32.0669225Z             >>> # scalar to scalar comparison
2025-08-14T21:17:32.0669320Z             >>> import math
2025-08-14T21:17:32.0669430Z             >>> expected = math.sqrt(2.0)
2025-08-14T21:17:32.0669552Z             >>> actual = 2.0 / math.sqrt(2.0)
2025-08-14T21:17:32.0669700Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0669785Z     
2025-08-14T21:17:32.0669925Z             >>> # numpy array to numpy array comparison
2025-08-14T21:17:32.0670030Z             >>> import numpy as np
2025-08-14T21:17:32.0670166Z             >>> expected = np.array([1e0, 1e-1, 1e-2])
2025-08-14T21:17:32.0670291Z             >>> actual = np.arccos(np.cos(expected))
2025-08-14T21:17:32.0670440Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0670536Z     
2025-08-14T21:17:32.0670658Z             >>> # sequence to sequence comparison
2025-08-14T21:17:32.0670761Z             >>> import numpy as np
2025-08-14T21:17:32.0671031Z             >>> # The types of the sequences do not have to match. They only have to have the same
2025-08-14T21:17:32.0671165Z             >>> # length and their elements have to match.
2025-08-14T21:17:32.0671327Z             >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)]
2025-08-14T21:17:32.0671553Z             >>> actual = tuple(expected)
2025-08-14T21:17:32.0671705Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0671803Z     
2025-08-14T21:17:32.0671924Z             >>> # mapping to mapping comparison
2025-08-14T21:17:32.0672050Z             >>> from collections import OrderedDict
2025-08-14T21:17:32.0672169Z             >>> import numpy as np
2025-08-14T21:17:32.0672274Z             >>> foo = torch.tensor(1.0)
2025-08-14T21:17:32.0672367Z             >>> bar = 2.0
2025-08-14T21:17:32.0672483Z             >>> baz = np.array(3.0)
2025-08-14T21:17:32.0672741Z             >>> # The types and a possible ordering of mappings do not have to match. They only
2025-08-14T21:17:32.0672945Z             >>> # have to have the same set of keys and their elements have to match.
2025-08-14T21:17:32.0673164Z             >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)])
2025-08-14T21:17:32.0673300Z             >>> actual = {"baz": baz, "bar": bar, "foo": foo}
2025-08-14T21:17:32.0673460Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0673580Z     
2025-08-14T21:17:32.0673705Z             >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-08-14T21:17:32.0673830Z             >>> actual = expected.clone()
2025-08-14T21:17:32.0673998Z             >>> # By default, directly related instances can be compared
2025-08-14T21:17:32.0674219Z             >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected)
2025-08-14T21:17:32.0674429Z             >>> # This check can be made more strict with allow_subclasses=False
2025-08-14T21:17:32.0674545Z             >>> torch.testing.assert_close(
2025-08-14T21:17:32.0674760Z             ...     torch.nn.Parameter(actual), expected, allow_subclasses=False
2025-08-14T21:17:32.0674847Z             ... )
2025-08-14T21:17:32.0674964Z             Traceback (most recent call last):
2025-08-14T21:17:32.0675064Z             ...
2025-08-14T21:17:32.0675270Z             TypeError: No comparison pair was able to handle inputs of type
2025-08-14T21:17:32.0675486Z             <class 'torch.nn.parameter.Parameter'> and <class 'torch.Tensor'>.
2025-08-14T21:17:32.0675725Z             >>> # If the inputs are not directly related, they are never considered close
2025-08-14T21:17:32.0675899Z             >>> torch.testing.assert_close(actual.numpy(), expected)
2025-08-14T21:17:32.0676027Z             Traceback (most recent call last):
2025-08-14T21:17:32.0676109Z             ...
2025-08-14T21:17:32.0676453Z             TypeError: No comparison pair was able to handle inputs of type <class 'numpy.ndarray'>
2025-08-14T21:17:32.0676597Z             and <class 'torch.Tensor'>.
2025-08-14T21:17:32.0676859Z             >>> # Exceptions to these rules are Python scalars. They can be checked regardless of
2025-08-14T21:17:32.0676978Z             >>> # their type if check_dtype=False.
2025-08-14T21:17:32.0677157Z             >>> torch.testing.assert_close(1.0, 1, check_dtype=False)
2025-08-14T21:17:32.0677237Z     
2025-08-14T21:17:32.0677341Z             >>> # NaN != NaN by default.
2025-08-14T21:17:32.0677479Z             >>> expected = torch.tensor(float("Nan"))
2025-08-14T21:17:32.0677587Z             >>> actual = expected.clone()
2025-08-14T21:17:32.0677745Z             >>> torch.testing.assert_close(actual, expected)
2025-08-14T21:17:32.0677862Z             Traceback (most recent call last):
2025-08-14T21:17:32.0677942Z             ...
2025-08-14T21:17:32.0678082Z             AssertionError: Scalars are not close!
2025-08-14T21:17:32.0678173Z             <BLANKLINE>
2025-08-14T21:17:32.0678280Z             Expected nan but got nan.
2025-08-14T21:17:32.0678436Z             Absolute difference: nan (up to 1e-05 allowed)
2025-08-14T21:17:32.0678581Z             Relative difference: nan (up to 1.3e-06 allowed)
2025-08-14T21:17:32.0678782Z             >>> torch.testing.assert_close(actual, expected, equal_nan=True)
2025-08-14T21:17:32.0678875Z     
2025-08-14T21:17:32.0678999Z             >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-08-14T21:17:32.0679136Z             >>> actual = torch.tensor([1.0, 4.0, 5.0])
2025-08-14T21:17:32.0679279Z             >>> # The default error message can be overwritten.
2025-08-14T21:17:32.0679395Z             >>> torch.testing.assert_close(
2025-08-14T21:17:32.0679590Z             ...     actual, expected, msg="Argh, the tensors are not close!"
2025-08-14T21:17:32.0679676Z             ... )
2025-08-14T21:17:32.0679793Z             Traceback (most recent call last):
2025-08-14T21:17:32.0679894Z             ...
2025-08-14T21:17:32.0680046Z             AssertionError: Argh, the tensors are not close!
2025-08-14T21:17:32.0680268Z             >>> # If msg is a callable, it can be used to augment the generated message with
2025-08-14T21:17:32.0680384Z             >>> # extra information
2025-08-14T21:17:32.0680498Z             >>> torch.testing.assert_close(
2025-08-14T21:17:32.0680710Z             ...     actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter"
2025-08-14T21:17:32.0680793Z             ... )
2025-08-14T21:17:32.0680937Z             Traceback (most recent call last):
2025-08-14T21:17:32.0681033Z             ...
2025-08-14T21:17:32.0681137Z             AssertionError: Header
2025-08-14T21:17:32.0681228Z             <BLANKLINE>
2025-08-14T21:17:32.0681347Z             Tensor-likes are not close!
2025-08-14T21:17:32.0681436Z             <BLANKLINE>
2025-08-14T21:17:32.0681548Z             Mismatched elements: 2 / 3 (66.7%)
2025-08-14T21:17:32.0681785Z             Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed)
2025-08-14T21:17:32.0682018Z             Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed)
2025-08-14T21:17:32.0682119Z             <BLANKLINE>
2025-08-14T21:17:32.0682203Z             Footer
2025-08-14T21:17:32.0682286Z         
2025-08-14T21:17:32.0682550Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0682631Z     
2025-08-14T21:17:32.0682728Z       warnings.warn(msg)
2025-08-14T21:17:32.0682821Z     
2025-08-14T21:17:32.0683080Z --- Parse Warning: 129 / 146 ---
2025-08-14T21:17:32.0684002Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134.
2025-08-14T21:17:32.0684280Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0684479Z     Register a container-like type as pytree node.
2025-08-14T21:17:32.0684600Z     
2025-08-14T21:17:32.0684685Z         Args:
2025-08-14T21:17:32.0684870Z             cls (type): A Python type to treat as an internal pytree node.
2025-08-14T21:17:32.0685154Z             flatten_fn (callable): A function to be used during flattening, taking an instance of
2025-08-14T21:17:32.0685401Z                 ``cls`` and returning a pair, with (1) an iterable for the children to be flattened
2025-08-14T21:17:32.0685693Z                 recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be
2025-08-14T21:17:32.0685825Z                 passed to the ``unflatten_fn``.
2025-08-14T21:17:32.0686102Z             unflatten_fn (callable): A function taking two arguments: the auxiliary data that was
2025-08-14T21:17:32.0686378Z                 returned by ``flatten_fn`` and stored in the treespec, and the unflattened children.
2025-08-14T21:17:32.0686537Z                 The function should return an instance of ``cls``.
2025-08-14T21:17:32.0686804Z             serialized_type_name (str, optional): A keyword argument used to specify the fully
2025-08-14T21:17:32.0686984Z                 qualified name used when serializing the tree spec.
2025-08-14T21:17:32.0687290Z             to_dumpable_context (callable, optional): An optional keyword argument to custom specify how
2025-08-14T21:17:32.0687580Z                 to convert the context of the pytree to a custom json dumpable representation. This is
2025-08-14T21:17:32.0687857Z                 used for json serialization, which is being used in :mod:`torch.export` right now.
2025-08-14T21:17:32.0688159Z             from_dumpable_context (callable, optional): An optional keyword argument to custom specify
2025-08-14T21:17:32.0688438Z                 how to convert the custom json dumpable representation of the context back to the
2025-08-14T21:17:32.0688699Z                 original context. This is used for json deserialization, which is being used in
2025-08-14T21:17:32.0688818Z                 :mod:`torch.export` right now.
2025-08-14T21:17:32.0688913Z     
2025-08-14T21:17:32.0689012Z         Example::
2025-08-14T21:17:32.0689104Z     
2025-08-14T21:17:32.0689207Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0689355Z             >>> # Registry a Python type with lambda functions
2025-08-14T21:17:32.0689473Z             >>> register_pytree_node(
2025-08-14T21:17:32.0689563Z             ...     set,
2025-08-14T21:17:32.0689688Z             ...     lambda s: (sorted(s), None, None),
2025-08-14T21:17:32.0689854Z             ...     lambda children, _: set(children),
2025-08-14T21:17:32.0689937Z             ... )
2025-08-14T21:17:32.0690025Z         
2025-08-14T21:17:32.0690292Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0690371Z     
2025-08-14T21:17:32.0690470Z       warnings.warn(msg)
2025-08-14T21:17:32.0690563Z     
2025-08-14T21:17:32.0690761Z --- Parse Warning: 130 / 146 ---
2025-08-14T21:17:32.0691751Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218.
2025-08-14T21:17:32.0692014Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0692096Z     
2025-08-14T21:17:32.0692326Z     Context passed to policy function during selective checkpointing.
2025-08-14T21:17:32.0692406Z     
2025-08-14T21:17:32.0692632Z     This class is used to pass relevant metadata to the policy function during
2025-08-14T21:17:32.0692911Z     selective checkpointing. The metadata includes whether the current invocation
2025-08-14T21:17:32.0693071Z     of the policy function is during recomputation or not.
2025-08-14T21:17:32.0693170Z     
2025-08-14T21:17:32.0693255Z     Example:
2025-08-14T21:17:32.0693383Z         >>> # xdoctest: +SKIP(stub)
2025-08-14T21:17:32.0693504Z         >>>
2025-08-14T21:17:32.0693632Z         >>> def policy_fn(ctx, op, *args, **kwargs):
2025-08-14T21:17:32.0693779Z         >>>    print(ctx.is_recompute)
2025-08-14T21:17:32.0693873Z         >>>
2025-08-14T21:17:32.0694145Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-08-14T21:17:32.0694226Z         >>>
2025-08-14T21:17:32.0694380Z         >>> out = torch.utils.checkpoint.checkpoint(
2025-08-14T21:17:32.0694471Z         >>>     fn, x, y,
2025-08-14T21:17:32.0694586Z         >>>     use_reentrant=False,
2025-08-14T21:17:32.0694694Z         >>>     context_fn=context_fn,
2025-08-14T21:17:32.0694776Z         >>> )
2025-08-14T21:17:32.0694873Z     
2025-08-14T21:17:32.0695124Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0695204Z     
2025-08-14T21:17:32.0695323Z       warnings.warn(msg)
2025-08-14T21:17:32.0695402Z     
2025-08-14T21:17:32.0695594Z --- Parse Warning: 131 / 146 ---
2025-08-14T21:17:32.0696601Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358.
2025-08-14T21:17:32.0696866Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0696959Z     
2025-08-14T21:17:32.0697198Z     Helper to avoid recomputing certain ops during activation checkpointing.
2025-08-14T21:17:32.0697277Z     
2025-08-14T21:17:32.0697507Z     Use this with `torch.utils.checkpoint.checkpoint` to control which
2025-08-14T21:17:32.0697669Z     operations are recomputed during the backward pass.
2025-08-14T21:17:32.0697749Z     
2025-08-14T21:17:32.0697845Z     Args:
2025-08-14T21:17:32.0697967Z         policy_fn_or_list (Callable or List):
2025-08-14T21:17:32.0698135Z           - If a policy function is provided, it should accept a
2025-08-14T21:17:32.0698394Z             :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and
2025-08-14T21:17:32.0698602Z             kwargs to the op, and return a :class:`CheckpointPolicy` enum value
2025-08-14T21:17:32.0698858Z             indicating whether the execution of the op should be recomputed or not.
2025-08-14T21:17:32.0699058Z           - If a list of operations is provided, it is equivalent to a policy
2025-08-14T21:17:32.0699244Z             returning `CheckpointPolicy.MUST_SAVE` for the specified
2025-08-14T21:17:32.0699500Z             operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other
2025-08-14T21:17:32.0699595Z             operations.
2025-08-14T21:17:32.0699809Z         allow_cache_entry_mutation (bool, optional): By default, an error is
2025-08-14T21:17:32.0700034Z             raised if any tensors cached by selective activation checkpoint are
2025-08-14T21:17:32.0700244Z             mutated in order to ensure correctness. If set to `True`, this check
2025-08-14T21:17:32.0700355Z             is disabled.
2025-08-14T21:17:32.0700441Z     Returns:
2025-08-14T21:17:32.0700554Z         A tuple of two context managers.
2025-08-14T21:17:32.0700647Z     
2025-08-14T21:17:32.0700734Z     Example:
2025-08-14T21:17:32.0700842Z         >>> # xdoctest: +REQUIRES(LINUX)
2025-08-14T21:17:32.0700953Z         >>> import functools
2025-08-14T21:17:32.0701035Z         >>>
2025-08-14T21:17:32.0701161Z         >>> x = torch.rand(10, 10, requires_grad=True)
2025-08-14T21:17:32.0701298Z         >>> y = torch.rand(10, 10, requires_grad=True)
2025-08-14T21:17:32.0701379Z         >>>
2025-08-14T21:17:32.0701474Z         >>> ops_to_save = [
2025-08-14T21:17:32.0701601Z         >>>    torch.ops.aten.mm.default,
2025-08-14T21:17:32.0701681Z         >>> ]
2025-08-14T21:17:32.0701776Z         >>>
2025-08-14T21:17:32.0701903Z         >>> def policy_fn(ctx, op, *args, **kwargs):
2025-08-14T21:17:32.0702004Z         >>>    if op in ops_to_save:
2025-08-14T21:17:32.0702181Z         >>>        return CheckpointPolicy.MUST_SAVE
2025-08-14T21:17:32.0702294Z         >>>    else:
2025-08-14T21:17:32.0702462Z         >>>        return CheckpointPolicy.PREFER_RECOMPUTE
2025-08-14T21:17:32.0702556Z         >>>
2025-08-14T21:17:32.0702829Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-08-14T21:17:32.0702909Z         >>>
2025-08-14T21:17:32.0703021Z         >>> # or equivalently
2025-08-14T21:17:32.0703295Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save)
2025-08-14T21:17:32.0703390Z         >>>
2025-08-14T21:17:32.0703485Z         >>> def fn(x, y):
2025-08-14T21:17:32.0703686Z         >>>     return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y
2025-08-14T21:17:32.0703782Z         >>>
2025-08-14T21:17:32.0703923Z         >>> out = torch.utils.checkpoint.checkpoint(
2025-08-14T21:17:32.0704016Z         >>>     fn, x, y,
2025-08-14T21:17:32.0704133Z         >>>     use_reentrant=False,
2025-08-14T21:17:32.0704241Z         >>>     context_fn=context_fn,
2025-08-14T21:17:32.0704326Z         >>> )
2025-08-14T21:17:32.0704421Z     
2025-08-14T21:17:32.0704671Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0704755Z     
2025-08-14T21:17:32.0704867Z       warnings.warn(msg)
2025-08-14T21:17:32.0704947Z     
2025-08-14T21:17:32.0705153Z --- Parse Warning: 132 / 146 ---
2025-08-14T21:17:32.0706067Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1147.
2025-08-14T21:17:32.0706332Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0706426Z     
2025-08-14T21:17:32.0706571Z     Create a :class:`setuptools.Extension` for C++.
2025-08-14T21:17:32.0706649Z     
2025-08-14T21:17:32.0706906Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:32.0707130Z     bare minimum (but often sufficient) arguments to build a C++ extension.
2025-08-14T21:17:32.0707225Z     
2025-08-14T21:17:32.0707433Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:32.0707580Z     constructor. Full list arguments can be found at
2025-08-14T21:17:32.0707920Z     https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-08-14T21:17:32.0708001Z     
2025-08-14T21:17:32.0708090Z     .. warning::
2025-08-14T21:17:32.0708361Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:32.0708571Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:32.0708766Z         the user's responsibility in their library to not use APIs from
2025-08-14T21:17:32.0709223Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:32.0709447Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:32.0709677Z         example, to give access to custom ops from python, the library should
2025-08-14T21:17:32.0709807Z         register the ops through the dispatcher.
2025-08-14T21:17:32.0709889Z     
2025-08-14T21:17:32.0710127Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:32.0710329Z         as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:32.0710536Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:32.0710766Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:32.0710976Z         safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:32.0711202Z         different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:32.0711308Z         CPython version of choice.
2025-08-14T21:17:32.0711549Z     
2025-08-14T21:17:32.0711698Z     Example:
2025-08-14T21:17:32.0711797Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0711986Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:32.0712115Z         >>> from setuptools import setup
2025-08-14T21:17:32.0712334Z         >>> from torch.utils.cpp_extension import BuildExtension, CppExtension
2025-08-14T21:17:32.0712420Z         >>> setup(
2025-08-14T21:17:32.0712534Z         ...     name='extension',
2025-08-14T21:17:32.0712629Z         ...     ext_modules=[
2025-08-14T21:17:32.0712738Z         ...         CppExtension(
2025-08-14T21:17:32.0712840Z         ...             name='extension',
2025-08-14T21:17:32.0712963Z         ...             sources=['extension.cpp'],
2025-08-14T21:17:32.0713095Z         ...             extra_compile_args=['-g'],
2025-08-14T21:17:32.0713249Z         ...             extra_link_args=['-Wl,--no-as-needed', '-lm'])
2025-08-14T21:17:32.0713334Z         ...     ],
2025-08-14T21:17:32.0713443Z         ...     cmdclass={
2025-08-14T21:17:32.0713557Z         ...         'build_ext': BuildExtension
2025-08-14T21:17:32.0713644Z         ...     })
2025-08-14T21:17:32.0713737Z     
2025-08-14T21:17:32.0713989Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0714080Z     
2025-08-14T21:17:32.0714176Z       warnings.warn(msg)
2025-08-14T21:17:32.0714253Z     
2025-08-14T21:17:32.0714476Z --- Parse Warning: 133 / 146 ---
2025-08-14T21:17:32.0715389Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1217.
2025-08-14T21:17:32.0715653Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0715749Z     
2025-08-14T21:17:32.0715911Z     Create a :class:`setuptools.Extension` for CUDA/C++.
2025-08-14T21:17:32.0715991Z     
2025-08-14T21:17:32.0716250Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:32.0716454Z     bare minimum (but often sufficient) arguments to build a CUDA/C++
2025-08-14T21:17:32.0716696Z     extension. This includes the CUDA include path, library path and runtime
2025-08-14T21:17:32.0716780Z     library.
2025-08-14T21:17:32.0716860Z     
2025-08-14T21:17:32.0717080Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:32.0717229Z     constructor. Full list arguments can be found at
2025-08-14T21:17:32.0717598Z     https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-08-14T21:17:32.0717693Z     
2025-08-14T21:17:32.0717788Z     .. warning::
2025-08-14T21:17:32.0718015Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:32.0718233Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:32.0718432Z         the user's responsibility in their library to not use APIs from
2025-08-14T21:17:32.0718677Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:32.0718893Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:32.0719103Z         example, to give access to custom ops from python, the library should
2025-08-14T21:17:32.0719245Z         register the ops through the dispatcher.
2025-08-14T21:17:32.0719328Z     
2025-08-14T21:17:32.0719548Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:32.0719768Z         as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:32.0719974Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:32.0720200Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:32.0720413Z         safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:32.0720679Z         different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:32.0720824Z         CPython version of choice.
2025-08-14T21:17:32.0720905Z     
2025-08-14T21:17:32.0720989Z     Example:
2025-08-14T21:17:32.0721101Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0721252Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:32.0721379Z         >>> from setuptools import setup
2025-08-14T21:17:32.0721599Z         >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension
2025-08-14T21:17:32.0721684Z         >>> setup(
2025-08-14T21:17:32.0721804Z         ...     name='cuda_extension',
2025-08-14T21:17:32.0721897Z         ...     ext_modules=[
2025-08-14T21:17:32.0721998Z         ...         CUDAExtension(
2025-08-14T21:17:32.0722127Z         ...                 name='cuda_extension',
2025-08-14T21:17:32.0722287Z         ...                 sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:32.0722419Z         ...                 extra_compile_args={'cxx': ['-g'],
2025-08-14T21:17:32.0722554Z         ...                                     'nvcc': ['-O2']},
2025-08-14T21:17:32.0722705Z         ...                 extra_link_args=['-Wl,--no-as-needed', '-lcuda'])
2025-08-14T21:17:32.0722802Z         ...     ],
2025-08-14T21:17:32.0722895Z         ...     cmdclass={
2025-08-14T21:17:32.0723007Z         ...         'build_ext': BuildExtension
2025-08-14T21:17:32.0723101Z         ...     })
2025-08-14T21:17:32.0723182Z     
2025-08-14T21:17:32.0723282Z     Compute capabilities:
2025-08-14T21:17:32.0723377Z     
2025-08-14T21:17:32.0723677Z     By default the extension will be compiled to run on all archs of the cards visible during the
2025-08-14T21:17:32.0723970Z     building process of the extension, plus PTX. If down the road a new card is installed the
2025-08-14T21:17:32.0724276Z     extension may need to be recompiled. If a visible card has a compute capability (CC) that's
2025-08-14T21:17:32.0724578Z     newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch
2025-08-14T21:17:32.0724877Z     will make nvcc fall back to building kernels with the newest version of PTX your nvcc does
2025-08-14T21:17:32.0725001Z     support (see below for details on PTX).
2025-08-14T21:17:32.0725084Z     
2025-08-14T21:17:32.0725408Z     You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which
2025-08-14T21:17:32.0725527Z     CCs you want the extension to support:
2025-08-14T21:17:32.0725607Z     
2025-08-14T21:17:32.0725833Z     ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py``
2025-08-14T21:17:32.0726067Z     ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py``
2025-08-14T21:17:32.0726159Z     
2025-08-14T21:17:32.0726478Z     The +PTX option causes extension kernel binaries to include PTX instructions for the specified
2025-08-14T21:17:32.0726799Z     CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >=
2025-08-14T21:17:32.0727117Z     the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with
2025-08-14T21:17:32.0727412Z     CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to
2025-08-14T21:17:32.0727737Z     provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on
2025-08-14T21:17:32.0728024Z     those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better
2025-08-14T21:17:32.0728349Z     off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6,
2025-08-14T21:17:32.0728673Z     "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but
2025-08-14T21:17:32.0728779Z     "8.0 8.6" would be better.
2025-08-14T21:17:32.0728860Z     
2025-08-14T21:17:32.0729198Z     Note that while it's possible to include all supported archs, the more archs get included the
2025-08-14T21:17:32.0729528Z     slower the building process will be, as it will build a separate kernel image for each arch.
2025-08-14T21:17:32.0729634Z     
2025-08-14T21:17:32.0729976Z     Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows.
2025-08-14T21:17:32.0730191Z     To workaround the issue, move python binding logic to pure C++ file.
2025-08-14T21:17:32.0730272Z     
2025-08-14T21:17:32.0730375Z     Example use:
2025-08-14T21:17:32.0730473Z         #include <ATen/ATen.h>
2025-08-14T21:17:32.0730627Z         at::Tensor SigmoidAlphaBlendForwardCuda(....)
2025-08-14T21:17:32.0730720Z     
2025-08-14T21:17:32.0730806Z     Instead of:
2025-08-14T21:17:32.0730923Z         #include <torch/extension.h>
2025-08-14T21:17:32.0731082Z         torch::Tensor SigmoidAlphaBlendForwardCuda(...)
2025-08-14T21:17:32.0731162Z     
2025-08-14T21:17:32.0731447Z     Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460
2025-08-14T21:17:32.0731960Z     Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48
2025-08-14T21:17:32.0732041Z     
2025-08-14T21:17:32.0732160Z     Relocatable device code linking:
2025-08-14T21:17:32.0732239Z     
2025-08-14T21:17:32.0732518Z     If you want to reference device symbols across compilation units (across object files),
2025-08-14T21:17:32.0732783Z     the object files need to be built with `relocatable device code` (-rdc=true or -dc).
2025-08-14T21:17:32.0733145Z     An exception to this rule is "dynamic parallelism" (nested kernel launches)  which is not used a lot anymore.
2025-08-14T21:17:32.0733484Z     `Relocatable device code` is less optimized so it needs to be used only on object files that need it.
2025-08-14T21:17:32.0733803Z     Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step
2025-08-14T21:17:32.0733984Z     helps reduce the protentional perf degradation of `-rdc`.
2025-08-14T21:17:32.0734166Z     Note that it needs to be used at both steps to be useful.
2025-08-14T21:17:32.0734247Z     
2025-08-14T21:17:32.0734615Z     If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step.
2025-08-14T21:17:32.0734798Z     There is also a case where `-dlink` is used without `-rdc`:
2025-08-14T21:17:32.0735055Z     when an extension is linked against a static lib containing rdc-compiled objects
2025-08-14T21:17:32.0735274Z     like the [NVSHMEM library](https://developer.nvidia.com/nvshmem).
2025-08-14T21:17:32.0735355Z     
2025-08-14T21:17:32.0735582Z     Note: Ninja is required to build a CUDA Extension with RDC linking.
2025-08-14T21:17:32.0735675Z     
2025-08-14T21:17:32.0735757Z     Example:
2025-08-14T21:17:32.0735854Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0736011Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:32.0736107Z         >>> CUDAExtension(
2025-08-14T21:17:32.0736224Z         ...        name='cuda_extension',
2025-08-14T21:17:32.0736385Z         ...        sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:32.0736480Z         ...        dlink=True,
2025-08-14T21:17:32.0736612Z         ...        dlink_libraries=["dlink_lib"],
2025-08-14T21:17:32.0736734Z         ...        extra_compile_args={'cxx': ['-g'],
2025-08-14T21:17:32.0736857Z         ...                            'nvcc': ['-O2', '-rdc=true']})
2025-08-14T21:17:32.0736948Z     
2025-08-14T21:17:32.0737202Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0737282Z     
2025-08-14T21:17:32.0737393Z       warnings.warn(msg)
2025-08-14T21:17:32.0737470Z     
2025-08-14T21:17:32.0737677Z --- Parse Warning: 134 / 146 ---
2025-08-14T21:17:32.0738637Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1408.
2025-08-14T21:17:32.0738925Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0739049Z     
2025-08-14T21:17:32.0739214Z     Creates a :class:`setuptools.Extension` for SYCL/C++.
2025-08-14T21:17:32.0739294Z     
2025-08-14T21:17:32.0739546Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-08-14T21:17:32.0739746Z     bare minimum (but often sufficient) arguments to build a SYCL/C++
2025-08-14T21:17:32.0739831Z     extension.
2025-08-14T21:17:32.0739924Z     
2025-08-14T21:17:32.0740131Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-08-14T21:17:32.0740231Z     constructor.
2025-08-14T21:17:32.0740311Z     
2025-08-14T21:17:32.0740397Z     .. warning::
2025-08-14T21:17:32.0740638Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-08-14T21:17:32.0740848Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-08-14T21:17:32.0741046Z         the user's responsibility in their library to not use APIs from
2025-08-14T21:17:32.0741287Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-08-14T21:17:32.0741503Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-08-14T21:17:32.0741725Z         example, to give access to custom ops from python, the library should
2025-08-14T21:17:32.0741853Z         register the ops through the dispatcher.
2025-08-14T21:17:32.0741931Z     
2025-08-14T21:17:32.0742164Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-08-14T21:17:32.0742367Z         as a compile flag when py_limited_api is specified as an option for
2025-08-14T21:17:32.0742575Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-08-14T21:17:32.0742798Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-08-14T21:17:32.0743009Z         safety, and sanity in order to encourage best practices. To target a
2025-08-14T21:17:32.0743224Z         different version, set min_supported_cpython to the hexcode of the
2025-08-14T21:17:32.0743343Z         CPython version of choice.
2025-08-14T21:17:32.0743422Z     
2025-08-14T21:17:32.0743517Z     Example:
2025-08-14T21:17:32.0743617Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0743766Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:32.0744004Z         >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension
2025-08-14T21:17:32.0744089Z         >>> setup(
2025-08-14T21:17:32.0744220Z         ...     name='xpu_extension',
2025-08-14T21:17:32.0744329Z         ...     ext_modules=[
2025-08-14T21:17:32.0744426Z         ...     SyclExtension(
2025-08-14T21:17:32.0744544Z         ...                 name='xpu_extension',
2025-08-14T21:17:32.0744722Z         ...                 sources=['extension.cpp', 'extension_kernel.cpp'],
2025-08-14T21:17:32.0744900Z         ...                 extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']})
2025-08-14T21:17:32.0745001Z         ...     ],
2025-08-14T21:17:32.0745090Z         ...     cmdclass={
2025-08-14T21:17:32.0745204Z         ...         'build_ext': BuildExtension
2025-08-14T21:17:32.0745299Z         ...     })
2025-08-14T21:17:32.0745378Z     
2025-08-14T21:17:32.0745673Z     By default the extension will be compiled to run on all archs of the cards visible during the
2025-08-14T21:17:32.0745939Z     building process of the extension. If down the road a new card is installed the
2025-08-14T21:17:32.0746192Z     extension may need to be recompiled. You can override the default behavior using
2025-08-14T21:17:32.0746507Z     `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension
2025-08-14T21:17:32.0746596Z     to support:
2025-08-14T21:17:32.0746674Z     
2025-08-14T21:17:32.0746883Z     ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py``
2025-08-14T21:17:32.0746962Z     
2025-08-14T21:17:32.0747307Z     Note that while it's possible to include all supported archs, the more archs get included the
2025-08-14T21:17:32.0747633Z     slower the building process will be, as it will build a separate kernel image for each arch.
2025-08-14T21:17:32.0747712Z     
2025-08-14T21:17:32.0747851Z     Note: Ninja is required to build SyclExtension.
2025-08-14T21:17:32.0747942Z     
2025-08-14T21:17:32.0748190Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0748281Z     
2025-08-14T21:17:32.0748377Z       warnings.warn(msg)
2025-08-14T21:17:32.0748456Z     
2025-08-14T21:17:32.0748665Z --- Parse Warning: 135 / 146 ---
2025-08-14T21:17:32.0749524Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1585.
2025-08-14T21:17:32.0749786Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0749879Z     
2025-08-14T21:17:32.0750025Z     Load a PyTorch C++ extension just-in-time (JIT).
2025-08-14T21:17:32.0750104Z     
2025-08-14T21:17:32.0750322Z     To load an extension, a Ninja build file is emitted, which is used to
2025-08-14T21:17:32.0750528Z     compile the given sources into a dynamic library. This library is
2025-08-14T21:17:32.0750763Z     subsequently loaded into the current Python process as a module and
2025-08-14T21:17:32.0750891Z     returned from this function, ready for use.
2025-08-14T21:17:32.0750973Z     
2025-08-14T21:17:32.0751195Z     By default, the directory to which the build file is emitted and the
2025-08-14T21:17:32.0751511Z     resulting library compiled to is ``<tmp>/torch_extensions/<name>``, where
2025-08-14T21:17:32.0751716Z     ``<tmp>`` is the temporary folder on the current platform and ``<name>``
2025-08-14T21:17:32.0751945Z     the name of the extension. This location can be overridden in two ways.
2025-08-14T21:17:32.0752151Z     First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it
2025-08-14T21:17:32.0752383Z     replaces ``<tmp>/torch_extensions`` and all extensions will be compiled
2025-08-14T21:17:32.0752599Z     into subfolders of this directory. Second, if the ``build_directory``
2025-08-14T21:17:32.0752828Z     argument to this function is supplied, it overrides the entire path, i.e.
2025-08-14T21:17:32.0753005Z     the library will be compiled into that folder directly.
2025-08-14T21:17:32.0753085Z     
2025-08-14T21:17:32.0753331Z     To compile the sources, the default system compiler (``c++``) is used,
2025-08-14T21:17:32.0753584Z     which can be overridden by setting the ``CXX`` environment variable. To pass
2025-08-14T21:17:32.0753807Z     additional arguments to the compilation process, ``extra_cflags`` or
2025-08-14T21:17:32.0754037Z     ``extra_ldflags`` can be provided. For example, to compile your extension
2025-08-14T21:17:32.0754249Z     with optimizations, pass ``extra_cflags=['-O3']``. You can also use
2025-08-14T21:17:32.0754403Z     ``extra_cflags`` to pass further include directories.
2025-08-14T21:17:32.0754497Z     
2025-08-14T21:17:32.0754730Z     CUDA support with mixed compilation is provided. Simply pass CUDA source
2025-08-14T21:17:32.0754911Z     files (``.cu`` or ``.cuh``) along with other sources. Such files will be
2025-08-14T21:17:32.0755162Z     detected and compiled with nvcc rather than the C++ compiler. This includes
2025-08-14T21:17:32.0755371Z     passing the CUDA lib64 directory as a library directory, and linking
2025-08-14T21:17:32.0755535Z     ``cudart``. You can pass additional flags to nvcc via
2025-08-14T21:17:32.0755738Z     ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various
2025-08-14T21:17:32.0755968Z     heuristics for finding the CUDA install directory are used, which usually
2025-08-14T21:17:32.0756195Z     work fine. If not, setting the ``CUDA_HOME`` environment variable is the
2025-08-14T21:17:32.0756349Z     safest option.
2025-08-14T21:17:32.0756457Z     
2025-08-14T21:17:32.0756730Z     SYCL support with mixed compilation is provided. Simply pass SYCL source
2025-08-14T21:17:32.0756929Z     files (``.sycl``) along with other sources. Such files will be detected
2025-08-14T21:17:32.0757144Z     and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather
2025-08-14T21:17:32.0757364Z     than the C++ compiler. You can pass additional flags to SYCL compiler
2025-08-14T21:17:32.0757554Z     via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++.
2025-08-14T21:17:32.0757776Z     SYCL compiler is expected to be found via system PATH environment
2025-08-14T21:17:32.0757862Z     variable.
2025-08-14T21:17:32.0757941Z     
2025-08-14T21:17:32.0758036Z     Args:
2025-08-14T21:17:32.0758242Z         name: The name of the extension to build. This MUST be the same as the
2025-08-14T21:17:32.0758349Z             name of the pybind11 module!
2025-08-14T21:17:32.0758566Z         sources: A list of relative or absolute paths to C++ source files.
2025-08-14T21:17:32.0758793Z         extra_cflags: optional list of compiler flags to forward to the build.
2025-08-14T21:17:32.0759026Z         extra_cuda_cflags: optional list of compiler flags to forward to nvcc
2025-08-14T21:17:32.0759134Z             when building CUDA sources.
2025-08-14T21:17:32.0759351Z         extra_sycl_cflags: optional list of compiler flags to forward to SYCL
2025-08-14T21:17:32.0759485Z             compiler when building SYCL sources.
2025-08-14T21:17:32.0759703Z         extra_ldflags: optional list of linker flags to forward to the build.
2025-08-14T21:17:32.0759923Z         extra_include_paths: optional list of include directories to forward
2025-08-14T21:17:32.0760032Z             to the build.
2025-08-14T21:17:32.0760210Z         build_directory: optional path to use as build workspace.
2025-08-14T21:17:32.0760400Z         verbose: If ``True``, turns on verbose logging of load steps.
2025-08-14T21:17:32.0760621Z         with_cuda: Determines whether CUDA headers and libraries are added to
2025-08-14T21:17:32.0760783Z             the build. If set to ``None`` (default), this value is
2025-08-14T21:17:32.0761002Z             automatically determined based on the existence of ``.cu`` or
2025-08-14T21:17:32.0761171Z             ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers
2025-08-14T21:17:32.0761281Z             and libraries to be included.
2025-08-14T21:17:32.0761515Z         with_sycl: Determines whether SYCL headers and libraries are added to
2025-08-14T21:17:32.0761702Z             the build. If set to ``None`` (default), this value is
2025-08-14T21:17:32.0761927Z             automatically determined based on the existence of ``.sycl`` in
2025-08-14T21:17:32.0762091Z             ``sources``. Set it to `True`` to force SYCL headers and
2025-08-14T21:17:32.0762198Z             libraries to be included.
2025-08-14T21:17:32.0762417Z         is_python_module: If ``True`` (default), imports the produced shared
2025-08-14T21:17:32.0762607Z             library as a Python module. If ``False``, behavior depends on
2025-08-14T21:17:32.0762709Z             ``is_standalone``.
2025-08-14T21:17:32.0762924Z         is_standalone: If ``False`` (default) loads the constructed extension
2025-08-14T21:17:32.0763120Z             into the process as a plain dynamic library. If ``True``, build a
2025-08-14T21:17:32.0763223Z             standalone executable.
2025-08-14T21:17:32.0763315Z     
2025-08-14T21:17:32.0763398Z     Returns:
2025-08-14T21:17:32.0763521Z         If ``is_python_module`` is ``True``:
2025-08-14T21:17:32.0763699Z             Returns the loaded PyTorch extension as a Python module.
2025-08-14T21:17:32.0763781Z     
2025-08-14T21:17:32.0763996Z         If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``:
2025-08-14T21:17:32.0764203Z             Returns nothing. (The shared library is loaded into the process as
2025-08-14T21:17:32.0764293Z             a side effect.)
2025-08-14T21:17:32.0764382Z     
2025-08-14T21:17:32.0764555Z         If ``is_standalone`` is ``True``.
2025-08-14T21:17:32.0764777Z             Return the path to the executable. (On Windows, TORCH_LIB_PATH is
2025-08-14T21:17:32.0764959Z             added to the PATH environment variable as a side effect.)
2025-08-14T21:17:32.0765037Z     
2025-08-14T21:17:32.0765134Z     Example:
2025-08-14T21:17:32.0765229Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0765370Z         >>> from torch.utils.cpp_extension import load
2025-08-14T21:17:32.0765477Z         >>> module = load(
2025-08-14T21:17:32.0765574Z         ...     name='extension',
2025-08-14T21:17:32.0765732Z         ...     sources=['extension.cpp', 'extension_kernel.cu'],
2025-08-14T21:17:32.0765848Z         ...     extra_cflags=['-O2'],
2025-08-14T21:17:32.0765939Z         ...     verbose=True)
2025-08-14T21:17:32.0766019Z     
2025-08-14T21:17:32.0766282Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0766361Z     
2025-08-14T21:17:32.0766461Z       warnings.warn(msg)
2025-08-14T21:17:32.0766551Z     
2025-08-14T21:17:32.0766761Z --- Parse Warning: 136 / 146 ---
2025-08-14T21:17:32.0767670Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1890.
2025-08-14T21:17:32.0767929Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0768007Z     
2025-08-14T21:17:32.0768231Z     Load a PyTorch C++ extension just-in-time (JIT) from string sources.
2025-08-14T21:17:32.0768307Z     
2025-08-14T21:17:32.0768535Z     This function behaves exactly like :func:`load`, but takes its sources as
2025-08-14T21:17:32.0768776Z     strings rather than filenames. These strings are stored to files in the
2025-08-14T21:17:32.0768983Z     build directory, after which the behavior of :func:`load_inline` is
2025-08-14T21:17:32.0769102Z     identical to :func:`load`.
2025-08-14T21:17:32.0769179Z     
2025-08-14T21:17:32.0769261Z     See `the
2025-08-14T21:17:32.0769598Z     tests <https://github.com/pytorch/pytorch/blob/master/test/test_cpp_extensions_jit.py>`_
2025-08-14T21:17:32.0769721Z     for good examples of using this function.
2025-08-14T21:17:32.0769799Z     
2025-08-14T21:17:32.0770041Z     Sources may omit two required parts of a typical non-inline C++ extension:
2025-08-14T21:17:32.0770280Z     the necessary header includes, as well as the (pybind11) binding code. More
2025-08-14T21:17:32.0770557Z     precisely, strings passed to ``cpp_sources`` are first concatenated into a
2025-08-14T21:17:32.0770745Z     single ``.cpp`` file. This file is then prepended with ``#include
2025-08-14T21:17:32.0770845Z     <torch/extension.h>``
2025-08-14T21:17:32.0770936Z     
2025-08-14T21:17:32.0771157Z     Furthermore, if the ``functions`` argument is supplied, bindings will be
2025-08-14T21:17:32.0771392Z     automatically generated for each function specified. ``functions`` can
2025-08-14T21:17:32.0771628Z     either be a list of function names, or a dictionary mapping from function
2025-08-14T21:17:32.0771849Z     names to docstrings. If a list is given, the name of each function is used
2025-08-14T21:17:32.0771941Z     as its docstring.
2025-08-14T21:17:32.0772031Z     
2025-08-14T21:17:32.0772241Z     The sources in ``cuda_sources`` are concatenated into a separate ``.cu``
2025-08-14T21:17:32.0772427Z     file and  prepended with ``torch/types.h``, ``cuda.h`` and
2025-08-14T21:17:32.0772636Z     ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled
2025-08-14T21:17:32.0772856Z     separately, but ultimately linked into a single library. Note that no
2025-08-14T21:17:32.0773094Z     bindings are generated for functions in ``cuda_sources`` per se. To bind
2025-08-14T21:17:32.0773307Z     to a CUDA kernel, you must create a C++ function that calls it, and either
2025-08-14T21:17:32.0773544Z     declare or define this C++ function in one of the ``cpp_sources`` (and
2025-08-14T21:17:32.0773716Z     include its name in ``functions``).
2025-08-14T21:17:32.0773794Z     
2025-08-14T21:17:32.0774023Z     The sources in ``sycl_sources`` are concatenated into a separate ``.sycl``
2025-08-14T21:17:32.0774237Z     file and  prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes.
2025-08-14T21:17:32.0774431Z     The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately
2025-08-14T21:17:32.0774656Z     linked into a single library. Note that no bindings are generated for
2025-08-14T21:17:32.0774868Z     functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must
2025-08-14T21:17:32.0775074Z     create a C++ function that calls it, and either declare or define this
2025-08-14T21:17:32.0775272Z     C++ function in one of the ``cpp_sources`` (and include its name
2025-08-14T21:17:32.0775363Z     in ``functions``).
2025-08-14T21:17:32.0775455Z     
2025-08-14T21:17:32.0775532Z     
2025-08-14T21:17:32.0775612Z     
2025-08-14T21:17:32.0775808Z     See :func:`load` for a description of arguments omitted below.
2025-08-14T21:17:32.0775887Z     
2025-08-14T21:17:32.0775969Z     Args:
2025-08-14T21:17:32.0776196Z         cpp_sources: A string, or list of strings, containing C++ source code.
2025-08-14T21:17:32.0776417Z         cuda_sources: A string, or list of strings, containing CUDA source code.
2025-08-14T21:17:32.0776635Z         sycl_sources: A string, or list of strings, containing SYCL source code.
2025-08-14T21:17:32.0776851Z         functions: A list of function names for which to generate function
2025-08-14T21:17:32.0777065Z             bindings. If a dictionary is given, it should map function names to
2025-08-14T21:17:32.0777258Z             docstrings (which are otherwise just the function names).
2025-08-14T21:17:32.0777477Z         with_cuda: Determines whether CUDA headers and libraries are added to
2025-08-14T21:17:32.0777636Z             the build. If set to ``None`` (default), this value is
2025-08-14T21:17:32.0777852Z             automatically determined based on whether ``cuda_sources`` is
2025-08-14T21:17:32.0778005Z             provided. Set it to ``True`` to force CUDA headers
2025-08-14T21:17:32.0778113Z             and libraries to be included.
2025-08-14T21:17:32.0778344Z         with_sycl: Determines whether SYCL headers and libraries are added to
2025-08-14T21:17:32.0778499Z             the build. If set to ``None`` (default), this value is
2025-08-14T21:17:32.0778711Z             automatically determined based on whether ``sycl_sources`` is
2025-08-14T21:17:32.0778885Z             provided. Set it to ``True`` to force SYCL headers
2025-08-14T21:17:32.0778994Z             and libraries to be included.
2025-08-14T21:17:32.0779211Z         with_pytorch_error_handling: Determines whether pytorch error and
2025-08-14T21:17:32.0779406Z             warning macros are handled by pytorch instead of pybind. To do
2025-08-14T21:17:32.0779621Z             this, each function ``foo`` is called via an intermediary ``_safe_foo``
2025-08-14T21:17:32.0779831Z             function. This redirection might cause issues in obscure cases
2025-08-14T21:17:32.0780012Z             of cpp. This flag should be set to ``False`` when this redirect
2025-08-14T21:17:32.0780119Z             causes issues.
2025-08-14T21:17:32.0780369Z         no_implicit_headers: If ``True``, skips automatically adding headers, most notably
2025-08-14T21:17:32.0780591Z             ``#include <torch/extension.h>`` and ``#include <torch/types.h>`` lines.
2025-08-14T21:17:32.0780762Z             Use this option to improve cold start times when you
2025-08-14T21:17:32.0781016Z             already include the necessary headers in your source code. Default: ``False``.
2025-08-14T21:17:32.0781095Z     
2025-08-14T21:17:32.0781193Z     Example:
2025-08-14T21:17:32.0781338Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-08-14T21:17:32.0781496Z         >>> from torch.utils.cpp_extension import load_inline
2025-08-14T21:17:32.0781625Z         >>> source = """
2025-08-14T21:17:32.0781797Z         at::Tensor sin_add(at::Tensor x, at::Tensor y) {
2025-08-14T21:17:32.0781935Z           return x.sin() + y.sin();
2025-08-14T21:17:32.0782017Z         }
2025-08-14T21:17:32.0782099Z         """
2025-08-14T21:17:32.0782248Z         >>> module = load_inline(name='inline_extension',
2025-08-14T21:17:32.0782365Z         ...                      cpp_sources=[source],
2025-08-14T21:17:32.0782480Z         ...                      functions=['sin_add'])
2025-08-14T21:17:32.0782572Z     
2025-08-14T21:17:32.0782654Z     .. note::
2025-08-14T21:17:32.0782890Z         Since load_inline will just-in-time compile the source code, please ensure
2025-08-14T21:17:32.0783129Z         that you have the right toolchains installed in the runtime. For example,
2025-08-14T21:17:32.0783344Z         when loading C++, make sure a C++ compiler is available. If you're loading
2025-08-14T21:17:32.0783599Z         a CUDA extension, you will need to additionally install the corresponding CUDA
2025-08-14T21:17:32.0783846Z         toolkit (nvcc and any other dependencies your code has). Compiling toolchains
2025-08-14T21:17:32.0784084Z         are not included when you install torch and must be additionally installed.
2025-08-14T21:17:32.0784173Z     
2025-08-14T21:17:32.0784423Z         During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build
2025-08-14T21:17:32.0784639Z         the extension. This may use up too many resources on some systems. One
2025-08-14T21:17:32.0784870Z         can control the number of workers by setting the `MAX_JOBS` environment
2025-08-14T21:17:32.0784985Z         variable to a non-negative number.
2025-08-14T21:17:32.0785076Z     
2025-08-14T21:17:32.0785324Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0785402Z     
2025-08-14T21:17:32.0785508Z       warnings.warn(msg)
2025-08-14T21:17:32.0785586Z     
2025-08-14T21:17:32.0785789Z --- Parse Warning: 137 / 146 ---
2025-08-14T21:17:32.0786783Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61.
2025-08-14T21:17:32.0787046Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0787140Z     
2025-08-14T21:17:32.0787433Z     This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark.
2025-08-14T21:17:32.0787510Z     
2025-08-14T21:17:32.0787848Z     This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible
2025-08-14T21:17:32.0788097Z     for executing a PyTorch module (nn.Module or ScriptModule) under an inference
2025-08-14T21:17:32.0788327Z     server like load. It can emulate multiple calling threads to a single module
2025-08-14T21:17:32.0788578Z     provided. In the future we plan to enhance this component to support inter and
2025-08-14T21:17:32.0788821Z     intra-op parallelism as well as multiple models running in a single process.
2025-08-14T21:17:32.0788915Z     
2025-08-14T21:17:32.0789167Z     Please note that even though nn.Module is supported, it might incur an overhead
2025-08-14T21:17:32.0789383Z     from the need to hold GIL every time we execute Python code or pass around
2025-08-14T21:17:32.0789636Z     inputs as Python objects. As soon as you have a ScriptModule version of your
2025-08-14T21:17:32.0789878Z     model for inference deployment it is better to switch to using it in this
2025-08-14T21:17:32.0789964Z     benchmark.
2025-08-14T21:17:32.0790052Z     
2025-08-14T21:17:32.0790138Z     Example::
2025-08-14T21:17:32.0790217Z     
2025-08-14T21:17:32.0790350Z         >>> # xdoctest: +SKIP("undefined vars")
2025-08-14T21:17:32.0790490Z         >>> from torch.utils import ThroughputBenchmark
2025-08-14T21:17:32.0790617Z         >>> bench = ThroughputBenchmark(my_module)
2025-08-14T21:17:32.0790812Z         >>> # Pre-populate benchmark's data set with the inputs
2025-08-14T21:17:32.0790959Z         >>> for input in inputs:
2025-08-14T21:17:32.0791189Z         ...     # Both args and kwargs work, same as any PyTorch Module / ScriptModule
2025-08-14T21:17:32.0791316Z         ...     bench.add_input(input[0], x2=input[1])
2025-08-14T21:17:32.0791586Z         >>> # Inputs supplied above are randomly used during the execution
2025-08-14T21:17:32.0791708Z         >>> stats = bench.benchmark(
2025-08-14T21:17:32.0791811Z         ...     num_calling_threads=4,
2025-08-14T21:17:32.0791914Z         ...     num_warmup_iters = 100,
2025-08-14T21:17:32.0792025Z         ...     num_iters = 1000,
2025-08-14T21:17:32.0792105Z         ... )
2025-08-14T21:17:32.0792289Z         >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms))
2025-08-14T21:17:32.0792477Z         >>> print("Number of iterations: {}".format(stats.num_iters))
2025-08-14T21:17:32.0792555Z     
2025-08-14T21:17:32.0792813Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0792909Z     
2025-08-14T21:17:32.0793007Z       warnings.warn(msg)
2025-08-14T21:17:32.0793085Z     
2025-08-14T21:17:32.0793297Z --- Parse Warning: 138 / 146 ---
2025-08-14T21:17:32.0794244Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18.
2025-08-14T21:17:32.0794522Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0794720Z     Sampler that restricts data loading to a subset of the dataset.
2025-08-14T21:17:32.0794800Z     
2025-08-14T21:17:32.0794943Z         It is especially useful in conjunction with
2025-08-14T21:17:32.0795187Z         :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each
2025-08-14T21:17:32.0795450Z         process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a
2025-08-14T21:17:32.0795693Z         :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the
2025-08-14T21:17:32.0795821Z         original dataset that is exclusive to it.
2025-08-14T21:17:32.0795912Z     
2025-08-14T21:17:32.0795999Z         .. note::
2025-08-14T21:17:32.0796232Z             Dataset is assumed to be of constant size and that any instance of it always
2025-08-14T21:17:32.0796381Z             returns the same elements in the same order.
2025-08-14T21:17:32.0796461Z     
2025-08-14T21:17:32.0796545Z         Args:
2025-08-14T21:17:32.0796720Z             dataset: Dataset used for sampling.
2025-08-14T21:17:32.0796933Z             num_replicas (int, optional): Number of processes participating in
2025-08-14T21:17:32.0797177Z                 distributed training. By default, :attr:`world_size` is retrieved from the
2025-08-14T21:17:32.0797300Z                 current distributed group.
2025-08-14T21:17:32.0797542Z             rank (int, optional): Rank of the current process within :attr:`num_replicas`.
2025-08-14T21:17:32.0797753Z                 By default, :attr:`rank` is retrieved from the current distributed
2025-08-14T21:17:32.0797836Z                 group.
2025-08-14T21:17:32.0798056Z             shuffle (bool, optional): If ``True`` (default), sampler will shuffle the
2025-08-14T21:17:32.0798153Z                 indices.
2025-08-14T21:17:32.0798340Z             seed (int, optional): random seed used to shuffle the sampler if
2025-08-14T21:17:32.0798536Z                 :attr:`shuffle=True`. This number should be identical across all
2025-08-14T21:17:32.0798712Z                 processes in the distributed group. Default: ``0``.
2025-08-14T21:17:32.0798924Z             drop_last (bool, optional): if ``True``, then the sampler will drop the
2025-08-14T21:17:32.0799127Z                 tail of the data to make it evenly divisible across the number of
2025-08-14T21:17:32.0799345Z                 replicas. If ``False``, the sampler will add extra indices to make
2025-08-14T21:17:32.0799582Z                 the data evenly divisible across the replicas. Default: ``False``.
2025-08-14T21:17:32.0799692Z     
2025-08-14T21:17:32.0799781Z         .. warning::
2025-08-14T21:17:32.0799967Z             In distributed mode, calling the :meth:`set_epoch` method at
2025-08-14T21:17:32.0800225Z             the beginning of each epoch **before** creating the :class:`DataLoader` iterator
2025-08-14T21:17:32.0800480Z             is necessary to make shuffling work properly across multiple epochs. Otherwise,
2025-08-14T21:17:32.0800618Z             the same ordering will be always used.
2025-08-14T21:17:32.0800695Z     
2025-08-14T21:17:32.0800783Z         Example::
2025-08-14T21:17:32.0800872Z     
2025-08-14T21:17:32.0800967Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0801184Z             >>> sampler = DistributedSampler(dataset) if is_distributed else None
2025-08-14T21:17:32.0801366Z             >>> loader = DataLoader(dataset, shuffle=(sampler is None),
2025-08-14T21:17:32.0801479Z             ...                     sampler=sampler)
2025-08-14T21:17:32.0801616Z             >>> for epoch in range(start_epoch, n_epochs):
2025-08-14T21:17:32.0801724Z             ...     if is_distributed:
2025-08-14T21:17:32.0801835Z             ...         sampler.set_epoch(epoch)
2025-08-14T21:17:32.0801942Z             ...     train(loader)
2025-08-14T21:17:32.0802020Z         
2025-08-14T21:17:32.0802269Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0802358Z     
2025-08-14T21:17:32.0802452Z       warnings.warn(msg)
2025-08-14T21:17:32.0802532Z     
2025-08-14T21:17:32.0802724Z --- Parse Warning: 139 / 146 ---
2025-08-14T21:17:32.0803672Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=227.
2025-08-14T21:17:32.0803948Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0804199Z     Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights).
2025-08-14T21:17:32.0804278Z     
2025-08-14T21:17:32.0804372Z         Args:
2025-08-14T21:17:32.0804611Z             weights (sequence)   : a sequence of weights, not necessary summing up to one
2025-08-14T21:17:32.0804746Z             num_samples (int): number of samples to draw
2025-08-14T21:17:32.0804964Z             replacement (bool): if ``True``, samples are drawn with replacement.
2025-08-14T21:17:32.0805200Z                 If not, they are drawn without replacement, which means that when a
2025-08-14T21:17:32.0805416Z                 sample index is drawn for a row, it cannot be drawn again for that row.
2025-08-14T21:17:32.0805581Z             generator (Generator): Generator used in sampling.
2025-08-14T21:17:32.0805659Z     
2025-08-14T21:17:32.0805757Z         Example:
2025-08-14T21:17:32.0805899Z             >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-08-14T21:17:32.0805986Z             >>> list(
2025-08-14T21:17:32.0806109Z             ...     WeightedRandomSampler(
2025-08-14T21:17:32.0806247Z             ...         [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True
2025-08-14T21:17:32.0806331Z             ...     )
2025-08-14T21:17:32.0806419Z             ... )
2025-08-14T21:17:32.0806501Z             [4, 4, 1, 4, 5]
2025-08-14T21:17:32.0806583Z             >>> list(
2025-08-14T21:17:32.0806703Z             ...     WeightedRandomSampler(
2025-08-14T21:17:32.0806842Z             ...         [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False
2025-08-14T21:17:32.0806934Z             ...     )
2025-08-14T21:17:32.0807011Z             ... )
2025-08-14T21:17:32.0807095Z             [0, 1, 4, 3, 2]
2025-08-14T21:17:32.0807185Z         
2025-08-14T21:17:32.0807434Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0807539Z     
2025-08-14T21:17:32.0807670Z       warnings.warn(msg)
2025-08-14T21:17:32.0807772Z     
2025-08-14T21:17:32.0807956Z --- Parse Warning: 140 / 146 ---
2025-08-14T21:17:32.0808860Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=300.
2025-08-14T21:17:32.0809288Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0809476Z     Wraps another sampler to yield a mini-batch of indices.
2025-08-14T21:17:32.0809556Z     
2025-08-14T21:17:32.0809640Z         Args:
2025-08-14T21:17:32.0809879Z             sampler (Sampler or Iterable): Base sampler. Can be any iterable object
2025-08-14T21:17:32.0809998Z             batch_size (int): Size of mini-batch.
2025-08-14T21:17:32.0810200Z             drop_last (bool): If ``True``, the sampler will drop the last batch if
2025-08-14T21:17:32.0810349Z                 its size would be less than ``batch_size``
2025-08-14T21:17:32.0810431Z     
2025-08-14T21:17:32.0810516Z         Example:
2025-08-14T21:17:32.0810610Z             >>> list(
2025-08-14T21:17:32.0810709Z             ...     BatchSampler(
2025-08-14T21:17:32.0810921Z             ...         SequentialSampler(range(10)), batch_size=3, drop_last=False
2025-08-14T21:17:32.0811002Z             ...     )
2025-08-14T21:17:32.0811083Z             ... )
2025-08-14T21:17:32.0811192Z             [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]
2025-08-14T21:17:32.0811275Z             >>> list(
2025-08-14T21:17:32.0811532Z             ...     BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True)
2025-08-14T21:17:32.0811619Z             ... )
2025-08-14T21:17:32.0811715Z             [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
2025-08-14T21:17:32.0811796Z         
2025-08-14T21:17:32.0812055Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0812139Z     
2025-08-14T21:17:32.0812241Z       warnings.warn(msg)
2025-08-14T21:17:32.0812320Z     
2025-08-14T21:17:32.0812505Z --- Parse Warning: 141 / 146 ---
2025-08-14T21:17:32.0813465Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py line=56.
2025-08-14T21:17:32.0813723Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0813799Z     
2025-08-14T21:17:32.0813994Z     Iterable-style DataPipe.
2025-08-14T21:17:32.0814074Z     
2025-08-14T21:17:32.0814326Z     All DataPipes that represent an iterable of data samples should subclass this.
2025-08-14T21:17:32.0814589Z     This style of DataPipes is particularly useful when data come from a stream, or
2025-08-14T21:17:32.0814946Z     when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its
2025-08-14T21:17:32.0815246Z     elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``.
2025-08-14T21:17:32.0815326Z     
2025-08-14T21:17:32.0815552Z     All subclasses should overwrite :meth:`__iter__`, which would return an
2025-08-14T21:17:32.0815905Z     iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its
2025-08-14T21:17:32.0816269Z     method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should
2025-08-14T21:17:32.0816554Z     override ``reset()`` if necessary. The common usages include resetting buffers, pointers,
2025-08-14T21:17:32.0816755Z     and various state variables within the custom ``IterDataPipe``.
2025-08-14T21:17:32.0816836Z     
2025-08-14T21:17:32.0816928Z     Note:
2025-08-14T21:17:32.0817138Z         Only `one` iterator can be valid for each ``IterDataPipe`` at a time,
2025-08-14T21:17:32.0817520Z         and the creation a second iterator will invalidate the first one. This constraint is necessary because
2025-08-14T21:17:32.0817969Z         some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators.
2025-08-14T21:17:32.0818235Z         The code example below presents details on how this constraint looks in practice.
2025-08-14T21:17:32.0818607Z         If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_.
2025-08-14T21:17:32.0818684Z     
2025-08-14T21:17:32.0818969Z     These DataPipes can be invoked in two ways, using the class constructor or applying their
2025-08-14T21:17:32.0819337Z     functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes).
2025-08-14T21:17:32.0819647Z     You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple
2025-08-14T21:17:32.0819749Z     operations in succession.
2025-08-14T21:17:32.0819841Z     
2025-08-14T21:17:32.0819977Z     .. _GitHub IterDataPipe Single Iterator Issue:
2025-08-14T21:17:32.0820123Z         https://github.com/pytorch/data/issues/45
2025-08-14T21:17:32.0820201Z     
2025-08-14T21:17:32.0820279Z     Note:
2025-08-14T21:17:32.0820515Z         When a subclass is used with :class:`~torch.utils.data.DataLoader`, each
2025-08-14T21:17:32.0820780Z         item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader`
2025-08-14T21:17:32.0820997Z         iterator. When :attr:`num_workers > 0`, each worker process will have a
2025-08-14T21:17:32.0821243Z         different copy of the DataPipe object, so it is often desired to configure
2025-08-14T21:17:32.0821477Z         each copy independently to avoid having duplicate data returned from the
2025-08-14T21:17:32.0821724Z         workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker
2025-08-14T21:17:32.0821973Z         process, returns information about the worker. It can be used in either the
2025-08-14T21:17:32.0822216Z         dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's
2025-08-14T21:17:32.0822411Z         :attr:`worker_init_fn` option to modify each copy's behavior.
2025-08-14T21:17:32.0822490Z     
2025-08-14T21:17:32.0822572Z     Examples:
2025-08-14T21:17:32.0822675Z         General Usage:
2025-08-14T21:17:32.0822772Z             >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0822974Z             >>> from torchdata.datapipes.iter import IterableWrapper, Mapper
2025-08-14T21:17:32.0823108Z             >>> dp = IterableWrapper(range(10))
2025-08-14T21:17:32.0823319Z             >>> map_dp_1 = Mapper(dp, lambda x: x + 1)  # Using class constructor
2025-08-14T21:17:32.0823428Z             >>> map_dp_2 = dp.map(
2025-08-14T21:17:32.0823524Z             ...     lambda x: x + 1
2025-08-14T21:17:32.0823653Z             ... )  # Using functional form (recommended)
2025-08-14T21:17:32.0823760Z             >>> list(map_dp_1)
2025-08-14T21:17:32.0823857Z             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
2025-08-14T21:17:32.0823948Z             >>> list(map_dp_2)
2025-08-14T21:17:32.0824053Z             [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
2025-08-14T21:17:32.0824198Z             >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0)
2025-08-14T21:17:32.0824292Z             >>> list(filter_dp)
2025-08-14T21:17:32.0824393Z             [2, 4, 6, 8, 10]
2025-08-14T21:17:32.0824504Z         Single Iterator Constraint Example:
2025-08-14T21:17:32.0824717Z             >>> from torchdata.datapipes.iter import IterableWrapper, Mapper
2025-08-14T21:17:32.0824847Z             >>> source_dp = IterableWrapper(range(10))
2025-08-14T21:17:32.0824947Z             >>> it1 = iter(source_dp)
2025-08-14T21:17:32.0825046Z             >>> list(it1)
2025-08-14T21:17:32.0825136Z             [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
2025-08-14T21:17:32.0825233Z             >>> it1 = iter(source_dp)
2025-08-14T21:17:32.0825334Z             >>> it2 = iter(
2025-08-14T21:17:32.0825422Z             ...     source_dp
2025-08-14T21:17:32.0825630Z             ... )  # The creation of a new iterator invalidates `it1`
2025-08-14T21:17:32.0825762Z             >>> next(it2)
2025-08-14T21:17:32.0825841Z             0
2025-08-14T21:17:32.0826038Z             >>> next(it1)  # Further usage of `it1` will raise a `RunTimeError`
2025-08-14T21:17:32.0826118Z     
2025-08-14T21:17:32.0826367Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0826459Z     
2025-08-14T21:17:32.0826551Z       warnings.warn(msg)
2025-08-14T21:17:32.0826628Z     
2025-08-14T21:17:32.0826836Z --- Parse Warning: 142 / 146 ---
2025-08-14T21:17:32.0827900Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=375.
2025-08-14T21:17:32.0828177Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0828255Z     
2025-08-14T21:17:32.0828711Z     Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``).
2025-08-14T21:17:32.0828803Z     
2025-08-14T21:17:32.0828987Z     A list of the child DataPipes is returned from this operation.
2025-08-14T21:17:32.0829061Z     
2025-08-14T21:17:32.0829156Z     Args:
2025-08-14T21:17:32.0829286Z         datapipe: Iterable DataPipe being filtered
2025-08-14T21:17:32.0829478Z         num_instances: number of instances of the DataPipe to create
2025-08-14T21:17:32.0829865Z         classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None``
2025-08-14T21:17:32.0830184Z         drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None``
2025-08-14T21:17:32.0830515Z         buffer_size: this defines the maximum number of inputs that the buffer can hold across all child
2025-08-14T21:17:32.0830697Z             DataPipes while waiting for their values to be yielded.
2025-08-14T21:17:32.0830873Z             Defaults to ``1000``. Use ``-1`` for the unlimited buffer.
2025-08-14T21:17:32.0830968Z     
2025-08-14T21:17:32.0831056Z     Examples:
2025-08-14T21:17:32.0831179Z         >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:32.0831369Z         >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:32.0831542Z         >>> def odd_or_even(n):
2025-08-14T21:17:32.0831653Z         ...     return n % 2
2025-08-14T21:17:32.0831816Z         >>> source_dp = IterableWrapper(range(5))
2025-08-14T21:17:32.0832029Z         >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even)
2025-08-14T21:17:32.0832131Z         >>> list(dp1)
2025-08-14T21:17:32.0832213Z         [0, 2, 4]
2025-08-14T21:17:32.0832298Z         >>> list(dp2)
2025-08-14T21:17:32.0832396Z         [1, 3]
2025-08-14T21:17:32.0832632Z         >>> # It can also filter out any element that gets `None` from the `classifier_fn`
2025-08-14T21:17:32.0832740Z         >>> def odd_or_even_no_zero(n):
2025-08-14T21:17:32.0832866Z         ...     return n % 2 if n != 0 else None
2025-08-14T21:17:32.0832972Z         >>> dp1, dp2 = source_dp.demux(
2025-08-14T21:17:32.0833198Z         ...     num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True
2025-08-14T21:17:32.0833282Z         ... )
2025-08-14T21:17:32.0833369Z         >>> list(dp1)
2025-08-14T21:17:32.0833463Z         [2, 4]
2025-08-14T21:17:32.0833548Z         >>> list(dp2)
2025-08-14T21:17:32.0833629Z         [1, 3]
2025-08-14T21:17:32.0833723Z     
2025-08-14T21:17:32.0833973Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0834052Z     
2025-08-14T21:17:32.0834158Z       warnings.warn(msg)
2025-08-14T21:17:32.0834236Z     
2025-08-14T21:17:32.0834428Z --- Parse Warning: 143 / 146 ---
2025-08-14T21:17:32.0835517Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=594.
2025-08-14T21:17:32.0835826Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0835918Z     
2025-08-14T21:17:32.0836226Z     Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``).
2025-08-14T21:17:32.0836304Z     
2025-08-14T21:17:32.0836662Z     As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration,
2025-08-14T21:17:32.0836846Z     and so on. It ends when the shortest input DataPipe is exhausted.
2025-08-14T21:17:32.0836924Z     
2025-08-14T21:17:32.0837016Z     Args:
2025-08-14T21:17:32.0837422Z         datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted
2025-08-14T21:17:32.0837516Z     
2025-08-14T21:17:32.0837604Z     Example:
2025-08-14T21:17:32.0837732Z         >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:32.0837921Z         >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:32.0838018Z         >>> dp1, dp2, dp3 = (
2025-08-14T21:17:32.0838132Z         ...     IterableWrapper(range(3)),
2025-08-14T21:17:32.0838263Z         ...     IterableWrapper(range(10, 15)),
2025-08-14T21:17:32.0838379Z         ...     IterableWrapper(range(20, 25)),
2025-08-14T21:17:32.0838461Z         ... )
2025-08-14T21:17:32.0838577Z         >>> list(dp1.mux(dp2, dp3))
2025-08-14T21:17:32.0838672Z         [0, 10, 20, 1, 11, 21, 2, 12, 22]
2025-08-14T21:17:32.0838750Z     
2025-08-14T21:17:32.0839013Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0839092Z     
2025-08-14T21:17:32.0839198Z       warnings.warn(msg)
2025-08-14T21:17:32.0839280Z     
2025-08-14T21:17:32.0839465Z --- Parse Warning: 144 / 146 ---
2025-08-14T21:17:32.0840503Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=665.
2025-08-14T21:17:32.0840764Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0840842Z     
2025-08-14T21:17:32.0841160Z     Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``).
2025-08-14T21:17:32.0841242Z     
2025-08-14T21:17:32.0841513Z     The output is stopped as soon as the shortest input DataPipe is exhausted.
2025-08-14T21:17:32.0841591Z     
2025-08-14T21:17:32.0841673Z     Args:
2025-08-14T21:17:32.0841833Z         *datapipes: Iterable DataPipes being aggregated
2025-08-14T21:17:32.0841911Z     
2025-08-14T21:17:32.0841995Z     Example:
2025-08-14T21:17:32.0842128Z         >>> # xdoctest: +REQUIRES(module:torchdata)
2025-08-14T21:17:32.0842304Z         >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:32.0842402Z         >>> dp1, dp2, dp3 = (
2025-08-14T21:17:32.0842528Z         ...     IterableWrapper(range(5)),
2025-08-14T21:17:32.0842649Z         ...     IterableWrapper(range(10, 15)),
2025-08-14T21:17:32.0842775Z         ...     IterableWrapper(range(20, 25)),
2025-08-14T21:17:32.0842859Z         ... )
2025-08-14T21:17:32.0842960Z         >>> list(dp1.zip(dp2, dp3))
2025-08-14T21:17:32.0843105Z         [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)]
2025-08-14T21:17:32.0843184Z     
2025-08-14T21:17:32.0843438Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0843531Z     
2025-08-14T21:17:32.0843626Z       warnings.warn(msg)
2025-08-14T21:17:32.0843708Z     
2025-08-14T21:17:32.0843902Z --- Parse Warning: 145 / 146 ---
2025-08-14T21:17:32.0844975Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18.
2025-08-14T21:17:32.0845294Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0845373Z     
2025-08-14T21:17:32.0845743Z     Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``).
2025-08-14T21:17:32.0845836Z     
2025-08-14T21:17:32.0845917Z     Args:
2025-08-14T21:17:32.0846082Z         datapipe: Iterable datapipe that provides pathnames
2025-08-14T21:17:32.0846270Z         mode: An optional string that specifies the mode in which
2025-08-14T21:17:32.0846478Z             the file is opened by ``open()``. It defaults to ``r``, other options are
2025-08-14T21:17:32.0846650Z             ``b`` for reading in binary mode and ``t`` for text mode.
2025-08-14T21:17:32.0846853Z         encoding: An optional string that specifies the encoding of the
2025-08-14T21:17:32.0847116Z             underlying file. It defaults to ``None`` to match the default encoding of ``open``.
2025-08-14T21:17:32.0847256Z         length: Nominal length of the datapipe
2025-08-14T21:17:32.0847336Z     
2025-08-14T21:17:32.0847418Z     Note:
2025-08-14T21:17:32.0847698Z         The opened file handles will be closed by Python's GC periodically. Users can choose
2025-08-14T21:17:32.0847803Z         to close them explicitly.
2025-08-14T21:17:32.0847880Z     
2025-08-14T21:17:32.0847979Z     Example:
2025-08-14T21:17:32.0848076Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0848209Z         >>> from torchdata.datapipes.iter import (
2025-08-14T21:17:32.0848315Z         ...     FileLister,
2025-08-14T21:17:32.0848404Z         ...     FileOpener,
2025-08-14T21:17:32.0848510Z         ...     StreamReader,
2025-08-14T21:17:32.0848594Z         ... )
2025-08-14T21:17:32.0848808Z         >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt"))
2025-08-14T21:17:32.0848922Z         >>> dp = FileOpener(dp)
2025-08-14T21:17:32.0849024Z         >>> dp = StreamReader(dp)
2025-08-14T21:17:32.0849110Z         >>> list(dp)
2025-08-14T21:17:32.0849217Z         [('./abc.txt', 'abc')]
2025-08-14T21:17:32.0849300Z     
2025-08-14T21:17:32.0849555Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0849648Z     
2025-08-14T21:17:32.0849742Z       warnings.warn(msg)
2025-08-14T21:17:32.0849820Z     
2025-08-14T21:17:32.0850015Z --- Parse Warning: 146 / 146 ---
2025-08-14T21:17:32.0851068Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155.
2025-08-14T21:17:32.0851342Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-08-14T21:17:32.0851421Z     
2025-08-14T21:17:32.0851832Z     Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``.
2025-08-14T21:17:32.0851922Z     
2025-08-14T21:17:32.0852029Z     (functional name: ``groupby``).
2025-08-14T21:17:32.0852119Z     
2025-08-14T21:17:32.0852501Z     The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group
2025-08-14T21:17:32.0852792Z     will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full,
2025-08-14T21:17:32.0853109Z     the DataPipe will yield the largest batch with the same key, provided that its size is larger
2025-08-14T21:17:32.0853429Z     than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``.
2025-08-14T21:17:32.0853507Z     
2025-08-14T21:17:32.0853895Z     After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity
2025-08-14T21:17:32.0854235Z     will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``.
2025-08-14T21:17:32.0854374Z     
2025-08-14T21:17:32.0854455Z     Args:
2025-08-14T21:17:32.0854586Z         datapipe: Iterable datapipe to be grouped
2025-08-14T21:17:32.0854875Z         group_key_fn: Function used to generate group key from the data of the source datapipe
2025-08-14T21:17:32.0855107Z         keep_key: Option to yield the matching key along with the items in a tuple,
2025-08-14T21:17:32.0855284Z             resulting in `(key, [items])` otherwise returning [items]
2025-08-14T21:17:32.0855452Z         buffer_size: The size of buffer for ungrouped data
2025-08-14T21:17:32.0855730Z         group_size: The max size of each group, a batch is yielded as soon as it reaches this size
2025-08-14T21:17:32.0856080Z         guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full
2025-08-14T21:17:32.0856439Z         drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer
2025-08-14T21:17:32.0856547Z             when the buffer is full
2025-08-14T21:17:32.0856638Z     
2025-08-14T21:17:32.0856721Z     Example:
2025-08-14T21:17:32.0856809Z         >>> import os
2025-08-14T21:17:32.0856919Z         >>> # xdoctest: +SKIP
2025-08-14T21:17:32.0857094Z         >>> from torchdata.datapipes.iter import IterableWrapper
2025-08-14T21:17:32.0857190Z         >>> def group_fn(file):
2025-08-14T21:17:32.0857342Z         ...     return os.path.basename(file).split(".")[0]
2025-08-14T21:17:32.0857456Z         >>> source_dp = IterableWrapper(
2025-08-14T21:17:32.0857629Z         ...     ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"]
2025-08-14T21:17:32.0857713Z         ... )
2025-08-14T21:17:32.0857852Z         >>> dp0 = source_dp.groupby(group_key_fn=group_fn)
2025-08-14T21:17:32.0857949Z         >>> list(dp0)
2025-08-14T21:17:32.0858108Z         [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']]
2025-08-14T21:17:32.0858297Z         >>> # A group is yielded as soon as its size equals to `group_size`
2025-08-14T21:17:32.0858493Z         >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2)
2025-08-14T21:17:32.0858580Z         >>> list(dp1)
2025-08-14T21:17:32.0858739Z         [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']]
2025-08-14T21:17:32.0859093Z         >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size`
2025-08-14T21:17:32.0859195Z         >>> dp2 = source_dp.groupby(
2025-08-14T21:17:32.0859348Z         ...     group_key_fn=group_fn,
2025-08-14T21:17:32.0859445Z         ...     buffer_size=3,
2025-08-14T21:17:32.0859537Z         ...     group_size=3,
2025-08-14T21:17:32.0859656Z         ...     guaranteed_group_size=2,
2025-08-14T21:17:32.0859739Z         ... )
2025-08-14T21:17:32.0859824Z         >>> list(dp2)
2025-08-14T21:17:32.0860000Z         [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']]
2025-08-14T21:17:32.0860081Z     
2025-08-14T21:17:32.0860335Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-08-14T21:17:32.0860429Z     
2025-08-14T21:17:32.0860526Z       warnings.warn(msg)
2025-08-14T21:17:32.0860617Z     
2025-08-14T21:17:32.0860726Z 
2025-08-14T21:17:32.0860897Z === Found 8 run-time warnings ===
2025-08-14T21:17:32.0861091Z --- Runtime Warning: 1 / 8 ---
2025-08-14T21:17:32.0861351Z example = <DocTest(torch._tensor Tensor.refine_names:0 ln 1333) at 0x7f46424b17b0>
2025-08-14T21:17:32.0862693Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py:1351: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /var/lib/jenkins/workspace/c10/core/TensorImpl.h:1978.)
2025-08-14T21:17:32.0862823Z       return super().refine_names(names)
2025-08-14T21:17:32.0862970Z     
2025-08-14T21:17:32.0863162Z --- Runtime Warning: 2 / 8 ---
2025-08-14T21:17:32.0863514Z example = <DocTest(torch.library Library._impl_with_aoti_compile:0 ln 247) at 0x7f46424b3680>
2025-08-14T21:17:32.0864141Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py:282: UserWarning: Warning only once for all operators,  other operators may also be overridden.
2025-08-14T21:17:32.0864471Z       Overriding a previously registered kernel for the same operator and the same dispatch key
2025-08-14T21:17:32.0864680Z       operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor
2025-08-14T21:17:32.0864990Z         registered at /var/lib/jenkins/workspace/build/aten/src/ATen/RegisterSchema.cpp:6
2025-08-14T21:17:32.0865088Z       dispatch key: CPU
2025-08-14T21:17:32.0865516Z       previous kernel: registered at /var/lib/jenkins/workspace/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079
2025-08-14T21:17:32.0866081Z            new kernel: registered at /dev/null:811 (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/core/dispatch/OperatorEntry.cpp:225.)
2025-08-14T21:17:32.0866245Z       impl_fn(self.ns, name.split("::")[-1], dispatch_key)
2025-08-14T21:17:32.0866325Z     
2025-08-14T21:17:32.0866517Z --- Runtime Warning: 3 / 8 ---
2025-08-14T21:17:32.0866751Z example = <DocTest(torch.nested as_nested_tensor:0 ln 61) at 0x7f46424fe250>
2025-08-14T21:17:32.0868615Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py:117: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. We recommend specifying layout=torch.jagged when constructing a nested tensor, as this layout receives active development, has better operator coverage, and works with torch.compile. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/NestedTensorImpl.cpp:182.)
2025-08-14T21:17:32.0868862Z       return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None)
2025-08-14T21:17:32.0868958Z     
2025-08-14T21:17:32.0869135Z --- Runtime Warning: 4 / 8 ---
2025-08-14T21:17:32.0869442Z example = <DocTest(torch._functorch.eager_transforms linearize:0 ln 1704) at 0x7f46425fa470>
2025-08-14T21:17:32.0870987Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/const_fold.py:271: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add the necessary submodule, GraphModule.add_parameter to add the necessary Parameter, or nn.Module.register_buffer to add the necessary buffer
2025-08-14T21:17:32.0871152Z       new_node = root_const_gm.graph.get_attr(in_node.target)
2025-08-14T21:17:32.0871244Z     
2025-08-14T21:17:32.0871501Z --- Runtime Warning: 5 / 8 ---
2025-08-14T21:17:32.0871789Z example = <DocTest(torch.nn.modules.transformer Transformer:0 ln 90) at 0x7f46426b6be0>
2025-08-14T21:17:32.0872886Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance)
2025-08-14T21:17:32.0872985Z       warnings.warn(
2025-08-14T21:17:32.0873065Z     
2025-08-14T21:17:32.0873259Z --- Runtime Warning: 6 / 8 ---
2025-08-14T21:17:32.0873585Z example = <DocTest(torch.nn.modules.transformer TransformerEncoder:0 ln 336) at 0x7f46426b6cf0>
2025-08-14T21:17:32.0874673Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance)
2025-08-14T21:17:32.0874765Z       warnings.warn(
2025-08-14T21:17:32.0874844Z     
2025-08-14T21:17:32.0875024Z --- Runtime Warning: 7 / 8 ---
2025-08-14T21:17:32.0875361Z example = <DocTest(torch.nn.utils.weight_norm weight_norm:0 ln 134) at 0x7f46426f09e0>
2025-08-14T21:17:32.0876193Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
2025-08-14T21:17:32.0876322Z       WeightNorm.apply(module, name, dim)
2025-08-14T21:17:32.0876399Z     
2025-08-14T21:17:32.0876580Z --- Runtime Warning: 8 / 8 ---
2025-08-14T21:17:32.0876884Z example = <DocTest(torch.nn.utils.weight_norm remove_weight_norm:0 ln 156) at 0x7f46426f0af0>
2025-08-14T21:17:32.0877689Z     /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
2025-08-14T21:17:32.0877819Z       WeightNorm.apply(module, name, dim)
2025-08-14T21:17:32.0877897Z     
2025-08-14T21:17:32.0878208Z === 338 passed, 394 skipped, 154 warnings in 14.94 seconds ===
2025-08-14T21:17:32.0878433Z Running inductor/test_max_autotune 1/1 ... [2025-08-14 21:17:31.842950]
2025-08-14T21:17:32.0878543Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:32.0879426Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_max_autotune.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:31.843354]
2025-08-14T21:17:38.5570425Z 
2025-08-14T21:17:38.5571415Z inductor/test_max_autotune 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_max_autotune_1.1_76d4a6e29c875913_.log
2025-08-14T21:17:38.5572142Z 
2025-08-14T21:17:38.5574882Z Running inductor/test_flex_attention 1/1 ... [2025-08-14 21:17:38.557325]
2025-08-14T21:17:38.5575361Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:38.5579127Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_attention.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:38.557667]
2025-08-14T21:17:42.0109763Z 
2025-08-14T21:17:42.0111069Z inductor/test_flex_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_attention_1.1_9a9ba32faa0d19ee_.log
2025-08-14T21:17:42.0111910Z 
2025-08-14T21:17:42.0114214Z Running inductor/test_benchmark_fusion 1/1 ... [2025-08-14 21:17:42.011229]
2025-08-14T21:17:42.0115083Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:42.0118251Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_benchmark_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:42.011570]
2025-08-14T21:17:49.5950306Z 
2025-08-14T21:17:49.5951965Z inductor/test_benchmark_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_benchmark_fusion_1.1_d8355b5936462826_.log
2025-08-14T21:17:49.5953375Z 
2025-08-14T21:17:49.5956079Z Running inductor/test_cutlass_backend 1/1 ... [2025-08-14 21:17:49.595375]
2025-08-14T21:17:49.5956836Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:49.5961332Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cutlass_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:49.595804]
2025-08-14T21:17:56.3831878Z 
2025-08-14T21:17:56.3832899Z inductor/test_cutlass_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_backend_1.1_2d2ab7d48823fd33_.log
2025-08-14T21:17:56.3833659Z 
2025-08-14T21:17:56.3836377Z Running dynamo/test_fake_distributed 1/1 ... [2025-08-14 21:17:56.383427]
2025-08-14T21:17:56.3837040Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:56.3840343Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_fake_distributed.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:56.383794]
2025-08-14T21:17:59.6023096Z 
2025-08-14T21:17:59.6024152Z dynamo/test_fake_distributed 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fake_distributed_1.1_9c2effbd2b659a05_.log
2025-08-14T21:17:59.6024923Z 
2025-08-14T21:17:59.6027103Z Running test_cpp_api_parity 1/1 ... [2025-08-14 21:17:59.602545]
2025-08-14T21:17:59.6027553Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:17:59.6031325Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_api_parity.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:17:59.602902]
2025-08-14T21:18:09.9825456Z 
2025-08-14T21:18:09.9826800Z test_cpp_api_parity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_api_parity_1.1_22431967428023aa_.log
2025-08-14T21:18:10.0021809Z Running 488 items in this shard: test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_cuda, 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test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_dtype_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special_cuda
2025-08-14T21:18:10.0211512Z 
2025-08-14T21:18:10.0211784Z Running test_transformers_privateuse1 1/1 ... [2025-08-14 21:18:09.983803]
2025-08-14T21:18:11.6693622Z -- The CXX compiler identification is Clang 12.0.1
2025-08-14T21:18:11.7894221Z -- The C compiler identification is Clang 12.0.1
2025-08-14T21:18:11.8129148Z -- Detecting CXX compiler ABI info
2025-08-14T21:18:12.0179169Z -- Detecting CXX compiler ABI info - done
2025-08-14T21:18:12.0315358Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped
2025-08-14T21:18:12.0324613Z -- Detecting CXX compile features
2025-08-14T21:18:12.0337548Z -- Detecting CXX compile features - done
2025-08-14T21:18:12.0533840Z -- Detecting C compiler ABI info
2025-08-14T21:18:12.1692491Z -- Detecting C compiler ABI info - done
2025-08-14T21:18:12.1821174Z -- Check for working C compiler: /opt/cache/bin/cc - skipped
2025-08-14T21:18:12.1824033Z -- Detecting C compile features
2025-08-14T21:18:12.1828415Z -- Detecting C compile features - done
2025-08-14T21:18:12.5149522Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message):
2025-08-14T21:18:12.5150378Z   static library kineto_LIBRARY-NOTFOUND not found.
2025-08-14T21:18:12.5150749Z Call Stack (most recent call first):
2025-08-14T21:18:12.5151531Z   /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found)
2025-08-14T21:18:12.5152262Z   CMakeLists.txt:27 (find_package)
2025-08-14T21:18:12.5152470Z 
2025-08-14T21:18:12.5152588Z 
2025-08-14T21:18:12.5157355Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so
2025-08-14T21:18:12.5257181Z -- Configuring done (1.1s)
2025-08-14T21:18:12.5379351Z -- Generating done (0.0s)
2025-08-14T21:18:12.5397072Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build
2025-08-14T21:18:12.6852889Z [  5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o
2025-08-14T21:18:12.6854355Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o
2025-08-14T21:18:12.7887452Z [ 17%] Linking CXX shared library libopenreg.so
2025-08-14T21:18:12.8724836Z [ 17%] Built target openreg
2025-08-14T21:18:12.8822173Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o
2025-08-14T21:18:12.8823651Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o
2025-08-14T21:18:12.8836414Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o
2025-08-14T21:18:12.8837886Z [ 41%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o
2025-08-14T21:18:12.8839462Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o
2025-08-14T21:18:12.8841046Z [ 52%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o
2025-08-14T21:18:12.8841962Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o
2025-08-14T21:18:12.8846614Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o
2025-08-14T21:18:13.0696170Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o
2025-08-14T21:18:13.0844672Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o
2025-08-14T21:18:13.1474269Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o
2025-08-14T21:18:13.5978900Z [ 88%] Linking CXX shared library libtorch_openreg.so
2025-08-14T21:18:14.0927245Z [ 88%] Built target torch_openreg
2025-08-14T21:18:14.1013287Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o
2025-08-14T21:18:14.6955719Z [100%] Linking CXX shared library libtorch_bindings.so
2025-08-14T21:18:14.8562815Z [100%] Built target torch_bindings
2025-08-14T21:18:14.8631898Z Install the project...
2025-08-14T21:18:14.8658648Z -- Install configuration: ""
2025-08-14T21:18:14.9314752Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/config/_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated
2025-08-14T21:18:14.9315705Z !!
2025-08-14T21:18:14.9315821Z 
2025-08-14T21:18:14.9315981Z         ********************************************************************************
2025-08-14T21:18:14.9316840Z         Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0).
2025-08-14T21:18:14.9317576Z 
2025-08-14T21:18:14.9317806Z         By 2026-Feb-18, you need to update your project and remove deprecated calls
2025-08-14T21:18:14.9318553Z         or your builds will no longer be supported.
2025-08-14T21:18:14.9318850Z 
2025-08-14T21:18:14.9319245Z         See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details.
2025-08-14T21:18:14.9319830Z         ********************************************************************************
2025-08-14T21:18:14.9320083Z 
2025-08-14T21:18:14.9320165Z !!
2025-08-14T21:18:14.9320387Z   corresp(dist, value, root_dir)
2025-08-14T21:18:14.9819419Z running install
2025-08-14T21:18:14.9833628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:18:14.9834425Z !!
2025-08-14T21:18:14.9834537Z 
2025-08-14T21:18:14.9834673Z         ********************************************************************************
2025-08-14T21:18:14.9835062Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:18:14.9835474Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:18:14.9835854Z         standards-based tools.
2025-08-14T21:18:14.9836050Z 
2025-08-14T21:18:14.9836277Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:18:14.9836766Z         or your builds will no longer be supported.
2025-08-14T21:18:14.9837025Z 
2025-08-14T21:18:14.9837323Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:18:14.9837858Z         ********************************************************************************
2025-08-14T21:18:14.9838099Z 
2025-08-14T21:18:14.9838183Z !!
2025-08-14T21:18:14.9838410Z   self.initialize_options()
2025-08-14T21:18:14.9967457Z running build
2025-08-14T21:18:14.9967736Z running build_py
2025-08-14T21:18:15.0049181Z creating build/lib.linux-x86_64-cpython-313/torch_openreg
2025-08-14T21:18:15.0051469Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg
2025-08-14T21:18:15.0059936Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:18:15.0061440Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:18:15.0068833Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:18:15.0078859Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:18:15.0079776Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:18:15.0095430Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:18:15.0218718Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:18:15.0258628Z running build_ext
2025-08-14T21:18:15.0379075Z building 'torch_openreg._C' extension
2025-08-14T21:18:15.0380216Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc
2025-08-14T21:18:15.0383819Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -g -Wall -Werror
2025-08-14T21:18:15.1987502Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib
2025-08-14T21:18:15.2248144Z running install_lib
2025-08-14T21:18:15.2329427Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages
2025-08-14T21:18:15.2332402Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg
2025-08-14T21:18:15.2333889Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg
2025-08-14T21:18:15.2335874Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg
2025-08-14T21:18:15.2337145Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg
2025-08-14T21:18:15.2339153Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/random.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg
2025-08-14T21:18:15.2340318Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:18:15.2341915Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:18:15.2344273Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:18:15.2365489Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:18:15.2371138Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg
2025-08-14T21:18:15.2377735Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/__init__.py to __init__.cpython-313.pyc
2025-08-14T21:18:15.2381418Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/__init__.py to __init__.cpython-313.pyc
2025-08-14T21:18:15.2387934Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/random.py to random.cpython-313.pyc
2025-08-14T21:18:15.2393696Z running install_egg_info
2025-08-14T21:18:15.2556141Z running egg_info
2025-08-14T21:18:15.2638239Z creating torch_openreg.egg-info
2025-08-14T21:18:15.2639509Z writing torch_openreg.egg-info/PKG-INFO
2025-08-14T21:18:15.2644493Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt
2025-08-14T21:18:15.2646338Z writing requirements to torch_openreg.egg-info/requires.txt
2025-08-14T21:18:15.2647741Z writing top-level names to torch_openreg.egg-info/top_level.txt
2025-08-14T21:18:15.2649089Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt'
2025-08-14T21:18:15.2739334Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt'
2025-08-14T21:18:15.2747393Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt'
2025-08-14T21:18:15.2749193Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info
2025-08-14T21:18:15.2755726Z running install_scripts
2025-08-14T21:18:15.6639522Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:18:15.6643153Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers_privateuse1.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:18:15.664036]
2025-08-14T21:18:19.0337618Z 
2025-08-14T21:18:19.0338714Z test_transformers_privateuse1 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_privateuse1_1.1_b77e1edd558fe4b3_.log
2025-08-14T21:18:19.0341535Z Running 3 items in this shard: test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_fused_sdp_choice_privateuseone, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable_backward
2025-08-14T21:18:19.0343362Z 
2025-08-14T21:18:19.0343601Z Running test_extension_utils 1/1 ... [2025-08-14 21:18:19.033976]
2025-08-14T21:18:19.0344137Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:18:19.0345484Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_extension_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:18:19.034325]
2025-08-14T21:18:22.2028551Z 
2025-08-14T21:18:22.2029690Z test_extension_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_extension_utils_1.1_80c8ca1b418e5ed5_.log
2025-08-14T21:18:22.2031245Z Running 2 items in this shard: test/test_extension_utils.py::TestExtensionUtils::test_external_module_register, test/test_extension_utils.py::TestExtensionUtils::test_external_module_register_with_renamed_backend
2025-08-14T21:18:22.2032757Z 
2025-08-14T21:18:22.2033044Z Running test_fx 1/1 ... [2025-08-14 21:18:22.203080]
2025-08-14T21:18:22.2033425Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:18:22.2036521Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:18:22.203401]
2025-08-14T21:22:34.5482814Z 
2025-08-14T21:22:34.5485559Z test_fx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_1.1_80d085a6357221a4_.log
2025-08-14T21:22:34.5969740Z Running 1260 items in this shard: test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu, test/test_fx.py::TestCSEPass::test_banned_list, test/test_fx.py::TestCSEPass::test_empty, test/test_fx.py::TestCSEPass::test_immutable_list_multiple_entries, test/test_fx.py::TestCSEPass::test_immutable_list_type, test/test_fx.py::TestCSEPass::test_kwarg, test/test_fx.py::TestCSEPass::test_nested_immutable_list_type, test/test_fx.py::TestCSEPass::test_nochange, test/test_fx.py::TestCSEPass::test_rand_like, test/test_fx.py::TestCSEPass::test_rand_n, test/test_fx.py::TestCSEPass::test_random, test/test_fx.py::TestCSEPass::test_simple, test/test_fx.py::TestCSEPass::test_simple_2, test/test_fx.py::TestCSEPass::test_simple_multiple_same_ops, test/test_fx.py::TestCSEPass::test_two_args, test/test_fx.py::TestCSEPass::test_two_args_default, test/test_fx.py::TestDCE::test_dead_chain, test/test_fx.py::TestDCE::test_dead_getattr, test/test_fx.py::TestDCE::test_dead_placeholder, test/test_fx.py::TestDCE::test_dead_placeholder_with_user, test/test_fx.py::TestDCE::test_impure_custom, test/test_fx.py::TestDCE::test_impure_kwargs, test/test_fx.py::TestDCE::test_impure_nodes_args, test/test_fx.py::TestDCE::test_impure_random, test/test_fx.py::TestDCE::test_keep_collectives, test/test_fx.py::TestDCE::test_keep_collectives_no_overload, test/test_fx.py::TestDCE::test_keep_module_with_side_effects, test/test_fx.py::TestDCE::test_keep_setitem, test/test_fx.py::TestDCE::test_keep_torch_assert, test/test_fx.py::TestDCE::test_simple, test/test_fx.py::TestConstFold::test_check_inline_non_const, test/test_fx.py::TestConstFold::test_check_inline_non_const_mult_return, test/test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input, test/test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node, test/test_fx.py::TestConstFold::test_const_fold_module_attr, test/test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs, test/test_fx.py::TestConstFold::test_const_fold_noop, test/test_fx.py::TestConstFold::test_const_fold_submod_hierarchy, test/test_fx.py::TestConstFold::test_const_fold_tensor_meta, test/test_fx.py::TestConstFold::test_const_fold_unused_placeholder, test/test_fx.py::TestConstFold::test_dict_output, test/test_fx.py::TestConstFold::test_fold_module, test/test_fx.py::TestConstFold::test_retain_node_meta, test/test_fx.py::TestConstFold::test_three_outputs, test/test_fx.py::TestConstFold::test_two_outputs, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const, test/test_fx.py::AnnotationsTest::test_annotate, test/test_fx.py::AnnotationsTest::test_annotations, test/test_fx.py::AnnotationsTest::test_broadcasting1, test/test_fx.py::AnnotationsTest::test_broadcasting2, test/test_fx.py::AnnotationsTest::test_broadcasting3, test/test_fx.py::AnnotationsTest::test_consistency, test/test_fx.py::AnnotationsTest::test_precision, test/test_fx.py::TypeCheckerTest::test_flatten_fully_static, test/test_fx.py::TypeCheckerTest::test_resnet50, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2, test/test_fx.py::TypeCheckerTest::test_type_check_add_false, test/test_fx.py::TypeCheckerTest::test_type_check_add_true, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_types, test/test_fx.py::TypeCheckerTest::test_type_check_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_flatten3, test/test_fx.py::TypeCheckerTest::test_type_check_flatten_2, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_true, test/test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_False, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_true, test/test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static, test/test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput, test/test_fx.py::TypeCheckerTest::test_typecheck_basicblock, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_function, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_module, test/test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map, test/test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad, test/test_fx.py::TestMatcher::test_variatic_arg_matching, test/test_fx.py::TestPassManager::test_pass_manager, test/test_fx.py::TestPassManager::test_pass_manager_bad_checks, test/test_fx.py::TestPassManager::test_pass_manager_checks, test/test_fx.py::TestPassManager::test_pass_manager_error, test/test_fx.py::TestPassManager::test_this_before_that_pass_constraint, test/test_fx.py::TestPassManager::test_topological_sort, test/test_fx.py::TestSourceMatcher::test_legalize_slice, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True, test/test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg, test/test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters, test/test_fx.py::TestSubgraphRewriter::test_replaced_nodes, test/test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results, test/test_fx.py::TestFX::test_all_input_nodes, test/test_fx.py::TestFX::test_annotation_with_future, test/test_fx.py::TestFX::test_annotations_empty_tuple, test/test_fx.py::TestFX::test_annotations_with_forward_references, test/test_fx.py::TestFX::test_annotations_with_no_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references, test/test_fx.py::TestFX::test_args_kwargs, test/test_fx.py::TestFX::test_args_kwargs_no_self, test/test_fx.py::TestFX::test_assert, test/test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message, test/test_fx.py::TestFX::test_ast_rewriter_wrap, test/test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly, test/test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_autowrap_functions, test/test_fx.py::TestFX::test_concrete_arg_none_assert, test/test_fx.py::TestFX::test_construct_root_dict, test/test_fx.py::TestFX::test_control_flow_tracing, test/test_fx.py::TestFX::test_copy_it, test/test_fx.py::TestFX::test_copy_no_remap, test/test_fx.py::TestFX::test_ctx_mgr, test/test_fx.py::TestFX::test_custom_codegen, test/test_fx.py::TestFX::test_custom_codegen_with_transformer, test/test_fx.py::TestFX::test_custom_import, test/test_fx.py::TestFX::test_custom_proxy_dynamic_value, test/test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow, test/test_fx.py::TestFX::test_custom_proxy_type, test/test_fx.py::TestFX::test_custom_proxy_type_literal, test/test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule, test/test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls, test/test_fx.py::TestFX::test_deepcopy_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graphmodule_with_transform, test/test_fx.py::TestFX::test_deepcopy_no_recursion, test/test_fx.py::TestFX::test_deepcopy_recursion_depth, test/test_fx.py::TestFX::test_deepcopy_tracer, test/test_fx.py::TestFX::test_deepcopy_with_submods_params, test/test_fx.py::TestFX::test_delete_unused_submodules_leaf, test/test_fx.py::TestFX::test_delete_unused_values, test/test_fx.py::TestFX::test_dict, test/test_fx.py::TestFX::test_direct_param_use, test/test_fx.py::TestFX::test_disallow_override, test/test_fx.py::TestFX::test_ellipsis, test/test_fx.py::TestFX::test_empty_graph_codegen, test/test_fx.py::TestFX::test_enum, test/test_fx.py::TestFX::test_erase_node_error, test/test_fx.py::TestFX::test_example_shape_prop, test/test_fx.py::TestFX::test_find_uses, test/test_fx.py::TestFX::test_fn_type_annotation_empty, test/test_fx.py::TestFX::test_fn_type_annotations, test/test_fx.py::TestFX::test_fx_and_or, test/test_fx.py::TestFX::test_fx_create_arg, test/test_fx.py::TestFX::test_fx_shifts, test/test_fx.py::TestFX::test_fx_stateless, test/test_fx.py::TestFX::test_get_torch_func_signature, test/test_fx.py::TestFX::test_getitem, test/test_fx.py::TestFX::test_getitem_subproc, test/test_fx.py::TestFX::test_graph_edit_with_proxy, test/test_fx.py::TestFX::test_graph_fns, test/test_fx.py::TestFX::test_graph_module, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_dict_init, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_mod_init, test/test_fx.py::TestFX::test_graph_module_replicate_for_dp, test/test_fx.py::TestFX::test_graph_unique_names, test/test_fx.py::TestFX::test_graph_unique_names_manual, test/test_fx.py::TestFX::test_immutable_dict_pytree_ops, test/test_fx.py::TestFX::test_immutable_list_pytree_ops, test/test_fx.py::TestFX::test_imul_code_print, test/test_fx.py::TestFX::test_inf_nan, test/test_fx.py::TestFX::test_inf_nan_kwds, test/test_fx.py::TestFX::test_informative_co_filename, test/test_fx.py::TestFX::test_inline_graph, test/test_fx.py::TestFX::test_insert_arg, test/test_fx.py::TestFX::test_insertion_point, test/test_fx.py::TestFX::test_interpreter, test/test_fx.py::TestFX::test_interpreter_default_args, test/test_fx.py::TestFX::test_interpreter_gc_values, test/test_fx.py::TestFX::test_interpreter_noop_resnet18, test/test_fx.py::TestFX::test_interpreter_not_enough_args, test/test_fx.py::TestFX::test_interpreter_onthefly_swap, test/test_fx.py::TestFX::test_interpreter_other_graph, test/test_fx.py::TestFX::test_interpreter_partial_eval, test/test_fx.py::TestFX::test_interpreter_run_node_override, test/test_fx.py::TestFX::test_interpreter_star_args, test/test_fx.py::TestFX::test_interpreter_with_codegen, test/test_fx.py::TestFX::test_layout, test/test_fx.py::TestFX::test_leaf_module, test/test_fx.py::TestFX::test_lineno_map, test/test_fx.py::TestFX::test_matmul_tracing, test/test_fx.py::TestFX::test_metadata_on_ph, test/test_fx.py::TestFX::test_module_deepcopy_edit_nodes, test/test_fx.py::TestFX::test_move_before, test/test_fx.py::TestFX::test_multi_insert_point, test/test_fx.py::TestFX::test_multiple_default_args, test/test_fx.py::TestFX::test_named_tuple_inlined, test/test_fx.py::TestFX::test_namedtuple_return_qualname, test/test_fx.py::TestFX::test_namedtuple_return_trace, test/test_fx.py::TestFX::test_native_callable, test/test_fx.py::TestFX::test_nn_module_stack, test/test_fx.py::TestFX::test_no_mutation, test/test_fx.py::TestFX::test_node_tagging, test/test_fx.py::TestFX::test_nonetype_annotation, test/test_fx.py::TestFX::test_partial_trace, test/test_fx.py::TestFX::test_pickle_custom_import, test/test_fx.py::TestFX::test_pickle_graphmodule, test/test_fx.py::TestFX::test_pickle_nonetype_annotation, test/test_fx.py::TestFX::test_pickle_torch_custom_ops, test/test_fx.py::TestFX::test_prepend_self, test/test_fx.py::TestFX::test_pretty_print, test/test_fx.py::TestFX::test_pretty_print_graph, test/test_fx.py::TestFX::test_pretty_print_node, test/test_fx.py::TestFX::test_pretty_print_targets, test/test_fx.py::TestFX::test_print_graph, test/test_fx.py::TestFX::test_profiler_ranges_side_effect, test/test_fx.py::TestFX::test_proxy_deepcopy_with_tracer, test/test_fx.py::TestFX::test_proxy_deepcopy_without_tracer, test/test_fx.py::TestFX::test_pytree, test/test_fx.py::TestFX::test_pytree_concrete, test/test_fx.py::TestFX::test_reassign_args_kwargs_uses, test/test_fx.py::TestFX::test_regular_and_default_args, test/test_fx.py::TestFX::test_remove_uses, test/test_fx.py::TestFX::test_remove_uses_with_custom_filter, test/test_fx.py::TestFX::test_replace_input, test/test_fx.py::TestFX::test_replace_uses, test/test_fx.py::TestFX::test_reserved_getattr, test/test_fx.py::TestFX::test_return_tuple, test/test_fx.py::TestFX::test_return_type_exists, test/test_fx.py::TestFX::test_return_type_exists_pre_pep585, test/test_fx.py::TestFX::test_script_method_trace, test/test_fx.py::TestFX::test_script_tensor_constant, test/test_fx.py::TestFX::test_sequential, test/test_fx.py::TestFX::test_shape_prop_aggregate, test/test_fx.py::TestFX::test_shape_prop_layout, test/test_fx.py::TestFX::test_shape_prop_layout_3d, test/test_fx.py::TestFX::test_shape_prop_unbacked_sym, test/test_fx.py::TestFX::test_single_default_arg, test/test_fx.py::TestFX::test_snake_case, test/test_fx.py::TestFX::test_sqrt, test/test_fx.py::TestFX::test_stack_traces, test/test_fx.py::TestFX::test_stack_traces_with_transformer, test/test_fx.py::TestFX::test_string_literal_return, test/test_fx.py::TestFX::test_submodule_manipulation_API, test/test_fx.py::TestFX::test_symbolic_trace_assert, test/test_fx.py::TestFX::test_symbolic_trace_sequential, test/test_fx.py::TestFX::test_tensor_attribute, test/test_fx.py::TestFX::test_tensor_attribute_coalseced, test/test_fx.py::TestFX::test_tensor_constant, test/test_fx.py::TestFX::test_throw_out_variant, test/test_fx.py::TestFX::test_torch_custom_ops, test/test_fx.py::TestFX::test_torch_fx_getattr, test/test_fx.py::TestFX::test_torch_fx_len, test/test_fx.py::TestFX::test_torch_op_overloads, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_dict_int_keys, test/test_fx.py::TestFX::test_trace_dict_proxy_keys, test/test_fx.py::TestFX::test_trace_fn_constant, test/test_fx.py::TestFX::test_trace_function, test/test_fx.py::TestFX::test_trace_multiple_funcs, test/test_fx.py::TestFX::test_trace_return_dataclass, test/test_fx.py::TestFX::test_trace_return_dataclass_nested, test/test_fx.py::TestFX::test_trace_return_namedtuple, test/test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules, test/test_fx.py::TestFX::test_transformer_multi_outputs, test/test_fx.py::TestFX::test_transformer_noop, test/test_fx.py::TestFX::test_transformer_op_swap, test/test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr, test/test_fx.py::TestFX::test_tuple_no_subscript, test/test_fx.py::TestFX::test_typename_print, test/test_fx.py::TestFX::test_typename_print_pre_pep585, test/test_fx.py::TestFX::test_unpack, test/test_fx.py::TestFX::test_unpack_dict_better_error, test/test_fx.py::TestFX::test_unpack_list_better_error, test/test_fx.py::TestFX::test_update_args_api, test/test_fx.py::TestFX::test_update_args_kwargs_yells_at_you, test/test_fx.py::TestFX::test_update_kwargs_api, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_function, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_module, test/test_fx.py::TestFX::test_varargs_concrete, test/test_fx.py::TestFX::test_wrap, test/test_fx.py::TestFX::test_wrap_decorated_function, test/test_fx.py::TestFX::test_wrap_fn_directly, test/test_fx.py::TestFX::test_wrap_with_submodule, test/test_fx.py::TestFX::test_wrapped_method, test/test_fx.py::TestFX::test_wrapped_retrace, test/test_fx.py::TestFX::test_wrapped_via_decorator, test/test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_wrong_target_type, test/test_fx.py::TestFX::test_wrong_topo, test/test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function, test/test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle, test/test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag, test/test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_glu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate, test/test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div, test/test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_linear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_normalize, test/test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pad, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pdist, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_prelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu6, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_silu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmin, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softplus, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_unfold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_H_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_T_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___getitem___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___radd___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rdiv___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmatmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmod___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rpow___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rsub___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__chunk_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__softmax_backward_data_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_abs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcdiv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_decomposed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_alias_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_all_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_allclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_aminmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_angle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_any_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_arange_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argsort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argwhere_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_baddbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bernoulli_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bfloat16_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_block_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bool_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_shapes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bucketize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_byte_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cartesian_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cauchy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdouble_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ceil_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cfloat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chalf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_char_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_inverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_max_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_min_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clone_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_column_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_combinations_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_physical_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_constant_pad_nd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_contiguous_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_copysign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_corrcoef_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_count_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cov_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumulative_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_deg2rad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_embed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagflat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diff_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_digamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_floor_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_no_rounding_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_trunc_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_double_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_einsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_permuted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_equal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expm1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eye_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flip_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fliplr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flipud_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gather_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ge_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geometric_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geqrf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gradient_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_grid_sampler_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_half_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hash_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_heaviside_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogram_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogramdd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hypot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igammac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_inner_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_int_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isfinite_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isnan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isneginf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isposinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isreal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_item_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_unary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kron_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kthvalue_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ldexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_le_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lerp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lgamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cond_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_det_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eig_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_householder_product_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_slogdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svdvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vander_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vecdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vector_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log10_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log1p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logcumsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_and_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_not_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_or_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_xor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_long_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_unpack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mH_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mT_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matrix_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_maximum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_minimum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_movedim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_msort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_multinomial_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nan_to_num_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmedian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanquantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nansum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_dropout_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ne_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nextafter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_celu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_elu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_glu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_group_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardswish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_kl_div_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_prelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu6_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rrelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_selu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_silu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softplus_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softsign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_threshold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_static_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_fro_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_inf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_nuc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_in_place_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_number_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ormqr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_outer_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pca_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pinverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polar_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_positive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_quantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rad2deg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rand_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ravel_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_real_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reciprocal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_remainder_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_renorm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_interleave_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize_as__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_roll_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rot90_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_neg_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scalar_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_searchsorted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sgn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_short_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_bartlett_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_blackman_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_gaussian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hann_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_kaiser_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_nuttall_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signbit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_mm_reduce_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_airy_ai_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_entr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_erfcx_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i0e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_log_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtri_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_xlog1py_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_zeta_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_list_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_square_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_multiple_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_to_size_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_along_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensor_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensordot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_sparse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_topk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapz_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triangular_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tril_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_true_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trunc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unflatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_uniform_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_consecutive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_where_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_xlogy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zero__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_like_cpu_float32, test/test_fx.py::TestVisionTracing::test_torchvision_models_alexnet, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_base, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_tiny, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet121, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet161, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet169, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet201, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_320_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fcos_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_keypointrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssd300_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssdlite320_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b0, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b1, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b2, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b3, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b4, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b5, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b6, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_l, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_m, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_googlenet, test/test_fx.py::TestVisionTracing::test_torchvision_models_inception_v3, test/test_fx.py::TestVisionTracing::test_torchvision_models_maxvit_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_75, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_3, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_128gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet152, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet18, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet34, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_32x8d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_64x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext50_32x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_lraspp_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x2_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_1, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mc3_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v1_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r2plus1d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r3d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_s3d, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_h_14, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet101_2, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet50_2
2025-08-14T21:22:34.6442242Z 
2025-08-14T21:22:34.6442467Z Running test_fake_tensor 1/1 ... [2025-08-14 21:22:34.550322]
2025-08-14T21:22:34.6442880Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:22:34.6444075Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fake_tensor.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:22:34.551596]
2025-08-14T21:22:48.4380519Z 
2025-08-14T21:22:48.4381876Z test_fake_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fake_tensor_1.1_981062b19223a3ae_.log
2025-08-14T21:22:48.4499473Z Running 290 items in this shard: test/test_fake_tensor.py::FakeTensorTest::test__adaptive_avg_pool2d_backward, test/test_fake_tensor.py::FakeTensorTest::test_alias_call, test/test_fake_tensor.py::FakeTensorTest::test_allow_meta, test/test_fake_tensor.py::FakeTensorTest::test_aten_copy_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_index_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_slice_scatter_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_basic, test/test_fake_tensor.py::FakeTensorTest::test_batch_tensor, test/test_fake_tensor.py::FakeTensorTest::test_binary_op_type_promotion, test/test_fake_tensor.py::FakeTensorTest::test_constructor, test/test_fake_tensor.py::FakeTensorTest::test_convert_fake_to_real, test/test_fake_tensor.py::FakeTensorTest::test_cpu_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cuda_initialized, test/test_fake_tensor.py::FakeTensorTest::test_cuda_lstm, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_with_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_without_fallback, test/test_fake_tensor.py::FakeTensorTest::test_custom_op_fallback, test/test_fake_tensor.py::FakeTensorTest::test_data_dependent_operator, test/test_fake_tensor.py::FakeTensorTest::test_deepcopy, test/test_fake_tensor.py::FakeTensorTest::test_device_inplace_copy, test/test_fake_tensor.py::FakeTensorTest::test_embedding_bag_meta, test/test_fake_tensor.py::FakeTensorTest::test_export_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fake_device, test/test_fake_tensor.py::FakeTensorTest::test_fake_dispatch_keys, test/test_fake_tensor.py::FakeTensorTest::test_fake_grad_copy, test/test_fake_tensor.py::FakeTensorTest::test_fake_mode_error, test/test_fake_tensor.py::FakeTensorTest::test_fast_div, test/test_fake_tensor.py::FakeTensorTest::test_from_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fsdp_flat_param, test/test_fake_tensor.py::FakeTensorTest::test_full, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex128, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int16, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int8, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_uint8, test/test_fake_tensor.py::FakeTensorTest::test_index_put_error, test/test_fake_tensor.py::FakeTensorTest::test_jagged_fake_to_fake_preserved, test/test_fake_tensor.py::FakeTensorTest::test_like_constructor, test/test_fake_tensor.py::FakeTensorTest::test_mixed_real_and_fake_inputs, test/test_fake_tensor.py::FakeTensorTest::test_mode, test/test_fake_tensor.py::FakeTensorTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorTest::test_nanmean_out, test/test_fake_tensor.py::FakeTensorTest::test_new, test/test_fake_tensor.py::FakeTensorTest::test_no_tag_func, test/test_fake_tensor.py::FakeTensorTest::test_non_kwarg_device, test/test_fake_tensor.py::FakeTensorTest::test_non_overlapping_stride_zero, test/test_fake_tensor.py::FakeTensorTest::test_non_parameter_grad, test/test_fake_tensor.py::FakeTensorTest::test_normalize_device, test/test_fake_tensor.py::FakeTensorTest::test_op_with_zero_dim_bypassed, test/test_fake_tensor.py::FakeTensorTest::test_out_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_parameter_instantiation, test/test_fake_tensor.py::FakeTensorTest::test_parameter_view, test/test_fake_tensor.py::FakeTensorTest::test_print_in_fake_mode, test/test_fake_tensor.py::FakeTensorTest::test_randperm, test/test_fake_tensor.py::FakeTensorTest::test_recursive_invocation, test/test_fake_tensor.py::FakeTensorTest::test_repr, test/test_fake_tensor.py::FakeTensorTest::test_same_shape_env_preserved, test/test_fake_tensor.py::FakeTensorTest::test_scalar_inputs, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_False, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_True, test/test_fake_tensor.py::FakeTensorTest::test_setitem, test/test_fake_tensor.py::FakeTensorTest::test_shape_take_not_device, test/test_fake_tensor.py::FakeTensorTest::test_split_return_self, test/test_fake_tensor.py::FakeTensorTest::test_throw, test/test_fake_tensor.py::FakeTensorTest::test_tolist, test/test_fake_tensor.py::FakeTensorTest::test_type_as, test/test_fake_tensor.py::FakeTensorTest::test_unbind_copy_out, test/test_fake_tensor.py::FakeTensorTest::test_unsqueeze_copy, test/test_fake_tensor.py::FakeTensorTest::test_upsample_bilinear_small_channels, test/test_fake_tensor.py::FakeTensorTest::test_zero_dim, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test__adaptive_avg_pool2d_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_alias_call_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_allow_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_copy_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_index_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_slice_scatter_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_basic_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_batch_tensor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_binary_op_type_promotion_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_convert_fake_to_real_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cpu_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_initialized_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_lstm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_with_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_without_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_custom_op_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_data_dependent_operator_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_deepcopy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_device_inplace_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_embedding_bag_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_export_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_dispatch_keys_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_grad_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fast_div_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_from_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fsdp_flat_param_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_full_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex128_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int16_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_uint8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_put_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_jagged_fake_to_fake_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_like_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mixed_real_and_fake_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nanmean_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_no_tag_func_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_overlapping_stride_zero_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_parameter_grad_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_normalize_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_op_with_zero_dim_bypassed_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_out_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_instantiation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_print_in_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_randperm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_recursive_invocation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_repr_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_same_shape_env_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scalar_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_False_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_True_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_setitem_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_shape_take_not_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_split_return_self_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_throw_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_tolist_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_type_as_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unbind_copy_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unsqueeze_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_upsample_bilinear_small_channels_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_zero_dim_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorConstHandling::test_aliased_const_write, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_propagate_through_functions, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_batch_norm_cpu, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_in_intlist_repro, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_add, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_view_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storage_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storages, test/test_fake_tensor.py::FakeTensorConstHandling::test_simple, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_aliased_const_write_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_propagate_through_functions_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_batch_norm_cpu_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_in_intlist_repro_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_add_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_view_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storage_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storages_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_simple_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_key, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_weak_ref, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_from_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_to_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_multiple_modes, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_active_mode, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_ref_cycle, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_mode_error, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_non_view, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_view, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_key_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_weak_ref_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_from_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_to_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_multiple_modes_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_active_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_ref_cycle_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_non_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_view_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_conv_c1_backward, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_cross_entropy_loss, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_embedding_bag_private, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_fake_gpu_no_init, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_flash_attention, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_like_ops, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_no_dispatch_with_like_function, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_non_kwarg_only_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_sparse_new, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_str_storage, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_new, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_conv_c1_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_cross_entropy_loss_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_embedding_bag_private_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_fake_gpu_no_init_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_flash_attention_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_like_ops_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_module_to_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_no_dispatch_with_like_function_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_non_kwarg_only_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_sparse_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_str_storage_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_new_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args, test/test_fake_tensor.py::FakeTensorPropTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorPropTest::test_nonzero_stride, test/test_fake_tensor.py::FakeTensorPropTest::test_torch_load_with_fake_mode, test/test_fake_tensor.py::FakeTensorPropTest::test_unbacked_shape_realloc, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nonzero_stride_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_torch_load_with_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_unbacked_shape_realloc_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization_with_tracing, test/test_fake_tensor.py::FakeTensorDispatchCache::test__upsample_bilinear2d_aa_backward_dynamic_shapes, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_aten_index, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_bypass, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_dispatch_key_set, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_hit, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_inplace_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_constants, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_conj, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_inference, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_neg, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_memory_format, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_requires_grad, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_shape, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_storage_offset, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_stride, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_tuple_outputs, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_view_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_fft_hfft2_issue145522, test/test_fake_tensor.py::FakeTensorDispatchCache::test_from_buffer, test/test_fake_tensor.py::FakeTensorDispatchCache::test_inference_mode, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph_cacheable_inplace, test/test_fake_tensor.py::FakeTensorDispatchCache::test_meta_tensor_to_fake_cpu, test/test_fake_tensor.py::FakeTensorDispatchCache::test_shape_env_settings, test/test_fake_tensor.py::FakeTensorDispatchCache::test_unbacked_output, test/test_fake_tensor.py::FakeTensorDispatchCache::test_wrapper_tensor_subclass_different_device, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type_cpu_only
2025-08-14T21:22:48.4615519Z 
2025-08-14T21:22:48.4615717Z Running test_openreg 1/1 ... [2025-08-14 21:22:48.438768]
2025-08-14T21:22:50.2657904Z -- The CXX compiler identification is Clang 12.0.1
2025-08-14T21:22:50.3476328Z -- The C compiler identification is Clang 12.0.1
2025-08-14T21:22:50.3580130Z -- Detecting CXX compiler ABI info
2025-08-14T21:22:50.6551326Z -- Detecting CXX compiler ABI info - done
2025-08-14T21:22:50.6686919Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped
2025-08-14T21:22:50.6690375Z -- Detecting CXX compile features
2025-08-14T21:22:50.6696544Z -- Detecting CXX compile features - done
2025-08-14T21:22:50.6872288Z -- Detecting C compiler ABI info
2025-08-14T21:22:50.8053672Z -- Detecting C compiler ABI info - done
2025-08-14T21:22:50.8181077Z -- Check for working C compiler: /opt/cache/bin/cc - skipped
2025-08-14T21:22:50.8184662Z -- Detecting C compile features
2025-08-14T21:22:50.8189158Z -- Detecting C compile features - done
2025-08-14T21:22:50.9320521Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message):
2025-08-14T21:22:50.9321412Z   static library kineto_LIBRARY-NOTFOUND not found.
2025-08-14T21:22:50.9321826Z Call Stack (most recent call first):
2025-08-14T21:22:50.9322616Z   /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found)
2025-08-14T21:22:50.9323418Z   CMakeLists.txt:27 (find_package)
2025-08-14T21:22:50.9323877Z 
2025-08-14T21:22:50.9324009Z 
2025-08-14T21:22:50.9329002Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so
2025-08-14T21:22:50.9389368Z -- Configuring done (1.2s)
2025-08-14T21:22:50.9515772Z -- Generating done (0.0s)
2025-08-14T21:22:50.9529993Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build
2025-08-14T21:22:51.1014588Z [  5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o
2025-08-14T21:22:51.1016224Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o
2025-08-14T21:22:51.2147479Z [ 17%] Linking CXX shared library libopenreg.so
2025-08-14T21:22:51.2964630Z [ 17%] Built target openreg
2025-08-14T21:22:51.3059089Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o
2025-08-14T21:22:51.3063829Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o
2025-08-14T21:22:51.3070102Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o
2025-08-14T21:22:51.3072596Z [ 41%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o
2025-08-14T21:22:51.3078133Z [ 52%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o
2025-08-14T21:22:51.3079833Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o
2025-08-14T21:22:51.3081303Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o
2025-08-14T21:22:51.3083274Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o
2025-08-14T21:22:51.4965184Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o
2025-08-14T21:22:51.5384500Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o
2025-08-14T21:22:51.5691461Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o
2025-08-14T21:22:53.3092644Z [ 88%] Linking CXX shared library libtorch_openreg.so
2025-08-14T21:22:53.8040500Z [ 88%] Built target torch_openreg
2025-08-14T21:22:53.8125047Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o
2025-08-14T21:22:55.1102188Z [100%] Linking CXX shared library libtorch_bindings.so
2025-08-14T21:22:55.2638442Z [100%] Built target torch_bindings
2025-08-14T21:22:55.2705105Z Install the project...
2025-08-14T21:22:55.2731559Z -- Install configuration: ""
2025-08-14T21:22:55.3381363Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/config/_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated
2025-08-14T21:22:55.3382781Z !!
2025-08-14T21:22:55.3383033Z 
2025-08-14T21:22:55.3383283Z         ********************************************************************************
2025-08-14T21:22:55.3384269Z         Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0).
2025-08-14T21:22:55.3384994Z 
2025-08-14T21:22:55.3385227Z         By 2026-Feb-18, you need to update your project and remove deprecated calls
2025-08-14T21:22:55.3385734Z         or your builds will no longer be supported.
2025-08-14T21:22:55.3385978Z 
2025-08-14T21:22:55.3386367Z         See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details.
2025-08-14T21:22:55.3386979Z         ********************************************************************************
2025-08-14T21:22:55.3387222Z 
2025-08-14T21:22:55.3387303Z !!
2025-08-14T21:22:55.3387528Z   corresp(dist, value, root_dir)
2025-08-14T21:22:55.3828487Z running install
2025-08-14T21:22:55.3842710Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:22:55.3843620Z !!
2025-08-14T21:22:55.3843746Z 
2025-08-14T21:22:55.3843871Z         ********************************************************************************
2025-08-14T21:22:55.3844312Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:22:55.3844738Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:22:55.3845178Z         standards-based tools.
2025-08-14T21:22:55.3845383Z 
2025-08-14T21:22:55.3845613Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:22:55.3846167Z         or your builds will no longer be supported.
2025-08-14T21:22:55.3846413Z 
2025-08-14T21:22:55.3846772Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:22:55.3847330Z         ********************************************************************************
2025-08-14T21:22:55.3847606Z 
2025-08-14T21:22:55.3847701Z !!
2025-08-14T21:22:55.3847913Z   self.initialize_options()
2025-08-14T21:22:55.3981627Z running build
2025-08-14T21:22:55.3982065Z running build_py
2025-08-14T21:22:55.4066597Z creating build/lib.linux-x86_64-cpython-313/torch_openreg
2025-08-14T21:22:55.4068785Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg
2025-08-14T21:22:55.4077375Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:22:55.4078724Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:22:55.4086604Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg
2025-08-14T21:22:55.4098075Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:22:55.4099494Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:22:55.4114349Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:22:55.4235744Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib
2025-08-14T21:22:55.4276739Z running build_ext
2025-08-14T21:22:55.4396592Z building 'torch_openreg._C' extension
2025-08-14T21:22:55.4398516Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc
2025-08-14T21:22:55.4402470Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -g -Wall -Werror
2025-08-14T21:22:55.5350930Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib
2025-08-14T21:22:55.5582601Z running install_lib
2025-08-14T21:22:55.5668986Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:22:55.5671688Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:22:55.5693390Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib
2025-08-14T21:22:55.5700023Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg
2025-08-14T21:22:55.5713976Z running install_egg_info
2025-08-14T21:22:55.5877185Z running egg_info
2025-08-14T21:22:55.5957772Z writing torch_openreg.egg-info/PKG-INFO
2025-08-14T21:22:55.5962298Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt
2025-08-14T21:22:55.5964724Z writing requirements to torch_openreg.egg-info/requires.txt
2025-08-14T21:22:55.5965880Z writing top-level names to torch_openreg.egg-info/top_level.txt
2025-08-14T21:22:55.6054585Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt'
2025-08-14T21:22:55.6071341Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt'
2025-08-14T21:22:55.6073175Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info' (and everything under it)
2025-08-14T21:22:55.6074920Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info
2025-08-14T21:22:55.6081182Z running install_scripts
2025-08-14T21:22:55.9065949Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:22:55.9069233Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_openreg.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:22:55.906639]
2025-08-14T21:23:00.7277410Z 
2025-08-14T21:23:00.7278497Z test_openreg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openreg_1.1_87129c0e8d72dfea_.log
2025-08-14T21:23:00.7290830Z Running 44 items in this shard: test/test_openreg.py::TestPrivateUse1::test_backend_dispatchstub, test/test_openreg.py::TestPrivateUse1::test_backend_generate_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_function, test/test_openreg.py::TestPrivateUse1::test_backend_module_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_registration, test/test_openreg.py::TestPrivateUse1::test_backend_name, test/test_openreg.py::TestPrivateUse1::test_backend_operator_registration, test/test_openreg.py::TestPrivateUse1::test_backend_packed_sequence_methods, test/test_openreg.py::TestPrivateUse1::test_backend_storage_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_type, test/test_openreg.py::TestPrivateUse1::test_backend_type_methods, test/test_openreg.py::TestOpenReg::test_autograd_init, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_aliasing, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_returns_self, test/test_openreg.py::TestOpenReg::test_copy_same_device, test/test_openreg.py::TestOpenReg::test_cross_device_copy, test/test_openreg.py::TestOpenReg::test_cross_diff_devices_copy, test/test_openreg.py::TestOpenReg::test_data_dependent_output, test/test_openreg.py::TestOpenReg::test_event_elapsed_time, test/test_openreg.py::TestOpenReg::test_event_wait_stream, test/test_openreg.py::TestOpenReg::test_expand, test/test_openreg.py::TestOpenReg::test_factory, test/test_openreg.py::TestOpenReg::test_fake_tensor, test/test_openreg.py::TestOpenReg::test_generator, test/test_openreg.py::TestOpenReg::test_manual_seed, test/test_openreg.py::TestOpenReg::test_named_tensor, test/test_openreg.py::TestOpenReg::test_open_device_cpu_serialization, test/test_openreg.py::TestOpenReg::test_open_device_dlpack, test/test_openreg.py::TestOpenReg::test_open_device_numpy_serialization, test/test_openreg.py::TestOpenReg::test_pin_memory, test/test_openreg.py::TestOpenReg::test_printing, test/test_openreg.py::TestOpenReg::test_quantize, test/test_openreg.py::TestOpenReg::test_record_event, test/test_openreg.py::TestOpenReg::test_resize, test/test_openreg.py::TestOpenReg::test_rewrapped_storage, test/test_openreg.py::TestOpenReg::test_rng_state, test/test_openreg.py::TestOpenReg::test_scalar_type_fallback, test/test_openreg.py::TestOpenReg::test_serialization, test/test_openreg.py::TestOpenReg::test_stream_synchronize, test/test_openreg.py::TestOpenReg::test_stream_wait_event, test/test_openreg.py::TestOpenReg::test_stream_wait_stream, test/test_openreg.py::TestOpenReg::test_tensor_type_fallback, test/test_openreg.py::TestOpenReg::test_tensorlist_type_fallback
2025-08-14T21:23:00.7302122Z 
2025-08-14T21:23:00.7302327Z Running test_show_pickle 1/1 ... [2025-08-14 21:23:00.727946]
2025-08-14T21:23:00.7302726Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:23:00.7303766Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_show_pickle.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:23:00.728312]
2025-08-14T21:23:03.9469635Z 
2025-08-14T21:23:03.9470495Z test_show_pickle 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_show_pickle_1.1_a966366faba01cd4_.log
2025-08-14T21:23:03.9471454Z Running 1 items in this shard: test/test_show_pickle.py::TestShowPickle::test_scripted_model
2025-08-14T21:23:03.9471957Z 
2025-08-14T21:23:03.9473691Z Running test_tensorexpr 1/1 ... [2025-08-14 21:23:03.947186]
2025-08-14T21:23:03.9474179Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:23:03.9477235Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:23:03.947504]
2025-08-14T21:23:25.1407405Z 
2025-08-14T21:23:25.1408696Z test_tensorexpr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_1.1_9bb351c8ecaff79d_.log
2025-08-14T21:23:25.1432015Z Running 74 items in this shard: test/test_tensorexpr.py::TestTensorExprFuser::test_add_const_rhs, test/test_tensorexpr.py::TestTensorExprFuser::test_add_sub, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_input_and_module, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_module, test/test_tensorexpr.py::TestTensorExprFuser::test_all_combos, test/test_tensorexpr.py::TestTensorExprFuser::test_alpha, test/test_tensorexpr.py::TestTensorExprFuser::test_binary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_bitwise_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast3, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_2, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_big2, test/test_tensorexpr.py::TestTensorExprFuser::test_cat, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_empty_tensors, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_negative_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_only, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_promote_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_with_constant_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_char, test/test_tensorexpr.py::TestTensorExprFuser::test_chunk, test/test_tensorexpr.py::TestTensorExprFuser::test_clamp, test/test_tensorexpr.py::TestTensorExprFuser::test_constant, test/test_tensorexpr.py::TestTensorExprFuser::test_double, test/test_tensorexpr.py::TestTensorExprFuser::test_double_intrinsics, test/test_tensorexpr.py::TestTensorExprFuser::test_dynamic_shape, test/test_tensorexpr.py::TestTensorExprFuser::test_easy, test/test_tensorexpr.py::TestTensorExprFuser::test_eq, test/test_tensorexpr.py::TestTensorExprFuser::test_exp_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_four_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_ge, test/test_tensorexpr.py::TestTensorExprFuser::test_gt, test/test_tensorexpr.py::TestTensorExprFuser::test_guard_fails, test/test_tensorexpr.py::TestTensorExprFuser::test_half_bn_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_half_gelu, test/test_tensorexpr.py::TestTensorExprFuser::test_int64_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_int_output, test/test_tensorexpr.py::TestTensorExprFuser::test_le, test/test_tensorexpr.py::TestTensorExprFuser::test_loop, test/test_tensorexpr.py::TestTensorExprFuser::test_lt, test/test_tensorexpr.py::TestTensorExprFuser::test_mask, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction2, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1_2, test/test_tensorexpr.py::TestTensorExprFuser::test_multi_rand, test/test_tensorexpr.py::TestTensorExprFuser::test_multioutput, test/test_tensorexpr.py::TestTensorExprFuser::test_multiple_outputs, test/test_tensorexpr.py::TestTensorExprFuser::test_nans, test/test_tensorexpr.py::TestTensorExprFuser::test_ne, test/test_tensorexpr.py::TestTensorExprFuser::test_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_propagated_mem_layout, test/test_tensorexpr.py::TestTensorExprFuser::test_rand_like, test/test_tensorexpr.py::TestTensorExprFuser::test_rank_two, test/test_tensorexpr.py::TestTensorExprFuser::test_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_remainder, test/test_tensorexpr.py::TestTensorExprFuser::test_reps, test/test_tensorexpr.py::TestTensorExprFuser::test_round_2, test/test_tensorexpr.py::TestTensorExprFuser::test_scalar, test/test_tensorexpr.py::TestTensorExprFuser::test_short, test/test_tensorexpr.py::TestTensorExprFuser::test_simple_add, test/test_tensorexpr.py::TestTensorExprFuser::test_sin_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_slice, test/test_tensorexpr.py::TestTensorExprFuser::test_sliced_stride, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cpu, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cuda, test/test_tensorexpr.py::TestTensorExprFuser::test_strided_output_preserved, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg2, test/test_tensorexpr.py::TestTensorExprFuser::test_transpose, test/test_tensorexpr.py::TestTensorExprFuser::test_unary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_unsqueeze, test/test_tensorexpr.py::TestTensorExprFuser::test_where
2025-08-14T21:23:25.1452423Z 
2025-08-14T21:23:25.1452600Z Running test_torch 1/1 ... [2025-08-14 21:23:25.141108]
2025-08-14T21:23:25.1452992Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:23:25.1453998Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_torch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:23:25.141463]
2025-08-14T21:23:46.2388431Z 
2025-08-14T21:23:46.2389266Z test_torch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_torch_1.1_10c0dca9f0b5ebd9_.log
2025-08-14T21:23:46.2726409Z Running 1045 items in this shard: test/test_torch.py::TestBasicVitalSigns::test_basic_vitals, test/test_torch.py::TestBasicVitalSigns::test_basic_vitals_read_write, test/test_torch.py::TestBasicVitalSigns::test_dataloader_vitals, test/test_torch.py::TestTorch::test_RNGState, test/test_torch.py::TestTorch::test_RNGStateAliasing, test/test_torch.py::TestTorch::test_RNG_after_pickle, test/test_torch.py::TestTorch::test_Size, test/test_torch.py::TestTorch::test_Size_concat_non_tuple_sequence, test/test_torch.py::TestTorch::test_Size_concat_wildcard, test/test_torch.py::TestTorch::test_Size_iter, test/test_torch.py::TestTorch::test_Size_scalar, test/test_torch.py::TestTorch::test_add_meta_scalar, test/test_torch.py::TestTorch::test_allow_tensor_metadata_change, test/test_torch.py::TestTorch::test_apply, test/test_torch.py::TestTorch::test_as_subclass, test/test_torch.py::TestTorch::test_assert_async, test/test_torch.py::TestTorch::test_backward_hooks_traverse, test/test_torch.py::TestTorch::test_batch_norm_cpu_inference, test/test_torch.py::TestTorch::test_bf16_supported_on_cpu, test/test_torch.py::TestTorch::test_bmm_multithreaded, test/test_torch.py::TestTorch::test_boxMullerState, test/test_torch.py::TestTorch::test_cat_neg_dim, test/test_torch.py::TestTorch::test_check, test/test_torch.py::TestTorch::test_chunk_neg_dim, test/test_torch.py::TestTorch::test_conj_neg_tolist, test/test_torch.py::TestTorch::test_conj_physical_meta_stride, test/test_torch.py::TestTorch::test_contains, test/test_torch.py::TestTorch::test_copy_broadcast, test/test_torch.py::TestTorch::test_copy_dtypes, test/test_torch.py::TestTorch::test_copy_float16, test/test_torch.py::TestTorch::test_copy_many_to_one, test/test_torch.py::TestTorch::test_copy_transpose, test/test_torch.py::TestTorch::test_cuda_not_built, test/test_torch.py::TestTorch::test_cummax_neg_dim, test/test_torch.py::TestTorch::test_cummin_neg_dim, test/test_torch.py::TestTorch::test_cumprod_neg_dim, test/test_torch.py::TestTorch::test_cumsum_neg_dim, test/test_torch.py::TestTorch::test_cxx_flags, test/test_torch.py::TestTorch::test_data_ptr_of_empty_tensor_with_storage, test/test_torch.py::TestTorch::test_data_ptr_of_empty_view_with_storage, test/test_torch.py::TestTorch::test_deepcopy_gradient, test/test_torch.py::TestTorch::test_deepcopy_parameter, test/test_torch.py::TestTorch::test_deterministic_fill_uninitialized_memory, test/test_torch.py::TestTorch::test_deterministic_flag, test/test_torch.py::TestTorch::test_device, test/test_torch.py::TestTorch::test_dim_order, test/test_torch.py::TestTorch::test_dir, test/test_torch.py::TestTorch::test_doc, test/test_torch.py::TestTorch::test_doc_template, test/test_torch.py::TestTorch::test_dot_data_use, test/test_torch.py::TestTorch::test_dtype_is_signed, test/test_torch.py::TestTorch::test_element_size, test/test_torch.py::TestTorch::test_empty_meta, test/test_torch.py::TestTorch::test_empty_storage_view, test/test_torch.py::TestTorch::test_equal, test/test_torch.py::TestTorch::test_error_msg_type_translation, test/test_torch.py::TestTorch::test_fill_diagonal, test/test_torch.py::TestTorch::test_format_scalar_meta, test/test_torch.py::TestTorch::test_from_buffer, test/test_torch.py::TestTorch::test_from_file, test/test_torch.py::TestTorch::test_gather_neg_dim, test/test_torch.py::TestTorch::test_generator_cpu, test/test_torch.py::TestTorch::test_get_cpu_capability, test/test_torch.py::TestTorch::test_has_internal_overlap, test/test_torch.py::TestTorch::test_has_storage, test/test_torch.py::TestTorch::test_index_add, test/test_torch.py::TestTorch::test_index_add_all_dtypes, test/test_torch.py::TestTorch::test_index_add_cornercase, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_neg_dim, test/test_torch.py::TestTorch::test_index_copy_neg_dim, test/test_torch.py::TestTorch::test_index_fill_neg_dim, test/test_torch.py::TestTorch::test_index_select_neg_dim, test/test_torch.py::TestTorch::test_invalid_arg_error_handling, test/test_torch.py::TestTorch::test_invalid_generator_raises, test/test_torch.py::TestTorch::test_is_nonzero, test/test_torch.py::TestTorch::test_is_same_size, test/test_torch.py::TestTorch::test_iter, test/test_torch.py::TestTorch::test_kthvalue_neg_dim, test/test_torch.py::TestTorch::test_linspace_logspace, test/test_torch.py::TestTorch::test_logcumsumexp_neg_dim, test/test_torch.py::TestTorch::test_manual_seed, test/test_torch.py::TestTorch::test_map, test/test_torch.py::TestTorch::test_map2, test/test_torch.py::TestTorch::test_max_neg_dim, test/test_torch.py::TestTorch::test_mean_neg_dim, test/test_torch.py::TestTorch::test_median_neg_dim, test/test_torch.py::TestTorch::test_memory_format, test/test_torch.py::TestTorch::test_memory_format_contiguous_returns_same_tensor_if_already_satisfies, test/test_torch.py::TestTorch::test_memory_format_empty, test/test_torch.py::TestTorch::test_min_neg_dim, test/test_torch.py::TestTorch::test_mode_neg_dim, test/test_torch.py::TestTorch::test_multinomial_invalid_probs, test/test_torch.py::TestTorch::test_nanmedian_neg_dim, test/test_torch.py::TestTorch::test_narrow_neg_dim, test/test_torch.py::TestTorch::test_nbytes, test/test_torch.py::TestTorch::test_ndim, test/test_torch.py::TestTorch::test_new, test/test_torch.py::TestTorch::test_newaxis_numpy_comparison, test/test_torch.py::TestTorch::test_newindex, test/test_torch.py::TestTorch::test_no_cuda_monkeypatch, test/test_torch.py::TestTorch::test_norm_neg_dim, test/test_torch.py::TestTorch::test_normal_shape, test/test_torch.py::TestTorch::test_numel, test/test_torch.py::TestTorch::test_parallel_info, test/test_torch.py::TestTorch::test_parsing_double, test/test_torch.py::TestTorch::test_parsing_int64, test/test_torch.py::TestTorch::test_parsing_intlist, test/test_torch.py::TestTorch::test_permute, test/test_torch.py::TestTorch::test_pickle, test/test_torch.py::TestTorch::test_pickle_dtype, test/test_torch.py::TestTorch::test_pickle_function, test/test_torch.py::TestTorch::test_pickle_generator, test/test_torch.py::TestTorch::test_pickle_parameter, test/test_torch.py::TestTorch::test_pickle_parameter_no_requires_grad, test/test_torch.py::TestTorch::test_pickle_size, test/test_torch.py::TestTorch::test_pin_memory, test/test_torch.py::TestTorch::test_print, test/test_torch.py::TestTorch::test_prod_neg_dim, test/test_torch.py::TestTorch::test_pyobj_preserved, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_renorm_neg_dim, test/test_torch.py::TestTorch::test_resizable, test/test_torch.py::TestTorch::test_reversed, test/test_torch.py::TestTorch::test_scatter_neg_dim, test/test_torch.py::TestTorch::test_select_neg_dim, test/test_torch.py::TestTorch::test_set_flush_denormal, test/test_torch.py::TestTorch::test_setting_real_imag_to_a_number, test/test_torch.py::TestTorch::test_show_config, test/test_torch.py::TestTorch::test_size_neg_dim, test/test_torch.py::TestTorch::test_size_stride, test/test_torch.py::TestTorch::test_sizeof, test/test_torch.py::TestTorch::test_slice, test/test_torch.py::TestTorch::test_slow_test, test/test_torch.py::TestTorch::test_sobolengine_bounds, test/test_torch.py::TestTorch::test_sobolengine_bounds_scrambled, test/test_torch.py::TestTorch::test_sobolengine_continuing, test/test_torch.py::TestTorch::test_sobolengine_continuing_scrambled, test/test_torch.py::TestTorch::test_sobolengine_default_dtype, test/test_torch.py::TestTorch::test_sobolengine_distribution, test/test_torch.py::TestTorch::test_sobolengine_distribution_scrambled, test/test_torch.py::TestTorch::test_sobolengine_draw, test/test_torch.py::TestTorch::test_sobolengine_draw_base2, test/test_torch.py::TestTorch::test_sobolengine_draw_base2_scrambled, test/test_torch.py::TestTorch::test_sobolengine_draw_scrambled, test/test_torch.py::TestTorch::test_sobolengine_fast_forward, test/test_torch.py::TestTorch::test_sobolengine_fast_forward_scrambled, test/test_torch.py::TestTorch::test_sobolengine_first_point, test/test_torch.py::TestTorch::test_sobolengine_high_dim, test/test_torch.py::TestTorch::test_sobolengine_raise, test/test_torch.py::TestTorch::test_sobolengine_reset, test/test_torch.py::TestTorch::test_sobolengine_reset_scrambled, test/test_torch.py::TestTorch::test_sort_neg_dim, test/test_torch.py::TestTorch::test_split_neg_dim, test/test_torch.py::TestTorch::test_split_with_sizes_copy_out, test/test_torch.py::TestTorch::test_squeeze_neg_dim, test/test_torch.py::TestTorch::test_std_neg_dim, test/test_torch.py::TestTorch::test_storage_base_init, test/test_torch.py::TestTorch::test_storage_base_new, test/test_torch.py::TestTorch::test_storage_byteswap, test/test_torch.py::TestTorch::test_storage_casts, test/test_torch.py::TestTorch::test_storage_cycle_via_dict, test/test_torch.py::TestTorch::test_storage_cycle_via_slots, test/test_torch.py::TestTorch::test_storage_dead_weak_ref, test/test_torch.py::TestTorch::test_storage_dealloc, test/test_torch.py::TestTorch::test_storage_dealloc_resurrected, test/test_torch.py::TestTorch::test_storage_dealloc_subclass_resurrected, test/test_torch.py::TestTorch::test_storage_dealloc_subclass_zombie, test/test_torch.py::TestTorch::test_storage_dict_dealloc, test/test_torch.py::TestTorch::test_storage_error, test/test_torch.py::TestTorch::test_storage_error_no_attribute, test/test_torch.py::TestTorch::test_storage_finalizer_dealloc, test/test_torch.py::TestTorch::test_storage_fix_weakref_no_leak, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc_resurrected, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc_zombie, test/test_torch.py::TestTorch::test_storage_preserve_nonhermetic_in_hermetic_context, test/test_torch.py::TestTorch::test_storage_resurrected_weak_ref, test/test_torch.py::TestTorch::test_storage_slot_dealloc, test/test_torch.py::TestTorch::test_storage_weakref_dealloc, test/test_torch.py::TestTorch::test_structseq_repr, test/test_torch.py::TestTorch::test_subclass_preserved, test/test_torch.py::TestTorch::test_subclass_tensors, test/test_torch.py::TestTorch::test_sum_neg_dim, test/test_torch.py::TestTorch::test_swap_basic, test/test_torch.py::TestTorch::test_swap_fail_slots, test/test_torch.py::TestTorch::test_t_not_2d_error, test/test_torch.py::TestTorch::test_tensor_base_init, test/test_torch.py::TestTorch::test_tensor_base_new, test/test_torch.py::TestTorch::test_tensor_ctor_scalar, test/test_torch.py::TestTorch::test_tensor_cycle_via_dict, test/test_torch.py::TestTorch::test_tensor_cycle_via_slots, test/test_torch.py::TestTorch::test_tensor_dead_weak_ref, test/test_torch.py::TestTorch::test_tensor_dict_dealloc, test/test_torch.py::TestTorch::test_tensor_finalizer_dealloc, test/test_torch.py::TestTorch::test_tensor_fix_weakref_no_leak, test/test_torch.py::TestTorch::test_tensor_item_no_warning, test/test_torch.py::TestTorch::test_tensor_ressurecting_clear, test/test_torch.py::TestTorch::test_tensor_resurrected_weak_ref, test/test_torch.py::TestTorch::test_tensor_set, test/test_torch.py::TestTorch::test_tensor_set_errors, test/test_torch.py::TestTorch::test_tensor_slot_dealloc, test/test_torch.py::TestTorch::test_tensor_weakref_dealloc, test/test_torch.py::TestTorch::test_tensor_where_scalar, test/test_torch.py::TestTorch::test_tensor_with_grad_to_scalar_warning, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_terminate_handler_on_crash, test/test_torch.py::TestTorch::test_to, test/test_torch.py::TestTorch::test_to_with_tensor, test/test_torch.py::TestTorch::test_topk_neg_dim, test/test_torch.py::TestTorch::test_torch_from_file, test/test_torch.py::TestTorch::test_transpose_neg_dim, test/test_torch.py::TestTorch::test_type, test/test_torch.py::TestTorch::test_type_alias, test/test_torch.py::TestTorch::test_type_conversion_via_dtype_name, test/test_torch.py::TestTorch::test_typed_storage_deprecation_warning, test/test_torch.py::TestTorch::test_typed_storage_internal_no_warning, test/test_torch.py::TestTorch::test_unbind_neg_dim, test/test_torch.py::TestTorch::test_unflatten, test/test_torch.py::TestTorch::test_unfold_neg_dim, test/test_torch.py::TestTorch::test_unsqueeze_neg_dim, test/test_torch.py::TestTorch::test_upsample_nearest1d_meta, test/test_torch.py::TestTorch::test_upsample_nearest2d_meta, test/test_torch.py::TestTorch::test_var_neg_dim, test/test_torch.py::TestTorch::test_warn_types, test/test_torch.py::TestTorch::test_wildcard_import, test/test_torch.py::TestVitalSignsCudaCPU::test_cuda_vitals_gpu_only_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test__local_scalar_dense_with_empty_tensor_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_cuda_errors_with_cpu_scalars_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_assertRaisesRegex_ignore_msg_non_native_device_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bfloat16_neg_abs_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bool_tensor_value_change_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_add_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcdiv_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcmul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_atan2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_copy_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_dist_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_div_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_eq_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_fmod_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ge_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_gt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_le_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lerp_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_fill_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_scatter_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_select_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_max_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_min_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_mul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ne_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_pow_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_remainder_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_sub_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_kstest_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_no_inf_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_no_inf_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_cuda_backward_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_euclidean_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_grad_p_lt_1_no_nan_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_large_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_non_contiguous_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_non_contiguous_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_norm_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_norm_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_same_inputs_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_check_tensor_all_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_check_tensor_internal_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_all_dtypes_and_devices_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_not_memory_dense_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_zero_stride_dim_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_complex_half_experimental_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_constants_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_conv_transposed_backward_agnostic_to_memory_format_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_conv_transposed_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_all_dtypes_and_devices_cpu, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxPool3d_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float64, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_scalar_check_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_non_unique_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_one_dim_deterministic_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_zero_size_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_serialization_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_default_tensor_type_warnings_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_shift_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_skip_xla_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_False_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_True_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint4x2, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_use_count_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_strides_propagation_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_sync_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_set_errors_multigpu_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_shape_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_type_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_ternary_op_mem_overlap_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_untyped_storage_meta_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_warn_always_caught_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_where_scalar_handcrafted_values_cpu
2025-08-14T21:23:46.3049207Z 
2025-08-14T21:23:46.3049388Z Running test_utils 1/1 ... [2025-08-14 21:23:46.240617]
2025-08-14T21:23:46.3049794Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:23:46.3050976Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:23:46.240995]
2025-08-14T21:27:07.4503847Z 
2025-08-14T21:27:07.4506362Z test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_1.1_e43f54a1a509360b_.log
2025-08-14T21:27:07.6665880Z Running 6045 items in this shard: test/test_utils.py::TestCheckpoint::test_checkpoint, test/test_utils.py::TestCheckpoint::test_checkpoint_module_list, test/test_utils.py::TestCheckpoint::test_checkpoint_no_tensors, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor_inputs_outputs, test/test_utils.py::TestCheckpoint::test_checkpoint_not_preserve_rng_state_and_without_reentrant, test/test_utils.py::TestCheckpoint::test_checkpoint_partial_grad, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cpu, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cuda, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_multiple_args, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_no_args, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_valid, test/test_utils.py::TestCheckpoint::test_checkpointing_without_reentrant_early_free, test/test_utils.py::TestCheckpoint::test_get_device_states_recursive, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_meta, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_multi_cuda, test/test_utils.py::TestDataLoaderUtils::test_multi_drop, test/test_utils.py::TestDataLoaderUtils::test_multi_keep, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_single_drop, test/test_utils.py::TestDataLoaderUtils::test_single_keep, test/test_utils.py::TestBottleneck::test_bottleneck_cpu_only, test/test_utils.py::TestBottleneck::test_bottleneck_cuda, test/test_utils.py::TestCollectEnv::test_smoke, test/test_utils.py::TestONNXUtils::test_check_onnx_broadcast, test/test_utils.py::TestONNXUtils::test_prepare_onnx_paddings, test/test_utils.py::TestHipify::test_import_hipify, test/test_utils.py::TestHipifyTrie::test_add_and_search_trie, test/test_utils.py::TestHipifyTrie::test_add_multiple_and_search_trie, test/test_utils.py::TestHipifyTrie::test_char_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_prefix_words_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_quote_escape, test/test_utils.py::TestHipifyTrie::test_single_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_special_char_export_trie_to_regex, test/test_utils.py::TestAssert::test_assert_scriptable, test/test_utils.py::TestAssert::test_assert_true, test/test_utils.py::TestStandaloneCPPJIT::test_load_standalone, test/test_utils.py::TestRenderUtils::test_basic, test/test_utils.py::TestDeviceUtilsCPU::test_basic_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_generator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_partial_views_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_scatter_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_asinh_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_shapes_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bool, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_one_hot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_more_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_nn_module_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_set_default_device_cpu, test/test_utils.py::TestCppExtensionUtils::test_cc_compiler_is_ok, test/test_utils.py::TestCppExtensionUtils::test_cpp_compiler_is_ok, test/test_utils.py::TestTraceback::test_basic, test/test_utils.py::TestTraceback::test_captured_traceback, test/test_utils.py::TestTraceback::test_captured_traceback_format_all, test/test_utils.py::TestTraceback::test_captured_traceback_format_all_cached, test/test_utils.py::TestTraceback::test_format_traceback_short, test/test_utils.py::TestTryImport::test_import_existing, test/test_utils.py::TestTryImport::test_import_imported, test/test_utils.py::TestTryImport::test_import_missing, test/test_utils.py::TestDeprecate::test_deprecated
2025-08-14T21:27:07.9268896Z 
2025-08-14T21:27:07.9269141Z Running test_python_dispatch 1/1 ... [2025-08-14 21:27:07.458677]
2025-08-14T21:27:07.9269618Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:27:07.9270683Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_python_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:27:07.459033]
2025-08-14T21:27:12.9311821Z 
2025-08-14T21:27:12.9312869Z test_python_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_python_dispatch_1.1_5549761889ee67ae_.log
2025-08-14T21:27:12.9358642Z Running 118 items in this shard: test/test_python_dispatch.py::TestDispatcherPythonBindings::test_call_boxed, test/test_python_dispatch.py::TestPythonRegistration::test_alias_analysis, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_no_existing, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_with_existing, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_eq, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_pickle, test/test_python_dispatch.py::TestPythonRegistration::test_error_for_unsupported_ns_or_kind, test/test_python_dispatch.py::TestPythonRegistration::test_error_if_fn_not_callable, test/test_python_dispatch.py::TestPythonRegistration::test_extend_library_with_dispatch_key_arg, test/test_python_dispatch.py::TestPythonRegistration::test_fallback, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_keyset, test/test_python_dispatch.py::TestPythonRegistration::test_fallthrough_for_dense_key_with_meta_in_tls, test/test_python_dispatch.py::TestPythonRegistration::test_finalizer, test/test_python_dispatch.py::TestPythonRegistration::test_override_aten_ops_with_multiple_libraries, test/test_python_dispatch.py::TestPythonRegistration::test_override_cpu_sum, test/test_python_dispatch.py::TestPythonRegistration::test_override_cuda_with_jiterator, test/test_python_dispatch.py::TestPythonRegistration::test_register_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_returning_symint, test/test_python_dispatch.py::TestPythonDispatch::test_all_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_autograd_in_attr, test/test_python_dispatch.py::TestPythonDispatch::test_basic, test/test_python_dispatch.py::TestPythonDispatch::test_capture_logs_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_construct_int_tensor, test/test_python_dispatch.py::TestPythonDispatch::test_custom_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_not_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_size_policy_dynamic_shapes, test/test_python_dispatch.py::TestPythonDispatch::test_data_ptr_respects_numel_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_non_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass_with_clone_returning_different_type, test/test_python_dispatch.py::TestPythonDispatch::test_detach_appears_twice_when_called_once, test/test_python_dispatch.py::TestPythonDispatch::test_device_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dim_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call_list_arg, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_dont_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_uint64, test/test_python_dispatch.py::TestPythonDispatch::test_error_using_class_method_on_mode, test/test_python_dispatch.py::TestPythonDispatch::test_exception_handling, test/test_python_dispatch.py::TestPythonDispatch::test_fancy_strides, test/test_python_dispatch.py::TestPythonDispatch::test_format, test/test_python_dispatch.py::TestPythonDispatch::test_get_cur_mode, test/test_python_dispatch.py::TestPythonDispatch::test_get_mode_stack, test/test_python_dispatch.py::TestPythonDispatch::test_index_put_where_only_index_is_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_invalid_ret, test/test_python_dispatch.py::TestPythonDispatch::test_is_contiguous_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only_and_positional_default, test/test_python_dispatch.py::TestPythonDispatch::test_layout_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_like, test/test_python_dispatch.py::TestPythonDispatch::test_list_ret, test/test_python_dispatch.py::TestPythonDispatch::test_make_fx_with_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_make_subclass_with_modes, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_noalloc, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_propagates_metadata, test/test_python_dispatch.py::TestPythonDispatch::test_maybe_tuple_bug, test/test_python_dispatch.py::TestPythonDispatch::test_mode_detection, test/test_python_dispatch.py::TestPythonDispatch::test_mode_with_make_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_multiple_ops_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_nested_push_logging_tensor_mode, test/test_python_dispatch.py::TestPythonDispatch::test_nesting_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_new_ones, test/test_python_dispatch.py::TestPythonDispatch::test_none_wrapping, test/test_python_dispatch.py::TestPythonDispatch::test_notimplemented_mode, test/test_python_dispatch.py::TestPythonDispatch::test_optional_tensor_list, test/test_python_dispatch.py::TestPythonDispatch::test_out, test/test_python_dispatch.py::TestPythonDispatch::test_produce_real_type, test/test_python_dispatch.py::TestPythonDispatch::test_record_stream, test/test_python_dispatch.py::TestPythonDispatch::test_return_and_correct_aliasing_gives_correct_stride, test/test_python_dispatch.py::TestPythonDispatch::test_return_stream, test/test_python_dispatch.py::TestPythonDispatch::test_set_data, test/test_python_dispatch.py::TestPythonDispatch::test_shallow_copy_and_detach, test/test_python_dispatch.py::TestPythonDispatch::test_sizes_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_standard_is_not_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_storage, test/test_python_dispatch.py::TestPythonDispatch::test_storage_can_be_converted_to_python_object, test/test_python_dispatch.py::TestPythonDispatch::test_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_creation, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_sym_sizes_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_tolist_numpy_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_basic, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_respects_no_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_unrelated_tensors, test/test_python_dispatch.py::TestPythonDispatch::test_version, test/test_python_dispatch.py::TestPythonDispatch::test_view_returns_alias_under_torch_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_with_mode_created_separately, test/test_python_dispatch.py::TestPythonDispatch::test_with_nested_modes, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_extra_dispatch_keys, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_multiprocessing_preserves_dtype, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_reentrant_dispatch_with_mode, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_serializes, test/test_python_dispatch.py::TestPythonDispatcher::test_basic, test/test_python_dispatch.py::TestPythonDispatcher::test_lstsq, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_cat_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_conv2d_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCatCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCubeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulScalarCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNMSCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNonzeroCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySortCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyTakeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyViewCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_fft_fft2_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_mul_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_native_batch_norm_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_out_op_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_list_args_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_view_cpu_float32
2025-08-14T21:27:12.9403452Z 
2025-08-14T21:27:12.9403635Z Running test_dispatch 1/1 ... [2025-08-14 21:27:12.931634]
2025-08-14T21:27:12.9404038Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:27:12.9405071Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:27:12.931976]
2025-08-14T21:27:39.7843040Z 
2025-08-14T21:27:39.7844086Z test_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dispatch_1.1_7214c1c50515b7eb_.log
2025-08-14T21:27:39.7854431Z Running 32 items in this shard: test/test_dispatch.py::TestDispatch::test_all_invariants, test/test_dispatch.py::TestDispatch::test_computed_table, test/test_dispatch.py::TestDispatch::test_computed_table_with_ambiguous_autogradother, test/test_dispatch.py::TestDispatch::test_computed_table_with_autograd, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math_autogradcpu_fallthrough, test/test_dispatch.py::TestDispatch::test_computed_table_with_math, test/test_dispatch.py::TestDispatch::test_def, test/test_dispatch.py::TestDispatch::test_def_impl_schema_mismatch, test/test_dispatch.py::TestDispatch::test_def_only, test/test_dispatch.py::TestDispatch::test_def_with_explicit_alias, test/test_dispatch.py::TestDispatch::test_def_with_inference, test/test_dispatch.py::TestDispatch::test_dispatch_print_registrations_for_dispatch_key_invalid, test/test_dispatch.py::TestDispatch::test_find_dangling_impls, test/test_dispatch.py::TestDispatch::test_find_dangling_impls_ext, test/test_dispatch.py::TestDispatch::test_impl_only, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_defaulting, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_mismatch, test/test_dispatch.py::TestDispatch::test_multiple_def_error, test/test_dispatch.py::TestDispatch::test_multiple_fallback, test/test_dispatch.py::TestDispatch::test_overwrite_math, test/test_dispatch.py::TestPythonDispatcher::test_autogradother, test/test_dispatch.py::TestPythonDispatcher::test_basic, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_math, test/test_dispatch.py::TestPythonDispatcher::test_duplicate_registrations, test/test_dispatch.py::TestPythonDispatcher::test_math_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_quantized_structured_not_implemented
2025-08-14T21:27:39.7864320Z 
2025-08-14T21:27:39.7864563Z Running test_namedtuple_return_api 1/1 ... [2025-08-14 21:27:39.784532]
2025-08-14T21:27:39.7865007Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:27:39.7866148Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:27:39.784862]
2025-08-14T21:27:43.9546917Z 
2025-08-14T21:27:43.9547995Z test_namedtuple_return_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtuple_return_api_1.1_b30ba2a9b2873539_.log
2025-08-14T21:27:43.9549919Z Running 3 items in this shard: test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_import_return_types, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_namedtuple_return, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_native_functions_yaml
2025-08-14T21:27:43.9551400Z 
2025-08-14T21:27:43.9551670Z Running test_multiprocessing 1/1 ... [2025-08-14 21:27:43.954920]
2025-08-14T21:27:43.9552172Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:27:43.9556235Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_multiprocessing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:27:43.955284]
2025-08-14T21:28:48.2686593Z 
2025-08-14T21:28:48.2688738Z test_multiprocessing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_1.1_fdf3819da74a579c_.log
2025-08-14T21:28:48.2707824Z Running 42 items in this shard: test/test_multiprocessing.py::TestMultiprocessing::test_autograd_errors, test/test_multiprocessing.py::TestMultiprocessing::test_autograd_fine_with_spawn, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_bad_call, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_ipc_deadlock, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_memory_allocation, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_send_many, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_simple, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_small_tensors, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_shared, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_event, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_exporter, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_importer, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_multi_gpu, test/test_multiprocessing.py::TestMultiprocessing::test_event_multiprocess, test/test_multiprocessing.py::TestMultiprocessing::test_fd_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fd_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fd_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs, test/test_multiprocessing.py::TestMultiprocessing::test_fs_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_fs_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fs_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_inherit_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cpu, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_mixed_types_cuda_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_non_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_rebuild_cuda_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_set_thread_name, test/test_multiprocessing.py::TestMultiprocessing::test_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_wrong_cuda_fork
2025-08-14T21:28:48.2722520Z 
2025-08-14T21:28:48.2722786Z Running test_autograd_fallback 1/1 ... [2025-08-14 21:28:48.269058]
2025-08-14T21:28:48.2723226Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:28:48.2724287Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autograd_fallback.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:28:48.269504]
2025-08-14T21:28:51.6386569Z 
2025-08-14T21:28:51.6387956Z test_autograd_fallback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autograd_fallback_1.1_a26d0c7b974f4d29_.log
2025-08-14T21:28:51.6404964Z Running 28 items in this shard: test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_warn
2025-08-14T21:28:51.6417435Z 
2025-08-14T21:28:51.6417659Z Running test_jit_disabled 1/1 ... [2025-08-14 21:28:51.638976]
2025-08-14T21:28:51.6418067Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:28:51.6419117Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_disabled.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:28:51.639396]
2025-08-14T21:28:54.9582650Z 
2025-08-14T21:28:54.9583487Z test_jit_disabled 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_disabled_1.1_3c2885f2ef61410c_.log
2025-08-14T21:28:54.9585051Z Running 3 items in this shard: test/test_jit_disabled.py::TestJitDisabled::test_attribute, test/test_jit_disabled.py::TestJitDisabled::test_recursive_script, test/test_jit_disabled.py::TestJitDisabled::test_script_module_construction
2025-08-14T21:28:54.9586138Z 
2025-08-14T21:28:54.9586821Z Running test_autocast 1/1 ... [2025-08-14 21:28:54.958526]
2025-08-14T21:28:54.9587215Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:28:54.9591463Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autocast.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:28:54.958874]
2025-08-14T21:28:58.9786971Z 
2025-08-14T21:28:58.9788134Z test_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autocast_1.1_7d28dc418125b322_.log
2025-08-14T21:28:58.9795604Z Running 20 items in this shard: test/test_autocast.py::TestAutocastCPU::test_autocast_disabled_with_fp32_dtype, test/test_autocast.py::TestAutocastCPU::test_autocast_methods_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_16, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_rnn, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_16, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_need_autocast_promote, test/test_autocast.py::TestAutocastCPU::test_cpu_autocast_deprecated_warning, test/test_autocast.py::TestAutocastCPU::test_generic_autocast, test/test_autocast.py::TestAutocastGPU::test_autocast_prioritize, test/test_autocast.py::TestAutocastGPU::test_cache_disabled, test/test_autocast.py::TestAutocastGPU::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_bfloat16_supported, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_error_message, test/test_autocast.py::TestTorchAutocast::test_autocast_fast_dtype, test/test_autocast.py::TestTorchAutocast::test_invalid_device, test/test_autocast.py::TestTorchAutocast::test_non_string_device
2025-08-14T21:28:58.9802356Z 
2025-08-14T21:28:58.9802544Z Running test_cuda_trace 1/1 ... [2025-08-14 21:28:58.979018]
2025-08-14T21:28:58.9803022Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:28:58.9804187Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_trace.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:28:58.979375]
2025-08-14T21:29:02.1716596Z 
2025-08-14T21:29:02.1717878Z test_cuda_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_trace_1.1_fcfd8df5e922e7a4_.log
2025-08-14T21:29:02.1719193Z Running 0 items in this shard:
2025-08-14T21:29:02.1719550Z 
2025-08-14T21:29:02.1722195Z Running test_native_mha 1/1 ... [2025-08-14 21:29:02.172017]
2025-08-14T21:29:02.1722886Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:29:02.1727415Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_mha.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:29:02.172417]
2025-08-14T21:29:05.6919986Z 
2025-08-14T21:29:05.6920905Z test_native_mha 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_mha_1.1_834aab35fb2581f2_.log
2025-08-14T21:29:05.6943153Z Running 28 items in this shard: test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_encoder_decoder_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_nested_cpu_float32
2025-08-14T21:29:05.6964040Z 
2025-08-14T21:29:05.6964248Z Running test_sort_and_select 1/1 ... [2025-08-14 21:29:05.692282]
2025-08-14T21:29:05.6964671Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:29:05.6965706Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sort_and_select.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:29:05.692620]
2025-08-14T21:29:11.1644818Z 
2025-08-14T21:29:11.1645780Z test_sort_and_select 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sort_and_select_1.1_0a043f53a899684e_.log
2025-08-14T21:29:11.1685344Z Running 113 items in this shard: test/test_sort_and_select.py::TestSortAndSelectCPU::test_complex_unsupported_cpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_dtypes_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_scalar_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_slow_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_expanded_tensor_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_slice_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_restride_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_stable_none_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_4d_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_arguments_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_noncontiguous_gpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_quantized_scalar_input_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_dim_cpu
2025-08-14T21:29:11.1723804Z 
2025-08-14T21:29:11.1724035Z Running test_cuda_nvml_based_avail 1/1 ... [2025-08-14 21:29:11.164801]
2025-08-14T21:29:11.1724491Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:29:11.1725612Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_nvml_based_avail.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:29:11.165173]
2025-08-14T21:29:14.2718583Z 
2025-08-14T21:29:14.2720042Z test_cuda_nvml_based_avail 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_nvml_based_avail_1.1_374522f5406b04e3_.log
2025-08-14T21:29:14.2720965Z Running 0 items in this shard:
2025-08-14T21:29:14.2721173Z 
2025-08-14T21:29:14.2722711Z Running test_cpp_extensions_jit 1/1 ... [2025-08-14 21:29:14.272126]
2025-08-14T21:29:14.2723216Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:29:14.2726978Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_jit.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:29:14.272483]
2025-08-14T21:29:50.7418430Z 
2025-08-14T21:29:50.7419424Z test_cpp_extensions_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_jit_1.1_79a1df62b423a5d4_.log
2025-08-14T21:29:50.7436093Z Running 34 items in this shard: test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_aoti_torch_call_dispatcher, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_autograd_from_cpp, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_compilation_error_formatting, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_same_output_as_python, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_up_to_date_attributes, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op_with_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_non_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_pluggable_allocator_include, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_compound_op_autograd, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_functorch_error, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_gen_extension_h_pch, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_half_support, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_custom_op_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_multiple_sources_and_no_functions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_throws_when_functions_is_bad, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_dict, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_list, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_xpu, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_compile_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_archflags, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cudnn_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_archlists, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_lenient_flag_handling_in_jit_extensions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_load_with_non_platform_default_encoding, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_mps_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_reload_jit_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_returns_shared_library_path_when_is_python_module_is_true, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_set_default_type_also_changes_aten_default_type, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_warning
2025-08-14T21:29:50.7450717Z 
2025-08-14T21:29:50.7450902Z Running nn/test_pooling 1/1 ... [2025-08-14 21:29:50.742268]
2025-08-14T21:29:50.7451376Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:29:50.7452467Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_pooling.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:29:50.742622]
2025-08-14T21:30:25.0157286Z 
2025-08-14T21:30:25.0158405Z nn/test_pooling 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pooling_1.1_7e753fbab7f98d2b_.log
2025-08-14T21:30:25.0201748Z Running 111 items in this shard: test/nn/test_pooling.py::TestAvgPool::test_avg_pool1d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool2d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool3d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d_with_divisor, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d_with_divisor, test/nn/test_pooling.py::TestPoolingNN::test_MaxUnpool2d_output_size, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_nhwc_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_backward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_forward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_non_contiguous, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_lower_precision, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_none, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_overflow, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool2d_nhwc_cpu, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool3d_input_check, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool1d_empty_kernel, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool3d, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool2d_empty_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool3d_backward_after_cat_dim1_device_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_errors_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case10_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case4_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case5_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case6_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case7_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case8_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case9_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool2d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool3d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_max_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pool_odd_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_uint8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool3d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_indices_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_with_indices_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool3d_non_square_backward_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool_indices_no_batch_dim_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_large_size_int64_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_size_one_feature_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_invalid_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_large_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_bfloat16_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_large_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_zero_stride_cpu
2025-08-14T21:30:25.0244472Z 
2025-08-14T21:30:25.6973422Z Uploading artifacts took 0.68 seconds
2025-08-14T21:30:25.6976242Z Running test_cuda_primary_ctx 1/1 ... [2025-08-14 21:30:25.697447]
2025-08-14T21:30:25.6976772Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:30:25.6980574Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_primary_ctx.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:30:25.697812]
2025-08-14T21:30:28.9539007Z 
2025-08-14T21:30:28.9539917Z test_cuda_primary_ctx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_primary_ctx_1.1_0804a5281c628518_.log
2025-08-14T21:30:28.9540684Z Running 0 items in this shard:
2025-08-14T21:30:28.9540893Z 
2025-08-14T21:30:28.9543164Z Running test_mobile_optimizer 1/1 ... [2025-08-14 21:30:28.954159]
2025-08-14T21:30:28.9543709Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:30:28.9547356Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mobile_optimizer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:30:28.954516]
2025-08-14T21:30:34.6837893Z 
2025-08-14T21:30:34.6838829Z test_mobile_optimizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mobile_optimizer_1.1_e2de2ca05c3046fc_.log
2025-08-14T21:30:34.6842447Z Running 7 items in this shard: test/test_mobile_optimizer.py::TestOptimizer::test_clone_module_with_class, test/test_mobile_optimizer.py::TestOptimizer::test_generate_mobile_module_lints, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_mobilenet_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_preserve_bundled_inputs_methods, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures
2025-08-14T21:30:34.6845234Z 
2025-08-14T21:30:34.6845490Z Running test_multiprocessing_spawn 1/1 ... [2025-08-14 21:30:34.683972]
2025-08-14T21:30:34.6845955Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:30:34.6847036Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_multiprocessing_spawn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:30:34.684305]
2025-08-14T21:32:45.7851601Z 
2025-08-14T21:32:45.7852675Z test_multiprocessing_spawn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_spawn_1.1_ffbd9642d714a31e_.log
2025-08-14T21:32:45.7864907Z Running 31 items in this shard: test/test_multiprocessing_spawn.py::SpawnTest::test_exception_all, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_single, test/test_multiprocessing_spawn.py::SpawnTest::test_first_argument_index, test/test_multiprocessing_spawn.py::SpawnTest::test_signal_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_success, test/test_multiprocessing_spawn.py::SpawnTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::SpawnTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ForkTest::test_exception_all, test/test_multiprocessing_spawn.py::ForkTest::test_exception_single, test/test_multiprocessing_spawn.py::ForkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ForkTest::test_success, test/test_multiprocessing_spawn.py::ForkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ForkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_all, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_single, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerPerfTest::test_forkserver_perf, test/test_multiprocessing_spawn.py::ErrorTest::test_errors_pickleable
2025-08-14T21:32:45.7876146Z 
2025-08-14T21:32:45.7876367Z Running nn/test_convolution 1/1 ... [2025-08-14 21:32:45.785470]
2025-08-14T21:32:45.7876788Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:32:45.7877925Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_convolution.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:32:45.785795]
2025-08-14T21:33:11.1946804Z 
2025-08-14T21:33:11.1947972Z nn/test_convolution 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_convolution_1.1_cb849319dc60439e_.log
2025-08-14T21:33:11.2302722Z Running 599 items in this shard: test/nn/test_convolution.py::TestConvolutionNN::test_Conv1d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_1x1, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_OneDNN, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_backward_twice, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias_v2, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_with_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_without_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_missing_argument, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_wbias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_half_cublas_gemm, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size_downsample_upsample, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose3d_correct_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv1d_issue_120547, test/nn/test_convolution.py::TestConvolutionNN::test_conv2d_discontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_conv3d_issue_120406, test/nn/test_convolution.py::TestConvolutionNN::test_conv_backcompat, test/nn/test_convolution.py::TestConvolutionNN::test_conv_cudnn_memory_layout_dominance, test/nn/test_convolution.py::TestConvolutionNN::test_conv_invalid_groups, test/nn/test_convolution.py::TestConvolutionNN::test_conv_modules_raise_error_on_incorrect_input_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv_padding_mode, test/nn/test_convolution.py::TestConvolutionNN::test_conv_shapecheck, test/nn/test_convolution.py::TestConvolutionNN::test_conv_tbc, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_non_contiguous, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_noncontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_not_mutate_stride, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grouped_conv_cudnn_nhwc_support, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv1d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv3d, test/nn/test_convolution.py::TestConvolutionNN::test_mismatch_shape_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_nnpack_conv, test/nn/test_convolution.py::TestConvolutionNN::test_permute_conv2d_issue_120211, test/nn/test_convolution.py::TestConvolutionNN::test_thnn_conv_strided_padded_dilated, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_backward_depthwise_cpu_complex128, 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test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_ic1_channels_last_for_oneDNN_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_batch_1_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_nosplit_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_and_bias_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose2d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose3d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transposed_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv2d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv3d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_depthwise_conv_64bit_indexing_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_convTranspose_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_conv_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float64
2025-08-14T21:33:11.2646294Z 
2025-08-14T21:33:11.2646518Z Running test_spectral_ops 1/1 ... [2025-08-14 21:33:11.196155]
2025-08-14T21:33:11.2646942Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:33:11.2648012Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:33:11.196511]
2025-08-14T21:33:22.5280092Z 
2025-08-14T21:33:22.5281338Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_d4cdfe7894d0d070_.log
2025-08-14T21:33:22.5377833Z Running 281 items in this shard: test/test_spectral_ops.py::TestFFTCPU::test_batch_istft_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_istft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_definition_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_onesided_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_plan_cache_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_float32, 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test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftfreq_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftn_cpu
2025-08-14T21:33:22.5469008Z 
2025-08-14T21:33:22.5469272Z Running distributions/test_distributions 1/1 ... [2025-08-14 21:33:22.528753]
2025-08-14T21:33:22.5469873Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:33:22.5470993Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:33:22.529084]
2025-08-14T21:34:11.5717539Z 
2025-08-14T21:34:11.5719445Z distributions/test_distributions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_1.1_edc301af39491c21_.log
2025-08-14T21:34:11.5815098Z Running 230 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_argmax_relaxed_categorical, test/distributions/test_distributions.py::TestDistributions::test_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_3d, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_beta_log_prob, test/distributions/test_distributions.py::TestDistributions::test_beta_sample, test/distributions/test_distributions.py::TestDistributions::test_beta_shape, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow_gpu, test/distributions/test_distributions.py::TestDistributions::test_binomial, test/distributions/test_distributions.py::TestDistributions::test_binomial_bfloat16, test/distributions/test_distributions.py::TestDistributions::test_binomial_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_binomial_extreme_vals, test/distributions/test_distributions.py::TestDistributions::test_binomial_half, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_stable, test/distributions/test_distributions.py::TestDistributions::test_binomial_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_categorical_enumerate_support, 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test/distributions/test_distributions.py::TestDistributions::test_poisson_shape, test/distributions/test_distributions.py::TestDistributions::test_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_repr, test/distributions/test_distributions.py::TestDistributions::test_rounded_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_rsample_requires_grad, test/distributions/test_distributions.py::TestDistributions::test_sample_detached, test/distributions/test_distributions.py::TestDistributions::test_studentT, test/distributions/test_distributions.py::TestDistributions::test_studentT_log_prob, test/distributions/test_distributions.py::TestDistributions::test_studentT_sample, 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test/distributions/test_distributions.py::TestDistributionShapes::test_halfcauchy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_halfcauchy_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_kumaraswamy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_mean_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_multinomial_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_normal_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_normal_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_one_hot_categorical_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_pareto_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_uniform_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_uniform_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_vonmises_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_vonmises_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_weibull_scale_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_tensor_params, test/distributions/test_distributions.py::TestKL::test_entropy_exponential_family, test/distributions/test_distributions.py::TestKL::test_entropy_monte_carlo, test/distributions/test_distributions.py::TestKL::test_kl_edgecases, test/distributions/test_distributions.py::TestKL::test_kl_exponential_family, test/distributions/test_distributions.py::TestKL::test_kl_infinite, test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal, test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_monte_carlo, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched_broadcasted, test/distributions/test_distributions.py::TestKL::test_kl_shape, test/distributions/test_distributions.py::TestKL::test_kl_transformed, test/distributions/test_distributions.py::TestConstraints::test_params_constraints, test/distributions/test_distributions.py::TestConstraints::test_support_constraints, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob_with_logits, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob_with_logits, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_logits_initialization, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_probs_initialization, test/distributions/test_distributions.py::TestAgainstScipy::test_cdf, test/distributions/test_distributions.py::TestAgainstScipy::test_icdf, test/distributions/test_distributions.py::TestAgainstScipy::test_mean, test/distributions/test_distributions.py::TestAgainstScipy::test_variance_stddev, test/distributions/test_distributions.py::TestFunctors::test_cat_event_dim, test/distributions/test_distributions.py::TestFunctors::test_cat_transform, test/distributions/test_distributions.py::TestFunctors::test_cat_transform_non_uniform, test/distributions/test_distributions.py::TestFunctors::test_stack_transform, test/distributions/test_distributions.py::TestValidation::test_invalid, test/distributions/test_distributions.py::TestValidation::test_invalid_log_probs_arg, test/distributions/test_distributions.py::TestValidation::test_valid, test/distributions/test_distributions.py::TestValidation::test_warning_unimplemented_constraints, test/distributions/test_distributions.py::TestJit::test_cdf, test/distributions/test_distributions.py::TestJit::test_entropy, test/distributions/test_distributions.py::TestJit::test_enumerate_support, test/distributions/test_distributions.py::TestJit::test_log_prob, test/distributions/test_distributions.py::TestJit::test_mean, test/distributions/test_distributions.py::TestJit::test_rsample, test/distributions/test_distributions.py::TestJit::test_sample, test/distributions/test_distributions.py::TestJit::test_variance
2025-08-14T21:34:11.5906025Z 
2025-08-14T21:34:11.5906265Z Running test_autoload_enable 1/1 ... [2025-08-14 21:34:11.572375]
2025-08-14T21:34:13.9191112Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:13.9192765Z   import pkg_resources
2025-08-14T21:34:13.9860672Z running install
2025-08-14T21:34:13.9862799Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:13.9863591Z !!
2025-08-14T21:34:13.9863704Z 
2025-08-14T21:34:13.9863841Z         ********************************************************************************
2025-08-14T21:34:13.9864221Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:13.9864629Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:13.9865010Z         standards-based tools.
2025-08-14T21:34:13.9865197Z 
2025-08-14T21:34:13.9865426Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:13.9865913Z         or your builds will no longer be supported.
2025-08-14T21:34:13.9866173Z 
2025-08-14T21:34:13.9866481Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:13.9867227Z         ********************************************************************************
2025-08-14T21:34:13.9867473Z 
2025-08-14T21:34:13.9867559Z !!
2025-08-14T21:34:13.9867785Z   self.initialize_options()
2025-08-14T21:34:13.9996901Z running build
2025-08-14T21:34:13.9997209Z running build_py
2025-08-14T21:34:14.0089032Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:14.0095908Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:14.0103311Z running build_ext
2025-08-14T21:34:14.0122154Z building 'torch_test_cpp_extension.cpp' extension
2025-08-14T21:34:14.0124125Z creating build/temp.linux-x86_64-cpython-313
2025-08-14T21:34:14.0129090Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-08-14T21:34:15.2211522Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12,
2025-08-14T21:34:15.2213343Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11,
2025-08-14T21:34:15.2214255Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9,
2025-08-14T21:34:15.2214893Z                  from extension.cpp:1:
2025-08-14T21:34:15.2240767Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_<MatrixMultiplier>’:
2025-08-14T21:34:15.2241675Z extension.cpp:45:53:   required from here
2025-08-14T21:34:15.2243260Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1539:7: warning: ‘pybind11::class_<MatrixMultiplier>’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes]
2025-08-14T21:34:15.2244505Z  1539 | class class_ : public detail::generic_type {
2025-08-14T21:34:15.2244849Z       |       ^~~~~~
2025-08-14T21:34:15.2246461Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< <template-parameter-1-1>, <template-parameter-1-2> >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’:
2025-08-14T21:34:15.2247846Z extension.cpp:45:53:   required from here
2025-08-14T21:34:15.2250167Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1599:28: warning: ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>’ declared with greater visibility than the type of its field ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>::<record capture>’ [-Wattributes]
2025-08-14T21:34:15.2252109Z  1599 |             with_internals([&](internals &internals) {
2025-08-14T21:34:15.2252485Z       |                            ^~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:15.2253005Z  1600 |                 auto &instances = record.module_local ? get_local_internals().registered_types_cpp
2025-08-14T21:34:15.2253586Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:15.2254038Z  1601 |                                                       : internals.registered_types_cpp;
2025-08-14T21:34:15.2254568Z       |                                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:15.2254996Z  1602 |                 instances[std::type_index(typeid(type_alias))]
2025-08-14T21:34:15.2255402Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:15.2255788Z  1603 |                     = instances[std::type_index(typeid(type))];
2025-08-14T21:34:15.2256196Z       |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:15.2256536Z  1604 |             });
2025-08-14T21:34:15.2256788Z       |             ~               
2025-08-14T21:34:15.2260073Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:15.9592802Z building 'torch_test_cpp_extension.maia' extension
2025-08-14T21:34:15.9597421Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-08-14T21:34:17.0883866Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:17.7185517Z building 'torch_test_cpp_extension.rng' extension
2025-08-14T21:34:17.7190073Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-08-14T21:34:19.0267973Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:19.0269821Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:19.0271043Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:19.0272539Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:19.0273604Z                  from rng_extension.cpp:6:
2025-08-14T21:34:19.0275425Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:19.0276695Z  1478 | #pragma unroll
2025-08-14T21:34:19.0277044Z       | 
2025-08-14T21:34:19.0277911Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4,
2025-08-14T21:34:19.0279461Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530,
2025-08-14T21:34:19.0280584Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:19.0281873Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:19.0283309Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:19.0284864Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:19.0286050Z                  from rng_extension.cpp:6:
2025-08-14T21:34:19.0287810Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:19.0289119Z    59 | #pragma unroll
2025-08-14T21:34:19.0289650Z       | 
2025-08-14T21:34:19.0290994Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:19.0292357Z    72 | #pragma unroll
2025-08-14T21:34:19.0292805Z       | 
2025-08-14T21:34:19.0294232Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:19.0295257Z    87 | #pragma unroll
2025-08-14T21:34:19.0295516Z       | 
2025-08-14T21:34:19.0296064Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531,
2025-08-14T21:34:19.0296967Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:19.0297778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:19.0298590Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:19.0299495Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:19.0300151Z                  from rng_extension.cpp:6:
2025-08-14T21:34:19.0301121Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:19.0301930Z   160 | #pragma unroll
2025-08-14T21:34:19.0302163Z       | 
2025-08-14T21:34:19.0302669Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0303652Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0304873Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0305725Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0306472Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0307308Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0308231Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0309343Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0310234Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0311171Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0312471Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0313297Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0313849Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0315049Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0316674Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0318432Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0320231Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0322124Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0324159Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0330417Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0341008Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0347011Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0347983Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0348371Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0354754Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0361323Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0362602Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0363010Z       |        ^~~~~~~~
2025-08-14T21:34:19.0363637Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0364637Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0365521Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0366360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0367118Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0367951Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0369007Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0370126Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0371265Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0372375Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0373379Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0374300Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0375172Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0375770Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0376603Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0377334Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0377684Z       |                     ^~~~
2025-08-14T21:34:19.0378259Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0379132Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0379948Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0380740Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0381481Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0394859Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0396023Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0396939Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0397867Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0398816Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0399770Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0400619Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0401172Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0402292Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0403974Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0405696Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0407458Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0409582Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0411633Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0417862Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0428308Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0434301Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0435237Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0435629Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0441877Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0448361Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0449663Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0450070Z       |        ^~~~~~~~
2025-08-14T21:34:19.0450692Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0451720Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0452603Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0453402Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0454164Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0454999Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0456053Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0457175Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0458320Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0459434Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0460439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0461363Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0462202Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0462756Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0463592Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0464378Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0464729Z       |                     ^~~~
2025-08-14T21:34:19.0465307Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0466161Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0466964Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0467758Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0468503Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0469337Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0470245Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0471133Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0472106Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0473079Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0474051Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0474889Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0475440Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0476467Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0478010Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0479725Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0481480Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0483353Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0485371Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0491580Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0501397Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0507058Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0508019Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0508392Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0514748Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0520970Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0522244Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0522662Z       |        ^~~~~~~~
2025-08-14T21:34:19.0523287Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0524372Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0525419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0526235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0526998Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0527836Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0528878Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0530012Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0531158Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0532274Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0533327Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0534306Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0535150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0535706Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0536590Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0537338Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0537689Z       |                     ^~~~
2025-08-14T21:34:19.0538257Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0539114Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0539924Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0540716Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0541445Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0542280Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0543204Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0544169Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0545045Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0545982Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0546938Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0547781Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0548322Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0549383Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0550954Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0552763Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0554521Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0556395Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0558420Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0564573Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0574986Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0580896Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0581819Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0582186Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0588395Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0594957Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0596272Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0596692Z       |        ^~~~~~~~
2025-08-14T21:34:19.0597314Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0598299Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0599181Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0599997Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0600759Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0601581Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0602639Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0603774Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0604916Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0606031Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0607021Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0607959Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0608836Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0609603Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0610441Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0611187Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0611543Z       |                     ^~~~
2025-08-14T21:34:19.0612108Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0612970Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0613780Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0614568Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0615303Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0616135Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0617055Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0618031Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0618944Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0619883Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0620887Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0621729Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0622272Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0623274Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0624830Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0626540Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0628296Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0630162Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0632261Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0638117Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0647979Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0653649Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0654563Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0654946Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0660815Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0667003Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0668315Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0668733Z       |        ^~~~~~~~
2025-08-14T21:34:19.0669344Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0670342Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0671229Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0672124Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0672868Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0673711Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0674774Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0675895Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0677082Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0678218Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0679219Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0680151Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0681008Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0681553Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0682385Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0683110Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0683457Z       |                     ^~~~
2025-08-14T21:34:19.0684023Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0684875Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0685667Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0686449Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0687189Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0688018Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0688919Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0689804Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0690686Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0691620Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0692602Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0693439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0693994Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0694991Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0696528Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0698231Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0699989Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0701857Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0703900Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0709889Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0719859Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0725462Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0726386Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0726769Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0732651Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0738854Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0740156Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0740574Z       |        ^~~~~~~~
2025-08-14T21:34:19.0741196Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0742198Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0743064Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0743875Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0744629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0745457Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0746500Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0747628Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0748767Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0749879Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0750865Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0751865Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0752748Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0753304Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0754125Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0754864Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0755253Z       |                     ^~~~
2025-08-14T21:34:19.0755826Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0756667Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0757478Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0758272Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0759008Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0759826Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0760777Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0761706Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0762586Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0763506Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0764529Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0765369Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0765929Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0766909Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0768463Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0770169Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0771926Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0773798Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0775810Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0781632Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0791396Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0797117Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0798034Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0798427Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0804295Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0810666Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0812029Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0812452Z       |        ^~~~~~~~
2025-08-14T21:34:19.0813077Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0814067Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0814956Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0815768Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0816525Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0817351Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0818400Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0819534Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0820712Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0821842Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0822843Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0823837Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0824675Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0825209Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0826037Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0826776Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0827125Z       |                     ^~~~
2025-08-14T21:34:19.0827682Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0828528Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0829334Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0830112Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0830852Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0831748Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0832666Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0833541Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0834426Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0835360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0836354Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0837179Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0837729Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0838724Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0840277Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0841978Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0843737Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0845619Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0847663Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0853784Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0864231Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0870120Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0871036Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0871417Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0877710Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0884218Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0885490Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0885906Z       |        ^~~~~~~~
2025-08-14T21:34:19.0886518Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0887517Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0888400Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0889212Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0889955Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0890791Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0891838Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0892959Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0894096Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0895204Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0896235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0897156Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0897995Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0898547Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0899360Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0900109Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0900457Z       |                     ^~~~
2025-08-14T21:34:19.0901039Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0901884Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0902699Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0903487Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0904243Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0905098Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0906015Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0906905Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0907807Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0908744Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0910061Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0910910Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0911455Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0912549Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0914109Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0915821Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0917574Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0919442Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0921457Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0927332Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.0937120Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.0942801Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.0943715Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.0944097Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.0949976Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.0956239Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.0957519Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.0957935Z       |        ^~~~~~~~
2025-08-14T21:34:19.0958561Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.0959544Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.0960426Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.0961246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.0962001Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.0962818Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.0963902Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.0965179Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.0966321Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.0967418Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.0968457Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.0969392Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.0970230Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0970770Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0971608Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.0972348Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.0972680Z       |                     ^~~~
2025-08-14T21:34:19.0973252Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.0974113Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.0974926Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.0975698Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.0976439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.0977271Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.0978183Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.0979053Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.0979970Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.0980898Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.0981936Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.0982763Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.0983314Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.0984301Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.0985853Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.0987553Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.0989335Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.0991232Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.0993323Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.0999165Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1009195Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1014832Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1015760Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1016139Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1022061Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1028320Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1029602Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1030019Z       |        ^~~~~~~~
2025-08-14T21:34:19.1030637Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1031708Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1032592Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1033396Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1034160Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1034990Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1036041Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1037156Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1038297Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1039463Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1040469Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1041404Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1042235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1042791Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1043628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1044354Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1044707Z       |                     ^~~~
2025-08-14T21:34:19.1045287Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1046143Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1046942Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1047788Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1048535Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1049400Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1050306Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1051196Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1052114Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1053051Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1053996Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1054835Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1055389Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1056379Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1057922Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1059627Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1061377Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1063243Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1065287Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1071202Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1081093Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1086741Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1087665Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1088049Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1093930Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1100098Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1101366Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1101788Z       |        ^~~~~~~~
2025-08-14T21:34:19.1102411Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1103404Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1104272Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1105089Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1105844Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1106717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1107756Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1108913Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1110347Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1111606Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1112602Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1113619Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1114468Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1115026Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1115863Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1116606Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1116954Z       |                     ^~~~
2025-08-14T21:34:19.1117535Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1118376Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1119185Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1119976Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1120718Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1121537Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1122447Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1123391Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1124276Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1125193Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1126150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1126991Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1127543Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1128522Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1130078Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1131777Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1133567Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1135476Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1137491Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1143296Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1153263Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1158872Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1159792Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1160162Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1166051Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1172293Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1173571Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1173997Z       |        ^~~~~~~~
2025-08-14T21:34:19.1174618Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1175600Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1176508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1177337Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1178109Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1178942Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1180013Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1181170Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1182309Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1183446Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1184451Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1185389Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1186233Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1186775Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1187611Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1188354Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1188709Z       |                     ^~~~
2025-08-14T21:34:19.1189276Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1190134Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1190949Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1191867Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1192631Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1193475Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1194396Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1195315Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1196185Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1197120Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1198079Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1198917Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1199451Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1200439Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1201993Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1203696Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1205442Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1207299Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1209610Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1215836Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1226220Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1232297Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1233215Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1233600Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1239817Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1246269Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1247545Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1247956Z       |        ^~~~~~~~
2025-08-14T21:34:19.1248565Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1249562Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1250441Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1251287Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1252034Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1252898Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1253947Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1255126Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1256268Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1257367Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1258370Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1259308Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1260150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1260684Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1261516Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1262252Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1262587Z       |                     ^~~~
2025-08-14T21:34:19.1263156Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1264007Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1264816Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1265583Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1266325Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1267190Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1268109Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1268981Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1269866Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1270799Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1271833Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1272658Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1273210Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1274201Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1275753Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1277493Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1279259Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1281167Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1283182Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1289409Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1299961Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1305930Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1306846Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1307229Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1313976Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1320651Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1321927Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1322343Z       |        ^~~~~~~~
2025-08-14T21:34:19.1322952Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1323949Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1324839Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1325652Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1326395Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1327286Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1328341Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1329474Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1330617Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1331716Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1332724Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1333667Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1334510Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1335052Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1336266Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1337413Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1337792Z       |                     ^~~~
2025-08-14T21:34:19.1338374Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1339376Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1340460Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1341282Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1342031Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1342869Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1343796Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1344671Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1345557Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1346490Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1347513Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1348387Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1348992Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1350054Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1351686Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1353414Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1355354Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1357904Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1360427Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1371832Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1384944Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1390960Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1391960Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1392347Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1398735Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1405279Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1406595Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1407040Z       |        ^~~~~~~~
2025-08-14T21:34:19.1407666Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1408648Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1409735Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1410624Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1411381Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1412206Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1413255Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1414391Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1415526Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1416630Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1417629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1418564Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1419405Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1419949Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1420794Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1421536Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1421893Z       |                     ^~~~
2025-08-14T21:34:19.1422520Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1423360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1424175Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1424967Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1425717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1426542Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1427460Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1428356Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1429248Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1430176Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1431169Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1432127Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1432686Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1433674Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1435269Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1436979Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1438736Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1440611Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1442629Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1448898Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1459468Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1465447Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1466404Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1466776Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1473162Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1479706Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1480985Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1481384Z       |        ^~~~~~~~
2025-08-14T21:34:19.1482051Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1483054Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1483924Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1484743Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1485502Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1486334Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1487369Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1488504Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1489642Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1490791Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1491783Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1492747Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1493585Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1494165Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1494985Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1495727Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1496074Z       |                     ^~~~
2025-08-14T21:34:19.1496645Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1497487Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1498299Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1499084Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1499822Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1500648Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1501560Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1502446Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1503328Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1504245Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1505196Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1506033Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1506614Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1507582Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1509403Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1511146Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1512981Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1514860Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1516965Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1523228Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1533982Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1540050Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1540973Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1541351Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1547691Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1554346Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1555648Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1556065Z       |        ^~~~~~~~
2025-08-14T21:34:19.1556687Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1557693Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1558569Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1559384Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1560142Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1560979Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1562017Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1563150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1564286Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1565392Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1566378Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1567349Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1568192Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1568742Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1569554Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1570298Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1570647Z       |                     ^~~~
2025-08-14T21:34:19.1571223Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1572065Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1572885Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1573677Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1574421Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1575277Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1576195Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1577112Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1578001Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1578951Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1579913Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1580754Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1581313Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1582282Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1583839Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1585547Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1587302Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1589164Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1591171Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1597524Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1608246Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1614455Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1615385Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1615756Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1622316Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1628905Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1630174Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1641133Z       |        ^~~~~~~~
2025-08-14T21:34:19.1641809Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1642801Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1643711Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1644522Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1645279Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1646232Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1647336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1648473Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1649623Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1650768Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1651771Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1652717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1653556Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1654099Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1655023Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1655762Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1656125Z       |                     ^~~~
2025-08-14T21:34:19.1656688Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1657543Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1658360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1659138Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1659880Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1660713Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1661629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1662536Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1663419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1664352Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1665305Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1666145Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1666682Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1667696Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1669264Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1670977Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1672887Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1674775Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1676838Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1683078Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1693655Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1699620Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1700539Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1700927Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1707239Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1714219Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1715505Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1715929Z       |        ^~~~~~~~
2025-08-14T21:34:19.1716625Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1717613Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1718503Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1719325Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1720092Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1720920Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1721973Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1723112Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1724254Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1725396Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1726432Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1727367Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1728210Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1728810Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1729644Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1730388Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1730735Z       |                     ^~~~
2025-08-14T21:34:19.1731305Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1732161Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1732971Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1733742Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1734486Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1735322Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1736236Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1737109Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1737992Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1738927Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1739882Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1740742Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1741294Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1742282Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1743841Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1745550Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1747306Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1749175Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1751219Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1757583Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1768182Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1774154Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1775069Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1775455Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1781811Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1788411Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1789689Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1790116Z       |        ^~~~~~~~
2025-08-14T21:34:19.1790749Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1791826Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1792712Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1793524Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1794290Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1795111Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1796162Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1797295Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1798434Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1799533Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1800536Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1801510Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1802348Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1802891Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1803729Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1804468Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1804817Z       |                     ^~~~
2025-08-14T21:34:19.1805379Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1806230Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1807041Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1807811Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1808549Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1809748Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1810713Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1811586Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1812472Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1813441Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1814393Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1815220Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1815777Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1816786Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1818342Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1820057Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1821793Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1823663Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1825679Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1832063Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1842647Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1848689Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1849606Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1849993Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1856323Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1862887Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1864171Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1864589Z       |        ^~~~~~~~
2025-08-14T21:34:19.1865213Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1866192Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1867084Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1867898Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1868657Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1869520Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1870598Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1872977Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1874211Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1875313Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1876320Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1877258Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1878102Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1878642Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1879523Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1880273Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1880613Z       |                     ^~~~
2025-08-14T21:34:19.1881188Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1882043Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1882861Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1883638Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1884385Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1885220Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1886142Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1887061Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1887947Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1888885Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1889845Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1890677Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1891229Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1892253Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1893816Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1895553Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1897338Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1899199Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1901263Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1907051Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1917341Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1922951Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1923880Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1924267Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.1930175Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.1936405Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.1937684Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.1938086Z       |        ^~~~~~~~
2025-08-14T21:34:19.1938711Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.1939706Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.1940594Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.1941394Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.1942156Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.1942990Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.1944047Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.1945171Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.1946346Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.1947455Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.1948456Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.1949375Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.1950218Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1950767Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1951682Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.1952416Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.1952771Z       |                     ^~~~
2025-08-14T21:34:19.1953344Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.1954184Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.1955057Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.1955869Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.1956607Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.1957428Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.1958518Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.1959409Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.1960292Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.1961215Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.1962238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.1963076Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.1963624Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.1964632Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.1966184Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.1967891Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.1970143Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.1972659Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.1974797Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.1981221Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.1991891Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.1997907Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.1998837Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.1999221Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.2005596Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.2012387Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.2013676Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.2014086Z       |        ^~~~~~~~
2025-08-14T21:34:19.2014713Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.2015709Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.2016690Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.2017531Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.2018290Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.2019126Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.2020208Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.2021339Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.2022478Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.2023591Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.2024592Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.2025513Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.2026356Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2026902Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2027732Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.2028455Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.2028803Z       |                     ^~~~
2025-08-14T21:34:19.2029376Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.2030215Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.2031020Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.2031865Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.2032662Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.2033485Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.2034395Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.2035282Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.2036163Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.2037078Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.2038026Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.2038867Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2039418Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2040401Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.2041985Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.2043719Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.2045473Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.2047373Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.2049388Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.2055600Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.2066295Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.2072400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.2073328Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.2073744Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.2080037Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.2086590Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.2087861Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.2088267Z       |        ^~~~~~~~
2025-08-14T21:34:19.2088890Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.2089889Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.2090753Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.2091563Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.2092364Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.2093200Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.2094238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.2095369Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.2096510Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.2097617Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.2098619Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.2099540Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.2100377Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2100962Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2101805Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.2102541Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.2102886Z       |                     ^~~~
2025-08-14T21:34:19.2103455Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.2104330Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.2105137Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.2105921Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.2106660Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.2107482Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.2108394Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.2109592Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.2110474Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.2111407Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.2112443Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.2113288Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2113829Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2114840Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.2116395Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.2118296Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.2120081Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.2121954Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.2124058Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.2130359Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.2140947Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.2146910Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.2147828Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.2148223Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.2154677Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.2161279Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.2162590Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.2163010Z       |        ^~~~~~~~
2025-08-14T21:34:19.2163624Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.2164691Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.2165579Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.2166393Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.2167141Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.2167984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.2169029Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.2170156Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.2171285Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.2172389Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.2173384Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.2174320Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.2175159Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2175693Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2176941Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.2178089Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.2178433Z       |                     ^~~~
2025-08-14T21:34:19.2179006Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.2179856Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.2180674Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.2181453Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.2182196Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.2183030Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.2183950Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.2184820Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.2185731Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.2186664Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.2187649Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.2188474Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2189021Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2190110Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.2191777Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.2193498Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.2195248Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.2197122Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.2199141Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.2204951Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.2215033Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.2220769Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.2221744Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.2222130Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.2227997Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.2234259Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.2235544Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.2235947Z       |        ^~~~~~~~
2025-08-14T21:34:19.2236569Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.2237674Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.2238554Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.2239353Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.2240112Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.2240947Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.2241994Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.2243109Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.2244248Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.2245357Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.2246388Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.2247363Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.2248201Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2248754Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2249620Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.2250347Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.2250693Z       |                     ^~~~
2025-08-14T21:34:19.2251263Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:19.2252122Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:19.2252920Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:19.2253705Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:19.2254444Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:19.2255275Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:19.2256180Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:19.2257063Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:19.2257945Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:19.2258875Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:19.2259814Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:19.2260648Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2261197Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2262202Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:19.2263757Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:19.2265472Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:19.2267229Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:19.2269107Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:19.2271121Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:19.2277488Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:19.2288109Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:19.2294106Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:19.2295035Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:19.2295421Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:19.2301734Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:19.2308307Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:19.2309830Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:19.2310242Z       |        ^~~~~~~~
2025-08-14T21:34:19.2310867Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:19.2311931Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:19.2312818Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:19.2313616Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:19.2314376Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:19.2315215Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:19.2316269Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:19.2317388Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:19.2318522Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:19.2320166Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:19.2321172Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:19.2322092Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:19.2323034Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:19.2323587Z                  from rng_extension.cpp:1:
2025-08-14T21:34:19.2324445Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:19.2325173Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:19.2325524Z       |                     ^~~~
2025-08-14T21:34:19.2328811Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:19.6892374Z running install_lib
2025-08-14T21:34:19.6982210Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages
2025-08-14T21:34:19.6985321Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:19.6986962Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:19.6989122Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:19.7060160Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:19.7132687Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:19.7211936Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension/__init__.py to __init__.cpython-313.pyc
2025-08-14T21:34:19.7214067Z running install_egg_info
2025-08-14T21:34:19.7408474Z running egg_info
2025-08-14T21:34:19.7486234Z creating torch_test_cpp_extension.egg-info
2025-08-14T21:34:19.7487730Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-08-14T21:34:19.7490974Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-08-14T21:34:19.7492749Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-08-14T21:34:19.7494786Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-08-14T21:34:19.7495654Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:19.7579242Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:19.7586437Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:19.7588060Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info
2025-08-14T21:34:19.7593878Z running install_scripts
2025-08-14T21:34:22.8305506Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:22.8307349Z   import pkg_resources
2025-08-14T21:34:22.8618231Z 
2025-08-14T21:34:22.8618405Z Running tests...
2025-08-14T21:34:22.8618726Z ----------------------------------------------------------------------
2025-08-14T21:34:22.8747402Z .
2025-08-14T21:34:22.8747717Z ----------------------------------------------------------------------
2025-08-14T21:34:22.8748088Z Ran 1 test in 0.013s
2025-08-14T21:34:22.8748270Z 
2025-08-14T21:34:22.8748351Z OK
2025-08-14T21:34:22.8748475Z 
2025-08-14T21:34:22.8748598Z Generating XML reports...
2025-08-14T21:34:23.6034178Z Running test_cpp_extensions_aot_no_ninja 1/1 ... [2025-08-14 21:34:23.603060]
2025-08-14T21:34:25.9404170Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:25.9405754Z   import pkg_resources
2025-08-14T21:34:26.0085414Z running install
2025-08-14T21:34:26.0087580Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:26.0088383Z !!
2025-08-14T21:34:26.0088509Z 
2025-08-14T21:34:26.0088863Z         ********************************************************************************
2025-08-14T21:34:26.0089272Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:26.0089734Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:26.0090111Z         standards-based tools.
2025-08-14T21:34:26.0090301Z 
2025-08-14T21:34:26.0090543Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:26.0091034Z         or your builds will no longer be supported.
2025-08-14T21:34:26.0091336Z 
2025-08-14T21:34:26.0091641Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:26.0092172Z         ********************************************************************************
2025-08-14T21:34:26.0092412Z 
2025-08-14T21:34:26.0092507Z !!
2025-08-14T21:34:26.0092717Z   self.initialize_options()
2025-08-14T21:34:26.0224408Z running build
2025-08-14T21:34:26.0224858Z running build_py
2025-08-14T21:34:26.0311331Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:26.0313859Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:26.0316889Z running build_ext
2025-08-14T21:34:26.0333250Z building 'torch_test_cpp_extension.cpp' extension
2025-08-14T21:34:26.0335060Z creating build/temp.linux-x86_64-cpython-313
2025-08-14T21:34:26.0340145Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-08-14T21:34:27.1108412Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12,
2025-08-14T21:34:27.1110295Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11,
2025-08-14T21:34:27.1111861Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9,
2025-08-14T21:34:27.1112771Z                  from extension.cpp:1:
2025-08-14T21:34:27.1114624Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_<MatrixMultiplier>’:
2025-08-14T21:34:27.1115495Z extension.cpp:45:53:   required from here
2025-08-14T21:34:27.1116984Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1539:7: warning: ‘pybind11::class_<MatrixMultiplier>’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes]
2025-08-14T21:34:27.1120259Z  1539 | class class_ : public detail::generic_type {
2025-08-14T21:34:27.1120629Z       |       ^~~~~~
2025-08-14T21:34:27.1122390Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< <template-parameter-1-1>, <template-parameter-1-2> >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’:
2025-08-14T21:34:27.1123814Z extension.cpp:45:53:   required from here
2025-08-14T21:34:27.1126614Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1599:28: warning: ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>’ declared with greater visibility than the type of its field ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>::<record capture>’ [-Wattributes]
2025-08-14T21:34:27.1128624Z  1599 |             with_internals([&](internals &internals) {
2025-08-14T21:34:27.1128993Z       |                            ^~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:27.1129517Z  1600 |                 auto &instances = record.module_local ? get_local_internals().registered_types_cpp
2025-08-14T21:34:27.1130091Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:27.1130606Z  1601 |                                                       : internals.registered_types_cpp;
2025-08-14T21:34:27.1130999Z       |                                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:27.1131419Z  1602 |                 instances[std::type_index(typeid(type_alias))]
2025-08-14T21:34:27.1131823Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:27.1132213Z  1603 |                     = instances[std::type_index(typeid(type))];
2025-08-14T21:34:27.1132601Z       |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:27.1132931Z  1604 |             });
2025-08-14T21:34:27.1133183Z       |             ~               
2025-08-14T21:34:27.1136473Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:27.7418581Z building 'torch_test_cpp_extension.maia' extension
2025-08-14T21:34:27.7423713Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-08-14T21:34:28.8377275Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:29.4491874Z building 'torch_test_cpp_extension.rng' extension
2025-08-14T21:34:29.4496160Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-08-14T21:34:30.6970173Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:30.6971703Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:30.6972938Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:30.6974434Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:30.6975546Z                  from rng_extension.cpp:6:
2025-08-14T21:34:30.6977420Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:30.6978765Z  1478 | #pragma unroll
2025-08-14T21:34:30.6979144Z       | 
2025-08-14T21:34:30.6980061Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4,
2025-08-14T21:34:30.6981673Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530,
2025-08-14T21:34:30.6983210Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:30.6984673Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:30.6985997Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:30.6987642Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:30.6988797Z                  from rng_extension.cpp:6:
2025-08-14T21:34:30.6990562Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:30.6992046Z    59 | #pragma unroll
2025-08-14T21:34:30.6992462Z       | 
2025-08-14T21:34:30.6994122Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:30.6995520Z    72 | #pragma unroll
2025-08-14T21:34:30.6995929Z       | 
2025-08-14T21:34:30.6997353Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:30.6998607Z    87 | #pragma unroll
2025-08-14T21:34:30.6999002Z       | 
2025-08-14T21:34:30.6999874Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531,
2025-08-14T21:34:30.7000936Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:30.7001751Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:30.7002557Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:30.7003462Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:30.7004134Z                  from rng_extension.cpp:6:
2025-08-14T21:34:30.7005242Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:30.7006097Z   160 | #pragma unroll
2025-08-14T21:34:30.7006331Z       | 
2025-08-14T21:34:30.7006844Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7007698Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7008508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7009714Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7010472Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7011311Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7012230Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7013106Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7013983Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7014915Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7015870Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7016691Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7017239Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7018318Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7019892Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7021671Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7023423Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7025299Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7027321Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7033690Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7044311Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7050266Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7051181Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7051563Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7057883Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7064446Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7065723Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7066173Z       |        ^~~~~~~~
2025-08-14T21:34:30.7066779Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7067773Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7068685Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7069494Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7070238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7071070Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7072194Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7073330Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7074489Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7075606Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7076596Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7077535Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7078377Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7078935Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7079753Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7080496Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7080849Z       |                     ^~~~
2025-08-14T21:34:30.7081469Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7082327Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7083138Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7083930Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7084663Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7085498Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7086420Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7087312Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7088180Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7089113Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7090098Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7090962Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7091749Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7092742Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7094328Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7096029Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7097779Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7099645Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7101666Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7107799Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7118502Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7124412Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7125381Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7125755Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7131943Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7138387Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7139665Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7140078Z       |        ^~~~~~~~
2025-08-14T21:34:30.7140700Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7141724Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7142609Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7143421Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7144178Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7145000Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7146048Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7147185Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7148322Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7149418Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7150448Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7151403Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7152341Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7152878Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7153750Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7154484Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7154832Z       |                     ^~~~
2025-08-14T21:34:30.7155391Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7156246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7157056Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7157841Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7158567Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7159406Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7160323Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7161203Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7162070Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7162999Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7163947Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7164784Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7165322Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7166330Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7167886Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7169594Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7171350Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7173208Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7175258Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7181048Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7190891Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7196583Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7197557Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7197939Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7203820Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7210186Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7211589Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7212004Z       |        ^~~~~~~~
2025-08-14T21:34:30.7212660Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7213660Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7214537Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7215352Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7216103Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7216941Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7217991Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7219130Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7220257Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7221373Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7222377Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7223316Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7224145Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7224700Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7225571Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7226316Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7226652Z       |                     ^~~~
2025-08-14T21:34:30.7227231Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7228086Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7228899Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7229674Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7230417Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7231256Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7232230Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7233114Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7234041Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7234997Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7235952Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7236778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7237356Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7238346Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7239895Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7241581Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7243332Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7245204Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7247214Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7253348Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7263734Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7269653Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7270572Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7270952Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7288417Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7295244Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7296638Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7297051Z       |        ^~~~~~~~
2025-08-14T21:34:30.7297679Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7298681Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7299567Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7300367Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7301124Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7301957Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7303017Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7304139Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7305317Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7306469Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7307473Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7308405Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7309486Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7310044Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7310891Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7311695Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7312047Z       |                     ^~~~
2025-08-14T21:34:30.7312627Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7313468Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7314277Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7315069Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7315810Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7316629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7317546Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7318432Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7319315Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7320235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7321274Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7322114Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7322666Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7323668Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7325232Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7326939Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7328705Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7330648Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7332672Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7338509Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7348348Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7354036Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7354971Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7355353Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7361269Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7367484Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7368812Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7369230Z       |        ^~~~~~~~
2025-08-14T21:34:30.7369852Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7370841Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7371728Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7372545Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7373303Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7374128Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7375183Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7376314Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7377457Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7378572Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7379561Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7380552Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7381395Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7381951Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7382764Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7383509Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7383867Z       |                     ^~~~
2025-08-14T21:34:30.7384428Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7385278Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7386088Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7386882Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7387612Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7388446Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7389415Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7390346Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7391217Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7392278Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7393281Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7394125Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7394664Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7395671Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7397230Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7398937Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7400700Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7402574Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7404587Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7411161Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7420999Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7426688Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7427600Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7427989Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7433918Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7440163Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7441443Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7441861Z       |        ^~~~~~~~
2025-08-14T21:34:30.7442475Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7443529Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7444435Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7445248Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7445996Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7446836Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7447890Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7449071Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7450200Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7451347Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7452357Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7453339Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7454172Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7454726Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7455566Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7456301Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7456640Z       |                     ^~~~
2025-08-14T21:34:30.7457213Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7458063Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7458872Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7459649Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7460392Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7461238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7462158Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7463031Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7463919Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7464852Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7465866Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7466695Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7467246Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7468242Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7469794Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7471617Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7473395Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7475318Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7477376Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7483159Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7492984Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7498577Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7499505Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7499892Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7505795Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7512316Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7513718Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7514122Z       |        ^~~~~~~~
2025-08-14T21:34:30.7514747Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7515752Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7516638Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7517439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7518200Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7519041Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7520092Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7521215Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7522358Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7523473Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7524477Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7525460Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7526308Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7526859Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7527694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7528421Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7528771Z       |                     ^~~~
2025-08-14T21:34:30.7529345Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7530182Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7530993Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7531782Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7532524Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7533396Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7534316Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7535246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7536134Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7537088Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7538054Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7538894Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7539442Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7540414Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7541964Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7543673Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7545426Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7547291Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7549301Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7555539Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7565935Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7571842Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7572766Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7573137Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7579348Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7585807Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7587072Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7587489Z       |        ^~~~~~~~
2025-08-14T21:34:30.7588119Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7589111Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7589982Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7590793Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7591608Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7592443Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7593515Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7594680Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7595820Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7596959Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7597945Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7598880Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7599723Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7600278Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7601096Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7601832Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7602177Z       |                     ^~~~
2025-08-14T21:34:30.7602737Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7603595Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7604402Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7605189Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7605912Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7606745Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7607661Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7608546Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7609898Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7610835Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7611792Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7612633Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7613172Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7614190Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7615745Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7617448Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7619254Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7621161Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7623172Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7628996Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7638840Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7644438Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7645347Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7645732Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7651605Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7657826Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7659101Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7659521Z       |        ^~~~~~~~
2025-08-14T21:34:30.7660129Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7661121Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7662004Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7662821Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7663566Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7664404Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7665452Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7666591Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7667729Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7668859Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7669859Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7670794Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7671694Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7672234Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7673067Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7673808Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7674140Z       |                     ^~~~
2025-08-14T21:34:30.7674725Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7675577Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7676386Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7677238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7677984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7678848Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7679768Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7680669Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7681551Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7682481Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7683435Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7684265Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7684811Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7685791Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7687345Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7689043Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7690776Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7692643Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7694685Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7700476Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7710502Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7716264Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7717190Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7717570Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7723475Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7729652Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7730922Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7731328Z       |        ^~~~~~~~
2025-08-14T21:34:30.7731951Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7732945Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7733834Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7734629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7735383Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7736240Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7737290Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7738435Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7739574Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7740714Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7741714Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7742643Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7743479Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7744032Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7744855Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7745575Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7745926Z       |                     ^~~~
2025-08-14T21:34:30.7746501Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7747353Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7748151Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7748940Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7749681Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7750515Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7751419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7752456Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7753338Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7754268Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7755220Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7756062Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7756617Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7757590Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7759156Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7760860Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7762635Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7764531Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7766590Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7772389Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7782161Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7787764Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7788693Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7789080Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7795079Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7801290Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7802575Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7802997Z       |        ^~~~~~~~
2025-08-14T21:34:30.7803609Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7804608Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7805532Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7806349Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7807097Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7807994Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7809274Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7810408Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7811535Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7812659Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7813689Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7814702Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7815590Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7816138Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7816973Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7817709Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7818086Z       |                     ^~~~
2025-08-14T21:34:30.7818664Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7819515Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7820314Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7821102Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7821848Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7822687Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7823590Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7824478Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7825360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7826300Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7827237Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7828075Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7828622Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7829606Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7831209Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7832987Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7834741Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7836614Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7838640Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7844450Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7854238Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7859837Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7860761Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7861142Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7867045Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7873354Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7874660Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7875060Z       |        ^~~~~~~~
2025-08-14T21:34:30.7875682Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7876676Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7877589Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7878400Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7879161Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7879995Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7881037Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7882166Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7883306Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7884418Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7885413Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7886335Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7887173Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7887719Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7888542Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7889268Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7889612Z       |                     ^~~~
2025-08-14T21:34:30.7890224Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7891067Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7891885Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7892670Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7893415Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7894236Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7895149Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7896040Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7896920Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7897868Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7898819Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7899683Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7900231Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7901199Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7902790Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7904500Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7906254Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7908129Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7910373Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7919411Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.7929885Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.7936352Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.7937332Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.7937722Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.7943925Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.7950514Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.7951889Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.7952313Z       |        ^~~~~~~~
2025-08-14T21:34:30.7952999Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.7953983Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.7954872Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.7955764Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.7956522Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.7957339Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.7958386Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.7959518Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.7960656Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.7961752Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.7962785Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.7963717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.7964549Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7965118Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7965987Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.7966783Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.7967133Z       |                     ^~~~
2025-08-14T21:34:30.7967690Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.7968544Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.7969360Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.7970129Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.7970868Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.7971703Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.7972619Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.7973489Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.7974370Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.7975299Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.7976248Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.7977180Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.7977787Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.7978793Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.7980407Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.7982124Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.7983863Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.7985739Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.7987754Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.7994089Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8004688Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8010863Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8011778Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8012253Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8018554Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8025131Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8026452Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8026869Z       |        ^~~~~~~~
2025-08-14T21:34:30.8027498Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8028477Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8029366Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8030177Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8030933Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8031829Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8032877Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8034010Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8035151Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8036242Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8037238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8038236Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8039076Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8039617Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8040483Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8041226Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8041564Z       |                     ^~~~
2025-08-14T21:34:30.8042138Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8042993Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8043810Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8044583Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8045323Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8046154Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8047101Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8047971Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8048851Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8049812Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8050779Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8051608Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8052161Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8053153Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8054708Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8056417Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8058154Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8060031Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8062045Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8068329Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8078954Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8084979Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8085893Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8086281Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8092599Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8099160Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8100439Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8100855Z       |        ^~~~~~~~
2025-08-14T21:34:30.8101478Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8102459Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8103347Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8104154Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8104907Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8105732Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8106808Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8107939Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8109251Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8110417Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8111422Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8112439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8113280Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8113820Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8114662Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8115397Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8115735Z       |                     ^~~~
2025-08-14T21:34:30.8116307Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8117159Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8117965Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8118737Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8119479Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8120313Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8121225Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8122187Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8123073Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8124052Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8125012Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8125844Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8126399Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8127391Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8128946Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8130651Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8132388Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8134296Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8136364Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8142585Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8153243Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8159218Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8160134Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8160519Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8166815Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8173390Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8174662Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8175082Z       |        ^~~~~~~~
2025-08-14T21:34:30.8175690Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8176681Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8177564Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8178373Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8179120Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8179951Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8180998Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8182167Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8183305Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8184431Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8185437Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8186372Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8187209Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8187754Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8188575Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8189311Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8189644Z       |                     ^~~~
2025-08-14T21:34:30.8190220Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8191102Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8191968Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8192744Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8193525Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8194366Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8195283Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8196156Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8197042Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8197978Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8198934Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8199767Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8200320Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8201309Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8202865Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8204576Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8206308Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8208218Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8210540Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8216781Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8227624Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8233718Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8234640Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8235029Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8241410Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8247941Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8249212Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8249628Z       |        ^~~~~~~~
2025-08-14T21:34:30.8250241Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8251280Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8252157Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8252968Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8253749Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8254578Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8255628Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8256758Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8257897Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8258991Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8259997Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8260929Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8261765Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8262307Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8263128Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8263864Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8264197Z       |                     ^~~~
2025-08-14T21:34:30.8264766Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8265615Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8266461Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8267239Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8267977Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8268846Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8269769Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8270644Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8271619Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8272569Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8273525Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8274351Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8274906Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8275930Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8277481Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8279225Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8280961Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8282832Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8284844Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8291107Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8301660Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8307635Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8308546Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8308929Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8315534Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8322149Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8323421Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8323836Z       |        ^~~~~~~~
2025-08-14T21:34:30.8324448Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8325440Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8326378Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8327187Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8327932Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8328804Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8329859Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8331000Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8332128Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8333236Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8334239Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8335173Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8336047Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8336584Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8337407Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8338232Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8338605Z       |                     ^~~~
2025-08-14T21:34:30.8339176Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8340021Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8340849Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8341624Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8342368Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8343205Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8344131Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8345004Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8345886Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8346825Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8347782Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8348610Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8349165Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8350202Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8351843Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8353617Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8355366Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8357232Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8359253Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8365484Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8376059Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8382036Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8382958Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8383339Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8389658Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8396301Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8397608Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8398025Z       |        ^~~~~~~~
2025-08-14T21:34:30.8398635Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8399625Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8400507Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8401326Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8402066Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8402895Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8403954Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8405086Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8406212Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8407319Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8408315Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8409466Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8410381Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8410921Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8411765Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8412502Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8412836Z       |                     ^~~~
2025-08-14T21:34:30.8413481Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8414341Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8415153Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8415921Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8416675Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8417508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8418423Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8419297Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8420216Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8421146Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8422099Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8422964Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8423516Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8424509Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8426058Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8427755Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8429504Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8431369Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8433448Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8439866Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8450610Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8456632Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8457557Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8457940Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8464223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8470812Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8472157Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8472573Z       |        ^~~~~~~~
2025-08-14T21:34:30.8473221Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8474218Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8475099Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8475911Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8476661Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8477494Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8478546Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8479677Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8480831Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8481940Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8482967Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8483898Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8484723Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8485275Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8486101Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8486841Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8487175Z       |                     ^~~~
2025-08-14T21:34:30.8487749Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8488606Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8489416Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8490187Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8490933Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8491773Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8492695Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8493570Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8494493Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8495428Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8496383Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8497238Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8497797Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8498785Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8500340Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8502043Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8503797Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8505669Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8507715Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8514259Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8524883Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8530835Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8531760Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8532143Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8538425Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8545037Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8546316Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8546735Z       |        ^~~~~~~~
2025-08-14T21:34:30.8547345Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8560622Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8561679Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8562487Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8563257Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8564100Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8565155Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8566276Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8567525Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8568644Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8569688Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8570615Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8571457Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8572014Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8572921Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8573655Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8574012Z       |                     ^~~~
2025-08-14T21:34:30.8574588Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8575431Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8576246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8577067Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8577811Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8578632Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8579635Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8580526Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8581411Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8582334Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8583291Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8584132Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8584682Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8585683Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8587243Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8588952Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8590711Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8592740Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8594772Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8600588Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8610612Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8616346Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8617277Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8617652Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8623538Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8629757Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8631028Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8631439Z       |        ^~~~~~~~
2025-08-14T21:34:30.8632132Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8633125Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8634014Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8634829Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8635593Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8636450Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8637495Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8638629Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8639803Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8640918Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8641909Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8642846Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8643686Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8644239Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8645056Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8645803Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8646148Z       |                     ^~~~
2025-08-14T21:34:30.8646709Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8647560Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8647925Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8648244Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8648544Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8648965Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8649377Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8649771Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8650176Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8650603Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8651018Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8651329Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8651457Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8652216Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8653067Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8654003Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8654977Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8656027Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8657130Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8662403Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8668381Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8669194Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8669363Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8669529Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8675674Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8677008Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8677219Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8677309Z       |        ^~~~~~~~
2025-08-14T21:34:30.8677788Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8678204Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8678564Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8678908Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8679201Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8679628Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8680171Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8680682Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8681227Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8681697Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8682119Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8682520Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8682849Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8682964Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8683555Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8683708Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8683804Z       |                     ^~~~
2025-08-14T21:34:30.8684233Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8684572Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8684913Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8685277Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8685575Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8685994Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8686373Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8686753Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8687142Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8687570Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8687986Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8688297Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8688409Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8689175Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8690032Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8690961Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8691902Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8692981Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8694053Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8699308Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8705285Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8706089Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8706259Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8706372Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8712861Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8714158Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8714368Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8714458Z       |        ^~~~~~~~
2025-08-14T21:34:30.8714979Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8715393Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8715751Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8716133Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8716426Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8716853Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8717370Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8717881Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8718397Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8718868Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8719292Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8719691Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8720018Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8720133Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8720725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8720876Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8720968Z       |                     ^~~~
2025-08-14T21:34:30.8721351Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8721740Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8722081Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8722414Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8722737Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8723152Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8723544Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8723922Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8724316Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8724745Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8725145Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8725468Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8725608Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8726372Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8727228Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8728197Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8729109Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8730162Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8731235Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8736527Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8742464Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8743305Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8743477Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8743625Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8749695Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8750947Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8751166Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8751254Z       |        ^~~~~~~~
2025-08-14T21:34:30.8751801Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8752261Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8752610Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8752995Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8753288Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8753719Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8754231Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8754732Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8755262Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8755726Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8756150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8756581Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8756896Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8757025Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8757658Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8757809Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8757902Z       |                     ^~~~
2025-08-14T21:34:30.8758286Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8758642Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8758986Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8759304Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8759614Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8760027Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8760415Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8760793Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8761171Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8761616Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8762017Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8762343Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8762459Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8763249Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8764118Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8765095Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8766024Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8767061Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8768146Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8772978Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8778525Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8779340Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8779532Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8779662Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8785308Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8786574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8786813Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8786915Z       |        ^~~~~~~~
2025-08-14T21:34:30.8787410Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8787835Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8788183Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8788523Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8788831Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8789244Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8789770Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8790272Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8790792Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8791274Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8791757Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8792177Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8792490Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8792606Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8793251Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8793391Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8793498Z       |                     ^~~~
2025-08-14T21:34:30.8793883Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:30.8794255Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:30.8794613Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:30.8794929Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:30.8795237Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:30.8795651Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:30.8796029Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:30.8796421Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:30.8796799Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:30.8797265Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:30.8797664Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:30.8797975Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8798129Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8798882Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:30.8799746Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:30.8800661Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:30.8801582Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:30.8802625Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:30.8803712Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:30.8809173Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:30.8815150Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:30.8816092Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:30.8816248Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:30.8816363Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:30.8822694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:30.8824030Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:30.8824246Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:30.8824351Z       |        ^~~~~~~~
2025-08-14T21:34:30.8824830Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:30.8825281Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:30.8825646Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:30.8825984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:30.8826276Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:30.8826708Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:30.8827221Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:30.8827731Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:30.8828249Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:30.8828747Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:30.8829172Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:30.8829601Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:30.8829927Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:30.8830042Z                  from rng_extension.cpp:1:
2025-08-14T21:34:30.8830642Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:30.8830792Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:30.8830888Z       |                     ^~~~
2025-08-14T21:34:30.8834073Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:31.3527096Z running install_lib
2025-08-14T21:34:31.3616706Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:31.3693421Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:31.3773615Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:31.3860572Z running install_egg_info
2025-08-14T21:34:31.4055118Z running egg_info
2025-08-14T21:34:31.4139955Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-08-14T21:34:31.4143449Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-08-14T21:34:31.4155702Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-08-14T21:34:31.4166510Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-08-14T21:34:31.4258113Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:31.4266311Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:31.4277195Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it)
2025-08-14T21:34:31.4278923Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info
2025-08-14T21:34:31.4284855Z running install_scripts
2025-08-14T21:34:33.6444972Z running install
2025-08-14T21:34:33.6446575Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:33.6447376Z !!
2025-08-14T21:34:33.6447522Z 
2025-08-14T21:34:33.6447647Z         ********************************************************************************
2025-08-14T21:34:33.6448277Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:33.6448680Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:33.6449061Z         standards-based tools.
2025-08-14T21:34:33.6449264Z 
2025-08-14T21:34:33.6449493Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:33.6450069Z         or your builds will no longer be supported.
2025-08-14T21:34:33.6450313Z 
2025-08-14T21:34:33.6450636Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:33.6451174Z         ********************************************************************************
2025-08-14T21:34:33.6451427Z 
2025-08-14T21:34:33.6451511Z !!
2025-08-14T21:34:33.6451740Z   self.initialize_options()
2025-08-14T21:34:33.6587877Z running build
2025-08-14T21:34:33.6588351Z running build_ext
2025-08-14T21:34:33.6923269Z building 'no_python_abi_suffix_test' extension
2025-08-14T21:34:33.6926470Z creating /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313
2025-08-14T21:34:33.8129704Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/no_python_abi_suffix_test.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=no_python_abi_suffix_test -std=c++17
2025-08-14T21:34:33.8179686Z creating build/lib.linux-x86_64-cpython-313
2025-08-14T21:34:33.8184381Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so
2025-08-14T21:34:33.9262253Z running install_lib
2025-08-14T21:34:33.9359483Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages
2025-08-14T21:34:33.9363107Z copying build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages
2025-08-14T21:34:33.9369621Z running install_egg_info
2025-08-14T21:34:33.9579542Z running egg_info
2025-08-14T21:34:33.9660259Z creating no_python_abi_suffix_test.egg-info
2025-08-14T21:34:33.9660978Z writing no_python_abi_suffix_test.egg-info/PKG-INFO
2025-08-14T21:34:33.9665966Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt
2025-08-14T21:34:33.9668445Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt
2025-08-14T21:34:33.9670030Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-08-14T21:34:33.9756856Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-08-14T21:34:33.9764668Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-08-14T21:34:33.9766252Z Copying no_python_abi_suffix_test.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info
2025-08-14T21:34:33.9772397Z running install_scripts
2025-08-14T21:34:34.4839623Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:34:34.4842530Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_aot_no_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:34:34.484019]
2025-08-14T21:34:37.8018942Z 
2025-08-14T21:34:37.8020253Z test_cpp_extensions_aot_no_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_no_ninja_1.1_720913e1b5fb22bf_.log
2025-08-14T21:34:37.8029353Z Running 21 items in this shard: test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_no_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_no_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_no_ninja.py::TestTorchLibrary::test_torch_library
2025-08-14T21:34:37.8037625Z 
2025-08-14T21:34:37.8037978Z Running test_autoload_disable 1/1 ... [2025-08-14 21:34:37.802115]
2025-08-14T21:34:40.1637769Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:40.1639343Z   import pkg_resources
2025-08-14T21:34:40.2323533Z running install
2025-08-14T21:34:40.2325579Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:40.2326388Z !!
2025-08-14T21:34:40.2326511Z 
2025-08-14T21:34:40.2326633Z         ********************************************************************************
2025-08-14T21:34:40.2327017Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:40.2327422Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:40.2327789Z         standards-based tools.
2025-08-14T21:34:40.2327986Z 
2025-08-14T21:34:40.2328439Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:40.2328924Z         or your builds will no longer be supported.
2025-08-14T21:34:40.2329167Z 
2025-08-14T21:34:40.2329468Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:40.2329997Z         ********************************************************************************
2025-08-14T21:34:40.2330320Z 
2025-08-14T21:34:40.2330402Z !!
2025-08-14T21:34:40.2330634Z   self.initialize_options()
2025-08-14T21:34:40.2462247Z running build
2025-08-14T21:34:40.2462563Z running build_py
2025-08-14T21:34:40.2550940Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:40.2553573Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:40.2556702Z running build_ext
2025-08-14T21:34:40.2573653Z building 'torch_test_cpp_extension.cpp' extension
2025-08-14T21:34:40.2575453Z creating build/temp.linux-x86_64-cpython-313
2025-08-14T21:34:40.2580558Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-08-14T21:34:41.3944634Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12,
2025-08-14T21:34:41.3945661Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11,
2025-08-14T21:34:41.3946540Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9,
2025-08-14T21:34:41.3947096Z                  from extension.cpp:1:
2025-08-14T21:34:41.3948364Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_<MatrixMultiplier>’:
2025-08-14T21:34:41.3949393Z extension.cpp:45:53:   required from here
2025-08-14T21:34:41.3950864Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1539:7: warning: ‘pybind11::class_<MatrixMultiplier>’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes]
2025-08-14T21:34:41.3952238Z  1539 | class class_ : public detail::generic_type {
2025-08-14T21:34:41.3952724Z       |       ^~~~~~
2025-08-14T21:34:41.3954589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< <template-parameter-1-1>, <template-parameter-1-2> >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’:
2025-08-14T21:34:41.3955992Z extension.cpp:45:53:   required from here
2025-08-14T21:34:41.3958420Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:1599:28: warning: ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>’ declared with greater visibility than the type of its field ‘pybind11::class_<MatrixMultiplier>::class_<>(pybind11::handle, const char*)::<lambda(pybind11::detail::internals&)>::<record capture>’ [-Wattributes]
2025-08-14T21:34:41.3960353Z  1599 |             with_internals([&](internals &internals) {
2025-08-14T21:34:41.3960746Z       |                            ^~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:41.3961269Z  1600 |                 auto &instances = record.module_local ? get_local_internals().registered_types_cpp
2025-08-14T21:34:41.3961936Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:41.3962378Z  1601 |                                                       : internals.registered_types_cpp;
2025-08-14T21:34:41.3962791Z       |                                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:41.3963273Z  1602 |                 instances[std::type_index(typeid(type_alias))]
2025-08-14T21:34:41.3963681Z       |                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:41.3964066Z  1603 |                     = instances[std::type_index(typeid(type))];
2025-08-14T21:34:41.3964462Z       |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:41.3964862Z  1604 |             });
2025-08-14T21:34:41.3965106Z       |             ~               
2025-08-14T21:34:41.3968416Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:42.1118359Z building 'torch_test_cpp_extension.maia' extension
2025-08-14T21:34:42.1123915Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-08-14T21:34:43.2356924Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:43.9488726Z building 'torch_test_cpp_extension.rng' extension
2025-08-14T21:34:43.9493404Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-08-14T21:34:45.1915461Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:45.1917047Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:45.1918565Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:45.1920141Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:45.1921126Z                  from rng_extension.cpp:6:
2025-08-14T21:34:45.1922781Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:45.1924050Z  1478 | #pragma unroll
2025-08-14T21:34:45.1924421Z       | 
2025-08-14T21:34:45.1925262Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4,
2025-08-14T21:34:45.1926723Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530,
2025-08-14T21:34:45.1928117Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:45.1929433Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:45.1930778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:45.1932301Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:45.1933432Z                  from rng_extension.cpp:6:
2025-08-14T21:34:45.1935026Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:45.1936326Z    59 | #pragma unroll
2025-08-14T21:34:45.1936749Z       | 
2025-08-14T21:34:45.1938104Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:45.1939069Z    72 | #pragma unroll
2025-08-14T21:34:45.1939611Z       | 
2025-08-14T21:34:45.1941066Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:45.1942212Z    87 | #pragma unroll
2025-08-14T21:34:45.1942460Z       | 
2025-08-14T21:34:45.1943120Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531,
2025-08-14T21:34:45.1944033Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8,
2025-08-14T21:34:45.1944851Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7,
2025-08-14T21:34:45.1945643Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37,
2025-08-14T21:34:45.1946565Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9,
2025-08-14T21:34:45.1947238Z                  from rng_extension.cpp:6:
2025-08-14T21:34:45.1948215Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas]
2025-08-14T21:34:45.1949001Z   160 | #pragma unroll
2025-08-14T21:34:45.1949245Z       | 
2025-08-14T21:34:45.1949758Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.1950789Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.1951740Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.1952527Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.1953320Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.1954149Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.1955048Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.1955938Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.1956828Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.1957758Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.1958698Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.1959536Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.1960184Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.1961261Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.1962833Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.1964580Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.1966382Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.1968260Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.1970307Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.1976922Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.1987686Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.1993854Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.1994788Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.1995166Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2001531Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2008229Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2009699Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2010140Z       |        ^~~~~~~~
2025-08-14T21:34:45.2010772Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2011834Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2012715Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2013528Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2014334Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2015152Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2016196Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2017333Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2018474Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2019581Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2020569Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2021499Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2022335Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2022892Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2023725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2024465Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2024815Z       |                     ^~~~
2025-08-14T21:34:45.2025377Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2026229Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2027076Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2027864Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2028592Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2029488Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2030410Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2031291Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2032256Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2033188Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2034144Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2034989Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2035564Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2036576Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2038141Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2039893Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2041637Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2043504Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2045508Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2051652Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2062018Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2067899Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2068813Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2069191Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2075423Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2081923Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2083202Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2083617Z       |        ^~~~~~~~
2025-08-14T21:34:45.2084238Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2085221Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2086138Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2086948Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2087699Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2088545Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2089599Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2090728Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2091862Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2092962Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2093964Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2094900Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2095767Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2096307Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2097134Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2097873Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2098249Z       |                     ^~~~
2025-08-14T21:34:45.2098815Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2099666Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2100471Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2101255Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2101984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2102814Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2103729Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2104607Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2105488Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2106418Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2107371Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2108212Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2108752Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2109949Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2111651Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2113438Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2115191Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2117051Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2119075Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2124878Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2134764Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2140371Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2141298Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2141687Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2147697Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2154283Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2155720Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2156138Z       |        ^~~~~~~~
2025-08-14T21:34:45.2156746Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2157736Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2158622Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2159432Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2160178Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2161010Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2162060Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2163192Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2164368Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2165481Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2166479Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2167415Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2168243Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2168792Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2169633Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2170372Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2170709Z       |                     ^~~~
2025-08-14T21:34:45.2171277Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2172126Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2172963Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2173748Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2174519Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2175354Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2176292Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2177176Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2178058Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2178992Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2179933Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2180775Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2181324Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2182316Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2183874Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2185565Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2187319Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2189183Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2191240Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2197507Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2207859Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2214223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2215157Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2215538Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2221790Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2228241Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2229511Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2229931Z       |        ^~~~~~~~
2025-08-14T21:34:45.2230543Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2231536Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2232492Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2233344Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2234144Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2234975Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2236022Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2237199Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2238336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2239449Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2240453Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2241397Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2242223Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2242776Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2243610Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2244334Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2244674Z       |                     ^~~~
2025-08-14T21:34:45.2245248Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2246099Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2246897Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2247679Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2248431Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2249303Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2250206Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2251095Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2251978Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2252911Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2253856Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2254698Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2255254Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2256238Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2257813Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2259550Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2261302Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2263208Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2265222Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2271011Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2280918Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2286537Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2287460Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2287838Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2293694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2299920Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2301189Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2301640Z       |        ^~~~~~~~
2025-08-14T21:34:45.2302265Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2303257Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2304124Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2304935Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2305698Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2306529Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2307568Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2308744Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2310072Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2311241Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2312331Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2313263Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2314101Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2314655Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2315479Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2316213Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2316559Z       |                     ^~~~
2025-08-14T21:34:45.2317134Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2317970Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2318836Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2319620Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2320404Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2321227Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2322141Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2323030Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2323919Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2324835Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2325786Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2326626Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2327177Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2328150Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2329700Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2331403Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2333150Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2335079Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2337132Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2342898Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2352741Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2358387Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2359308Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2359676Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2365574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2371755Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2373024Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2373442Z       |        ^~~~~~~~
2025-08-14T21:34:45.2374063Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2375046Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2375929Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2376743Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2377591Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2378413Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2379499Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2380632Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2381768Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2382864Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2383870Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2384801Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2385635Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2386177Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2387002Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2387734Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2388078Z       |                     ^~~~
2025-08-14T21:34:45.2388643Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2389495Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2390308Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2391096Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2391960Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2392801Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2393717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2394621Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2395512Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2396450Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2397407Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2398249Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2398790Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2399782Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2401340Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2403081Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2404835Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2406727Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2408741Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2414712Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2424566Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2430169Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2431089Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2431467Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2437403Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2443674Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2444953Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2445371Z       |        ^~~~~~~~
2025-08-14T21:34:45.2445981Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2446975Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2447857Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2448674Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2449419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2450253Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2451342Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2452476Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2453652Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2454764Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2455766Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2473410Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2474480Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2475047Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2476008Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2476847Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2477186Z       |                     ^~~~
2025-08-14T21:34:45.2477774Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2478739Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2479538Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2480328Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2481123Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2481958Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2482862Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2483752Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2484640Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2485573Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2486514Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2487529Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2488081Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2489121Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2490691Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2492392Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2494193Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2496067Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2498125Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2504240Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2514882Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2520880Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2521813Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2522197Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2528465Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2534914Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2536195Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2536600Z       |        ^~~~~~~~
2025-08-14T21:34:45.2537237Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2538235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2539161Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2539962Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2540758Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2541595Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2542646Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2543767Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2544907Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2546016Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2547019Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2547959Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2548786Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2549335Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2550164Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2550891Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2551241Z       |                     ^~~~
2025-08-14T21:34:45.2551895Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2552749Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2553588Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2554378Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2555117Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2555980Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2556886Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2557772Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2558655Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2559593Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2560534Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2561374Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2561931Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2562921Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2564488Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2566233Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2567977Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2569844Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2571856Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2577625Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2587448Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2593130Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2594059Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2594486Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2600353Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2606558Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2607815Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2608232Z       |        ^~~~~~~~
2025-08-14T21:34:45.2608864Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2610198Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2611072Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2611886Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2612729Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2613569Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2614612Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2615794Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2616940Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2618058Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2619052Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2619988Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2620833Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2621388Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2622227Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2623012Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2623363Z       |                     ^~~~
2025-08-14T21:34:45.2623937Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2624777Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2625635Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2626424Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2627166Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2627992Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2628915Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2629800Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2630685Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2631682Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2632636Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2633480Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2634032Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2635021Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2636575Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2638323Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2640073Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2641970Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2643995Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2649776Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2659610Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2665206Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2666117Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2666504Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2672477Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2678668Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2679941Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2680357Z       |        ^~~~~~~~
2025-08-14T21:34:45.2680984Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2682005Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2682889Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2683703Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2684514Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2685335Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2686384Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2687518Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2688661Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2689758Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2690765Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2691704Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2692547Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2693089Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2693911Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2694653Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2695001Z       |                     ^~~~
2025-08-14T21:34:45.2695560Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2696413Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2697257Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2698033Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2698804Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2699642Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2700563Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2701436Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2702320Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2703255Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2704211Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2705039Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2705619Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2706605Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2708157Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2710094Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2711922Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2713792Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2715806Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2721666Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2731426Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2737023Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2737993Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2738383Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2744246Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2750455Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2751797Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2752202Z       |        ^~~~~~~~
2025-08-14T21:34:45.2752828Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2753834Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2754717Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2755509Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2756309Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2757141Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2758218Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2759336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2760470Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2761580Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2762583Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2763503Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2764336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2764884Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2765737Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2766458Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2766798Z       |                     ^~~~
2025-08-14T21:34:45.2767367Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2768235Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2769044Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2769823Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2770563Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2771382Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2772306Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2773191Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2774074Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2774991Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2775941Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2776777Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2777328Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2778296Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2779844Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2781577Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2783358Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2785227Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2787233Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2793077Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2802894Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2808489Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2809593Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2809964Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2815927Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2822118Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2823375Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2823791Z       |        ^~~~~~~~
2025-08-14T21:34:45.2824408Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2825460Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2826328Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2827186Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2827942Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2828764Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2829814Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2830944Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2832163Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2833270Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2834260Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2835193Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2836036Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2836585Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2837400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2838133Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2838477Z       |                     ^~~~
2025-08-14T21:34:45.2839033Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2839926Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2840739Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2841526Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2842282Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2843122Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2844043Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2844926Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2845799Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2846730Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2847682Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2848523Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2849099Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2850080Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2851624Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2853371Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2855121Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2856989Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2858992Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2865140Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2875590Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2881486Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2882392Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2882777Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2889018Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2895457Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2896740Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2897154Z       |        ^~~~~~~~
2025-08-14T21:34:45.2897782Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2898764Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2899697Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2900508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2901314Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2902133Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2903192Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2904329Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2905475Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2906572Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2907574Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2908508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2909616Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2910157Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2911002Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2911931Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2912284Z       |                     ^~~~
2025-08-14T21:34:45.2912846Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2913696Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2914509Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2915300Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2916028Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2916859Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2917778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2918662Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2919527Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2920458Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2921416Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2922256Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2922791Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2923875Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.2925438Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.2927199Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.2928959Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.2930808Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.2932830Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.2939060Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.2949639Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.2955725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.2956640Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.2957022Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.2963480Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.2970262Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.2971584Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.2972002Z       |        ^~~~~~~~
2025-08-14T21:34:45.2972623Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.2973603Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.2974486Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.2975303Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.2976057Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.2976874Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.2977927Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.2979055Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.2980312Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.2981412Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.2982415Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.2983352Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.2984246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2984784Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2985628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.2986365Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.2986710Z       |                     ^~~~
2025-08-14T21:34:45.2987305Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.2988165Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.2988972Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.2989752Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.2990586Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.2991418Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.2992407Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.2993295Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.2994218Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.2995148Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.2996098Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.2996976Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.2997515Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.2998516Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3000077Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3001791Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3003549Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3005422Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3007424Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3014042Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3024604Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3030637Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3031629Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3032019Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3038307Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3044874Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3046150Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3046568Z       |        ^~~~~~~~
2025-08-14T21:34:45.3047223Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3048225Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3049114Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3049929Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3050683Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3051519Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3052577Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3053711Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3054871Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3055978Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3057023Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3057955Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3058793Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3059330Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3060158Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3060894Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3061228Z       |                     ^~~~
2025-08-14T21:34:45.3061798Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3062655Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3063460Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3064228Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3064968Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3065803Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3066716Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3067587Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3068507Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3069438Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3070391Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3071246Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3071878Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3072872Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3074418Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3076114Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3077865Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3079724Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3081772Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3088031Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3098591Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3104530Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3105450Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3105830Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3112423Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3119170Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3120455Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3120871Z       |        ^~~~~~~~
2025-08-14T21:34:45.3121478Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3122479Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3123363Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3124170Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3124919Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3125750Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3126801Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3127932Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3129107Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3130221Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3131264Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3132204Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3133030Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3133579Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3134399Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3135140Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3135471Z       |                     ^~~~
2025-08-14T21:34:45.3136040Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3136887Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3137696Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3138504Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3139242Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3140075Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3141025Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3141896Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3142778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3143709Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3144668Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3145493Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3146040Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3147026Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3148572Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3150259Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3152093Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3154007Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3156020Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3162285Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3172830Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3178809Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3179730Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3180112Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3186462Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3193066Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3194352Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3194769Z       |        ^~~~~~~~
2025-08-14T21:34:45.3195381Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3196387Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3197276Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3198127Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3198876Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3199709Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3200793Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3201920Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3203046Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3204154Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3205155Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3206088Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3206921Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3207470Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3208288Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3209214Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3209561Z       |                     ^~~~
2025-08-14T21:34:45.3210136Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3210984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3211789Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3212646Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3213386Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3214216Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3215169Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3216049Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3216934Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3217869Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3218822Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3219649Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3220197Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3221198Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3222820Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3224510Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3226306Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3228170Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3230174Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3236469Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3247075Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3253020Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3253967Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3254344Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3260628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3267170Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3268443Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3268858Z       |        ^~~~~~~~
2025-08-14T21:34:45.3269474Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3270468Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3271350Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3272272Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3273017Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3273847Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3274924Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3276061Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3277185Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3278294Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3279295Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3280225Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3281053Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3281644Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3282468Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3283201Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3283530Z       |                     ^~~~
2025-08-14T21:34:45.3284100Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3284987Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3285795Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3286569Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3287312Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3288147Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3289070Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3289945Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3290831Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3291761Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3292712Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3293534Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3294084Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3295065Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3296645Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3298338Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3300118Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3302001Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3304011Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3310407Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3321132Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3327077Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3328003Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3328392Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3334780Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3341322Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3342631Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3343054Z       |        ^~~~~~~~
2025-08-14T21:34:45.3343667Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3344696Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3345584Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3346403Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3347152Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3347986Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3349033Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3350171Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3351298Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3352484Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3353483Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3354419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3355242Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3355790Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3356659Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3357395Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3357725Z       |                     ^~~~
2025-08-14T21:34:45.3358297Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3359182Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3359984Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3360768Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3361508Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3362350Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3363256Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3364148Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3365032Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3365992Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3366942Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3367765Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3368343Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3369325Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3370872Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3372565Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3374322Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3376192Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3378205Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3384474Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3395069Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3401095Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3402017Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3402398Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3408683Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3415557Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3416840Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3417256Z       |        ^~~~~~~~
2025-08-14T21:34:45.3417866Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3418905Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3419789Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3420599Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3421341Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3422175Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3423222Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3424352Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3425474Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3426637Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3427634Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3428607Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3429431Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3429976Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3430800Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3431607Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3431949Z       |                     ^~~~
2025-08-14T21:34:45.3432521Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3433369Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3434165Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3434958Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3435699Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3436531Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3437432Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3438314Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3439201Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3440128Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3441138Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3441983Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3442530Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3443553Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3445112Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3446804Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3448563Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3450433Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3452479Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3458690Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3469277Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3475349Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3476281Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3476666Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3483091Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3489700Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3490978Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3491402Z       |        ^~~~~~~~
2025-08-14T21:34:45.3492134Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3493144Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3494026Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3494851Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3495597Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3496424Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3497475Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3498606Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3499728Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3500884Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3501880Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3502810Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3503682Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3504235Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3505071Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3505805Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3506139Z       |                     ^~~~
2025-08-14T21:34:45.3506719Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3507568Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3508364Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3509321Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3510064Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3510985Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3511986Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3512930Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3513813Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3514745Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3515690Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3516533Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3517081Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3518082Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3519637Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3521330Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3523086Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3524956Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3527030Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3532982Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3542746Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3548608Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3549535Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3549916Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3555898Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3562084Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3563441Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3563850Z       |        ^~~~~~~~
2025-08-14T21:34:45.3564474Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3565472Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3566347Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3567161Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3567918Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3568747Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3569786Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3570947Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3572083Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3573229Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3574226Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3575150Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3575985Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3576539Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3577364Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3578102Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3578531Z       |                     ^~~~
2025-08-14T21:34:45.3579108Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3579950Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3580302Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3580621Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3580933Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3581343Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3581723Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3582151Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3582527Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3582965Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3583389Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3583705Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3583830Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3584592Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3585464Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3586384Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3587308Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3588388Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3589507Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3594856Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3600795Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3601643Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3601828Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3601960Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3608026Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3609490Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3609699Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3609807Z       |        ^~~~~~~~
2025-08-14T21:34:45.3610347Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3610776Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3611124Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3611469Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3611778Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3612192Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3612722Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3613220Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3613736Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3614259Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3614716Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3615131Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3615446Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3615633Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3616248Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3616386Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3616481Z       |                     ^~~~
2025-08-14T21:34:45.3616883Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3617224Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3617580Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3617897Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3618193Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3618624Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3619004Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3619396Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3619771Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3620202Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3620615Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3620927Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3621082Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3621838Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3622689Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3623623Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3624529Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3625581Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3626701Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3632062Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3638035Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3638856Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3639011Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3639126Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3645222Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3646512Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3646745Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3646844Z       |        ^~~~~~~~
2025-08-14T21:34:45.3647309Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3647720Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3648084Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3648423Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3648730Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3649148Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3649662Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3650174Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3650696Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3651174Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3651580Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3652008Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3652336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3652450Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3653055Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3653194Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3653286Z       |                     ^~~~
2025-08-14T21:34:45.3653681Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3654091Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3654482Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3654809Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3655106Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3655563Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3655968Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3656343Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3656729Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3657184Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3657593Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3657903Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3658018Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3658794Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3659650Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3660584Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3661490Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3662542Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3663614Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3669094Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3675132Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3676009Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3676182Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3676295Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3682519Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3683837Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3684047Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3684136Z       |        ^~~~~~~~
2025-08-14T21:34:45.3684609Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3685022Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3685387Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3685723Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3686012Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3686439Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3686988Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3687493Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3688011Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3688505Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3688922Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3689322Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3689649Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3689762Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3690354Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3690501Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3690595Z       |                     ^~~~
2025-08-14T21:34:45.3690994Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3691337Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3691675Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3692006Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3692305Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3692725Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3693103Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3693515Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3693903Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3694355Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3694767Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3695078Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3695189Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3696039Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3696909Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3697842Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3698745Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3699834Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3700946Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3705756Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3711498Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3712399Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3712567Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3712683Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3718320Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3719655Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3719876Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3719961Z       |        ^~~~~~~~
2025-08-14T21:34:45.3720427Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3720850Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3721202Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3721552Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3721842Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3722256Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3722786Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3723283Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3723868Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3724336Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3724745Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3725184Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3725500Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3725624Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3726214Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3726352Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3726460Z       |                     ^~~~
2025-08-14T21:34:45.3726844Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20,
2025-08-14T21:34:45.3727196Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3,
2025-08-14T21:34:45.3727538Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13,
2025-08-14T21:34:45.3741591Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3,
2025-08-14T21:34:45.3742131Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3,
2025-08-14T21:34:45.3742572Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3,
2025-08-14T21:34:45.3743003Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2,
2025-08-14T21:34:45.3743387Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6,
2025-08-14T21:34:45.3743777Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3,
2025-08-14T21:34:45.3744213Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3,
2025-08-14T21:34:45.3744631Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
2025-08-14T21:34:45.3744942Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3745056Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3745937Z In member function ‘void c10::SmallVectorTemplateCommon<T, <template-parameter-1-2> >::grow_pod(size_t, size_t) [with T = char*; <template-parameter-1-2> = void]’,
2025-08-14T21:34:45.3746802Z     inlined from ‘void c10::SmallVectorTemplateBase<T, true>::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19,
2025-08-14T21:34:45.3747744Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17,
2025-08-14T21:34:45.3748658Z     inlined from ‘void c10::SmallVectorImpl<T>::reserve(c10::SmallVectorImpl<T>::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8,
2025-08-14T21:34:45.3749707Z     inlined from ‘void c10::SmallVectorImpl<T>::append(in_iter, in_iter) [with in_iter = char**; <template-parameter-2-2> = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18,
2025-08-14T21:34:45.3750821Z     inlined from ‘c10::SmallVector<T, N>::SmallVector(ItTy, ItTy) [with ItTy = char**; <template-parameter-2-2> = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17,
2025-08-14T21:34:45.3756229Z     inlined from ‘at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21,
2025-08-14T21:34:45.3762194Z     inlined from ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52:
2025-08-14T21:34:45.3763037Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized]
2025-08-14T21:34:45.3763211Z   139 |     Base::grow_pod(getFirstEl(), MinSize, TSize);
2025-08-14T21:34:45.3763328Z       |     ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2025-08-14T21:34:45.3769458Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref<Ret(Params ...)>::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d<at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)> >(const at::native::CPU_CAPABILITY::cpu_serial_kernel<at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()> >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel<TestCPUGenerator*>(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::<lambda()>::<lambda()>::<lambda()>&&, const at::Range&)::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)>; Ret = void; Params = {char**, const long int*, long int, long int}]’:
2025-08-14T21:34:45.3770735Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase<Size_T>::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here
2025-08-14T21:34:45.3770945Z    73 |   void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize);
2025-08-14T21:34:45.3771037Z       |        ^~~~~~~~
2025-08-14T21:34:45.3771519Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12,
2025-08-14T21:34:45.3771930Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15,
2025-08-14T21:34:45.3772293Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37,
2025-08-14T21:34:45.3772665Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13,
2025-08-14T21:34:45.3772956Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18,
2025-08-14T21:34:45.3773385Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
2025-08-14T21:34:45.3773927Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
2025-08-14T21:34:45.3774432Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
2025-08-14T21:34:45.3774953Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4,
2025-08-14T21:34:45.3775419Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
2025-08-14T21:34:45.3775844Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
2025-08-14T21:34:45.3776242Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9,
2025-08-14T21:34:45.3776571Z                  from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5,
2025-08-14T21:34:45.3776687Z                  from rng_extension.cpp:1:
2025-08-14T21:34:45.3777277Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here
2025-08-14T21:34:45.3777429Z   413 |           PtrVector data(base, base + ntensor);
2025-08-14T21:34:45.3777524Z       |                     ^~~~
2025-08-14T21:34:45.3780659Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:45.8710344Z running install_lib
2025-08-14T21:34:45.8801130Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:45.8877677Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:45.8956297Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:45.9041378Z running install_egg_info
2025-08-14T21:34:45.9244331Z running egg_info
2025-08-14T21:34:45.9323958Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-08-14T21:34:45.9326895Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-08-14T21:34:45.9328484Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-08-14T21:34:45.9330530Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-08-14T21:34:45.9414365Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:45.9422739Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:45.9424310Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it)
2025-08-14T21:34:45.9425791Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info
2025-08-14T21:34:45.9431840Z running install_scripts
2025-08-14T21:34:49.0186420Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:49.0187970Z   import pkg_resources
2025-08-14T21:34:49.0459124Z 
2025-08-14T21:34:49.0459681Z Running tests...
2025-08-14T21:34:49.0460064Z ----------------------------------------------------------------------
2025-08-14T21:34:49.0577705Z .
2025-08-14T21:34:49.0578068Z ----------------------------------------------------------------------
2025-08-14T21:34:49.0578464Z Ran 1 test in 0.012s
2025-08-14T21:34:49.0578621Z 
2025-08-14T21:34:49.0578718Z OK
2025-08-14T21:34:49.0578827Z 
2025-08-14T21:34:49.0578933Z Generating XML reports...
2025-08-14T21:34:49.8049913Z Running test_cpp_extensions_aot_ninja 1/1 ... [2025-08-14 21:34:49.804619]
2025-08-14T21:34:52.2244002Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:34:52.2245545Z   import pkg_resources
2025-08-14T21:34:52.2956756Z running install
2025-08-14T21:34:52.2958838Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:52.2959648Z !!
2025-08-14T21:34:52.2959759Z 
2025-08-14T21:34:52.2959902Z         ********************************************************************************
2025-08-14T21:34:52.2960296Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:52.2960689Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:52.2961069Z         standards-based tools.
2025-08-14T21:34:52.2961255Z 
2025-08-14T21:34:52.2961719Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:52.2962194Z         or your builds will no longer be supported.
2025-08-14T21:34:52.2962451Z 
2025-08-14T21:34:52.2962751Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:52.2963349Z         ********************************************************************************
2025-08-14T21:34:52.2963590Z 
2025-08-14T21:34:52.2963694Z !!
2025-08-14T21:34:52.2963903Z   self.initialize_options()
2025-08-14T21:34:52.3102244Z running build
2025-08-14T21:34:52.3102528Z running build_py
2025-08-14T21:34:52.3195221Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:52.3197482Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension
2025-08-14T21:34:52.3201009Z running build_ext
2025-08-14T21:34:52.3567631Z building 'torch_test_cpp_extension.cpp' extension
2025-08-14T21:34:52.3568953Z creating /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313
2025-08-14T21:34:53.1720241Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-08-14T21:34:53.1832541Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:53.7817138Z building 'torch_test_cpp_extension.maia' extension
2025-08-14T21:34:54.5239294Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/maia_extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-08-14T21:34:54.5296032Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:55.0609660Z building 'torch_test_cpp_extension.rng' extension
2025-08-14T21:34:55.9686226Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/rng_extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-08-14T21:34:55.9740229Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so
2025-08-14T21:34:56.5231128Z running install_lib
2025-08-14T21:34:56.5325573Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:56.5370209Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:56.5416609Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension
2025-08-14T21:34:56.5464622Z running install_egg_info
2025-08-14T21:34:56.5661456Z running egg_info
2025-08-14T21:34:56.5742513Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-08-14T21:34:56.5745760Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-08-14T21:34:56.5747660Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-08-14T21:34:56.5749922Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-08-14T21:34:56.5835355Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:56.5844393Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-08-14T21:34:56.5845647Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it)
2025-08-14T21:34:56.5847545Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info
2025-08-14T21:34:56.5853873Z running install_scripts
2025-08-14T21:34:58.7270135Z running install
2025-08-14T21:34:58.7271074Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-08-14T21:34:58.7271930Z !!
2025-08-14T21:34:58.7272059Z 
2025-08-14T21:34:58.7272182Z         ********************************************************************************
2025-08-14T21:34:58.7272594Z         Please avoid running ``setup.py`` directly.
2025-08-14T21:34:58.7272996Z         Instead, use pypa/build, pypa/installer or other
2025-08-14T21:34:58.7273374Z         standards-based tools.
2025-08-14T21:34:58.7273573Z 
2025-08-14T21:34:58.7273801Z         By 2025-Oct-31, you need to update your project and remove deprecated calls
2025-08-14T21:34:58.7274287Z         or your builds will no longer be supported.
2025-08-14T21:34:58.7274531Z 
2025-08-14T21:34:58.7274844Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-08-14T21:34:58.7275607Z         ********************************************************************************
2025-08-14T21:34:58.7275861Z 
2025-08-14T21:34:58.7275942Z !!
2025-08-14T21:34:58.7276162Z   self.initialize_options()
2025-08-14T21:34:58.7405437Z running build
2025-08-14T21:34:58.7405744Z running build_ext
2025-08-14T21:34:58.7735740Z building 'no_python_abi_suffix_test' extension
2025-08-14T21:34:58.8322109Z ninja: no work to do.
2025-08-14T21:34:58.8366447Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so
2025-08-14T21:34:58.9466065Z running install_lib
2025-08-14T21:34:58.9561527Z copying build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages
2025-08-14T21:34:58.9566781Z running install_egg_info
2025-08-14T21:34:58.9764557Z running egg_info
2025-08-14T21:34:58.9841871Z writing no_python_abi_suffix_test.egg-info/PKG-INFO
2025-08-14T21:34:58.9846150Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt
2025-08-14T21:34:58.9858860Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt
2025-08-14T21:34:58.9950089Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-08-14T21:34:58.9958015Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-08-14T21:34:58.9969386Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info' (and everything under it)
2025-08-14T21:34:58.9970800Z Copying no_python_abi_suffix_test.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info
2025-08-14T21:34:58.9976091Z running install_scripts
2025-08-14T21:34:59.4324423Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:34:59.4327523Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_aot_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:34:59.432499]
2025-08-14T21:35:02.8416338Z 
2025-08-14T21:35:02.8418085Z test_cpp_extensions_aot_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_ninja_1.1_e4a7b540c1845995_.log
2025-08-14T21:35:02.8430930Z Running 21 items in this shard: test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_ninja.py::TestTorchLibrary::test_torch_library
2025-08-14T21:35:02.8439095Z 
2025-08-14T21:35:02.8439370Z Running inductor/test_cudagraph_trees 1/1 ... [2025-08-14 21:35:02.842145]
2025-08-14T21:35:02.8439846Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:02.8440992Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cudagraph_trees.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:02.842574]
2025-08-14T21:35:09.5415790Z 
2025-08-14T21:35:09.5416897Z inductor/test_cudagraph_trees 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_1.1_fbfa8366089c822c_.log
2025-08-14T21:35:09.5417752Z 
2025-08-14T21:35:09.5419607Z Running dynamo/test_repros 1/1 ... [2025-08-14 21:35:09.541801]
2025-08-14T21:35:09.5420097Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:09.5423668Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_repros.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:09.542141]
2025-08-14T21:35:12.9442700Z 
2025-08-14T21:35:12.9443649Z dynamo/test_repros 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_repros_1.1_7a48e82b1506e1e5_.log
2025-08-14T21:35:12.9444325Z 
2025-08-14T21:35:12.9446484Z Running inductor/test_compiled_optimizers 1/1 ... [2025-08-14 21:35:12.944481]
2025-08-14T21:35:12.9447065Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:12.9451191Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compiled_optimizers.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:12.944814]
2025-08-14T21:35:20.9716758Z 
2025-08-14T21:35:20.9718085Z inductor/test_compiled_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_optimizers_1.1_96e4c1c4ceacfdef_.log
2025-08-14T21:35:20.9718910Z 
2025-08-14T21:35:20.9720394Z Running dynamo/test_logging 1/1 ... [2025-08-14 21:35:20.971875]
2025-08-14T21:35:20.9720828Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:20.9723970Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:20.972200]
2025-08-14T21:35:27.5455592Z 
2025-08-14T21:35:27.5456548Z dynamo/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_logging_1.1_2db71a699ce96f86_.log
2025-08-14T21:35:27.5457215Z 
2025-08-14T21:35:27.5459452Z Running inductor/test_triton_kernels 1/1 ... [2025-08-14 21:35:27.545777]
2025-08-14T21:35:27.5459907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:27.5463558Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_triton_kernels.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:27.546147]
2025-08-14T21:35:34.2071377Z 
2025-08-14T21:35:34.2073013Z inductor/test_triton_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_kernels_1.1_d91150e3ea2cbe59_.log
2025-08-14T21:35:34.2074665Z 
2025-08-14T21:35:34.2077314Z Running inductor/test_torchbind 1/1 ... [2025-08-14 21:35:34.207512]
2025-08-14T21:35:34.2078031Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:34.2082419Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchbind.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:34.207920]
2025-08-14T21:35:40.8474733Z 
2025-08-14T21:35:40.8476357Z inductor/test_torchbind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchbind_1.1_a927fa6251817c8a_.log
2025-08-14T21:35:40.8477677Z 
2025-08-14T21:35:40.8480275Z Running inductor/test_aot_inductor_package 1/1 ... [2025-08-14 21:35:40.847801]
2025-08-14T21:35:40.8481080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:40.8485325Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:40.848214]
2025-08-14T21:35:47.4590299Z 
2025-08-14T21:35:47.4591241Z inductor/test_aot_inductor_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_package_1.1_4dfa7fd01aef7d5c_.log
2025-08-14T21:35:47.4592139Z 
2025-08-14T21:35:47.4593518Z Running dynamo/test_utils 1/1 ... [2025-08-14 21:35:47.459204]
2025-08-14T21:35:47.4594001Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:47.4597400Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:47.459524]
2025-08-14T21:35:50.4815853Z 
2025-08-14T21:35:50.4818751Z dynamo/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_utils_1.1_05849379c2ca31eb_.log
2025-08-14T21:35:50.4819674Z 
2025-08-14T21:35:50.4820224Z Running dynamo/test_error_messages 1/1 ... [2025-08-14 21:35:50.481832]
2025-08-14T21:35:50.4820671Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:50.4824278Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_error_messages.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:50.482193]
2025-08-14T21:35:53.7553906Z 
2025-08-14T21:35:53.7555212Z dynamo/test_error_messages 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_error_messages_1.1_e42c04986dc5d969_.log
2025-08-14T21:35:53.7555954Z 
2025-08-14T21:35:53.7557772Z Running dynamo/test_exceptions 1/1 ... [2025-08-14 21:35:53.755600]
2025-08-14T21:35:53.7558251Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:53.7561547Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_exceptions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:53.755939]
2025-08-14T21:35:57.0336435Z 
2025-08-14T21:35:57.0337523Z dynamo/test_exceptions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_exceptions_1.1_61e3a1cf6462ef3d_.log
2025-08-14T21:35:57.0338511Z 
2025-08-14T21:35:57.0340330Z Running dynamo/test_structured_trace 1/1 ... [2025-08-14 21:35:57.033863]
2025-08-14T21:35:57.0340850Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:35:57.0344203Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_structured_trace.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:35:57.034195]
2025-08-14T21:36:03.6726523Z 
2025-08-14T21:36:03.6727618Z dynamo/test_structured_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_structured_trace_1.1_3d4531daf65769a3_.log
2025-08-14T21:36:03.6728429Z 
2025-08-14T21:36:03.6730623Z Running inductor/test_cudagraph_trees_expandable_segments 1/1 ... [2025-08-14 21:36:03.672882]
2025-08-14T21:36:03.6731269Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:03.6734557Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cudagraph_trees_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:03.673219]
2025-08-14T21:36:10.2296583Z 
2025-08-14T21:36:10.2297800Z inductor/test_cudagraph_trees_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_expandable_segments_1.1_e02cd6de4cd02b86_.log
2025-08-14T21:36:10.2298756Z 
2025-08-14T21:36:10.2300153Z Running test_ops 6/8 ... [2025-08-14 21:36:10.229870]
2025-08-14T21:36:10.2300617Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:10.2304164Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'serial', '--shard-id=6', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:10.230207]
2025-08-14T21:36:24.2638904Z 
2025-08-14T21:36:24.2639829Z test_ops 6/8 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_6.8_d0666180a8912013_.log
2025-08-14T21:36:24.2640772Z Running 0 items in this shard:
2025-08-14T21:36:24.2640980Z 
2025-08-14T21:36:24.2645081Z Running inductor/test_torchinductor 1/1 ... [2025-08-14 21:36:24.264273]
2025-08-14T21:36:24.2645580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:24.2650295Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:24.264702]
2025-08-14T21:36:31.4451094Z 
2025-08-14T21:36:31.4452469Z inductor/test_torchinductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_1.1_ea9c1db7d0c0ff0f_.log
2025-08-14T21:36:31.4453261Z 
2025-08-14T21:36:31.4455297Z Running inductor/test_torchinductor_codegen_dynamic_shapes 1/1 ... [2025-08-14 21:36:31.445331]
2025-08-14T21:36:31.4455873Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:31.4459143Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_codegen_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:31.445678]
2025-08-14T21:36:38.6592789Z 
2025-08-14T21:36:38.6593992Z inductor/test_torchinductor_codegen_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_dynamic_shapes_1.1_ebdd213138856b2c_.log
2025-08-14T21:36:38.6594958Z 
2025-08-14T21:36:38.6597206Z Running inductor/test_cpu_repro 1/1 ... [2025-08-14 21:36:38.659496]
2025-08-14T21:36:38.6597945Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:38.6600573Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_repro.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:38.659828]
2025-08-14T21:36:45.8325153Z 
2025-08-14T21:36:45.8326380Z inductor/test_cpu_repro 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_repro_1.1_476f11b2abaf758b_.log
2025-08-14T21:36:45.8327094Z 
2025-08-14T21:36:45.8329035Z Running inductor/test_kernel_benchmark 1/1 ... [2025-08-14 21:36:45.832713]
2025-08-14T21:36:45.8329526Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:45.8332636Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_kernel_benchmark.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:45.833040]
2025-08-14T21:36:52.4225403Z 
2025-08-14T21:36:52.4226409Z inductor/test_kernel_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_benchmark_1.1_bd7cc0bc22340ef2_.log
2025-08-14T21:36:52.4227182Z 
2025-08-14T21:36:52.4229288Z Running inductor/test_pattern_matcher 1/1 ... [2025-08-14 21:36:52.422746]
2025-08-14T21:36:52.4229794Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:52.4233019Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pattern_matcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:52.423075]
2025-08-14T21:36:59.1033059Z 
2025-08-14T21:36:59.1034097Z inductor/test_pattern_matcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pattern_matcher_1.1_63a29eedcd87f419_.log
2025-08-14T21:36:59.1034876Z 
2025-08-14T21:36:59.1036910Z Running inductor/test_perf 1/1 ... [2025-08-14 21:36:59.103521]
2025-08-14T21:36:59.1037342Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:36:59.1041263Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_perf.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:36:59.103870]
2025-08-14T21:37:05.7704005Z 
2025-08-14T21:37:05.7704985Z inductor/test_perf 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_perf_1.1_13766a005849c258_.log
2025-08-14T21:37:05.7705639Z 
2025-08-14T21:37:05.7707757Z Running dynamo/test_modules 1/1 ... [2025-08-14 21:37:05.770593]
2025-08-14T21:37:05.7708445Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:05.7712154Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:05.770977]
2025-08-14T21:37:12.3880267Z 
2025-08-14T21:37:12.3881636Z dynamo/test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_modules_1.1_17f20816ce3d6377_.log
2025-08-14T21:37:12.3882890Z 
2025-08-14T21:37:12.3886477Z Running inductor/test_coordinate_descent_tuner 1/1 ... [2025-08-14 21:37:12.388368]
2025-08-14T21:37:12.3887273Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:12.3890039Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_coordinate_descent_tuner.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:12.388760]
2025-08-14T21:37:19.0089623Z 
2025-08-14T21:37:19.0090694Z inductor/test_coordinate_descent_tuner 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_coordinate_descent_tuner_1.1_b40efabea8bdc1cb_.log
2025-08-14T21:37:19.0091537Z 
2025-08-14T21:37:19.0093920Z Running inductor/test_select_algorithm 1/1 ... [2025-08-14 21:37:19.009221]
2025-08-14T21:37:19.0094401Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:19.0097976Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_select_algorithm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:19.009565]
2025-08-14T21:37:25.5473356Z 
2025-08-14T21:37:25.5474470Z inductor/test_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_select_algorithm_1.1_6a28c3134483a149_.log
2025-08-14T21:37:25.5475311Z 
2025-08-14T21:37:25.5477063Z Running inductor/test_compiled_autograd 1/1 ... [2025-08-14 21:37:25.547519]
2025-08-14T21:37:25.5477538Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:25.5480968Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compiled_autograd.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:25.547866]
2025-08-14T21:37:33.6307881Z 
2025-08-14T21:37:33.6309001Z inductor/test_compiled_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_autograd_1.1_0eb1d1eb211ba105_.log
2025-08-14T21:37:33.6310020Z 
2025-08-14T21:37:33.6312528Z Running inductor/test_group_batch_fusion 1/1 ... [2025-08-14 21:37:33.631008]
2025-08-14T21:37:33.6314852Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:33.6316113Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_group_batch_fusion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:33.631352]
2025-08-14T21:37:40.3879837Z 
2025-08-14T21:37:40.3880841Z inductor/test_group_batch_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_group_batch_fusion_1.1_c0ccce68cb2bafa2_.log
2025-08-14T21:37:40.3881674Z 
2025-08-14T21:37:40.3884047Z Running inductor/test_split_cat_fx_passes 1/1 ... [2025-08-14 21:37:40.388217]
2025-08-14T21:37:40.3884532Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:40.3887793Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_split_cat_fx_passes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:40.388539]
2025-08-14T21:37:47.1491031Z 
2025-08-14T21:37:47.1492040Z inductor/test_split_cat_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_split_cat_fx_passes_1.1_47738cbc5cde4a76_.log
2025-08-14T21:37:47.1492891Z 
2025-08-14T21:37:47.1494383Z Running inductor/test_snode_runtime 1/1 ... [2025-08-14 21:37:47.149247]
2025-08-14T21:37:47.1494836Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:47.1497977Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_snode_runtime.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:47.149577]
2025-08-14T21:37:53.8906998Z 
2025-08-14T21:37:53.8907992Z inductor/test_snode_runtime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_snode_runtime_1.1_895623d8c43fc69b_.log
2025-08-14T21:37:53.8908732Z 
2025-08-14T21:37:53.8910786Z Running inductor/test_config 1/1 ... [2025-08-14 21:37:53.890923]
2025-08-14T21:37:53.8911290Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:37:53.8914821Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_config.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:37:53.891260]
2025-08-14T21:38:00.5004714Z 
2025-08-14T21:38:00.5005993Z inductor/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_config_1.1_e6d4961e0f25f65a_.log
2025-08-14T21:38:00.5006686Z 
2025-08-14T21:38:00.5008627Z Running dynamo/test_after_aot 1/1 ... [2025-08-14 21:38:00.500677]
2025-08-14T21:38:00.5009465Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:00.5012897Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:00.501036]
2025-08-14T21:38:03.8148164Z 
2025-08-14T21:38:03.8149391Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_459afe53ad0a0a96_.log
2025-08-14T21:38:03.8150075Z 
2025-08-14T21:38:03.8152140Z Running inductor/test_binary_folding 1/1 ... [2025-08-14 21:38:03.814985]
2025-08-14T21:38:03.8152634Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:03.8155207Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:03.815311]
2025-08-14T21:38:10.9033166Z 
2025-08-14T21:38:10.9034207Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_2445ee99d864b49a_.log
2025-08-14T21:38:10.9034965Z 
2025-08-14T21:38:10.9036909Z Running dynamo/test_cudagraphs 1/1 ... [2025-08-14 21:38:10.903521]
2025-08-14T21:38:10.9037359Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:10.9040882Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:10.903843]
2025-08-14T21:38:14.2078723Z 
2025-08-14T21:38:14.2079708Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_15dc0b05cba764ca_.log
2025-08-14T21:38:14.2080473Z 
2025-08-14T21:38:14.2082933Z Running dynamo/test_ctx_manager 1/1 ... [2025-08-14 21:38:14.208103]
2025-08-14T21:38:14.2083446Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:14.2086667Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_ctx_manager.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:14.208441]
2025-08-14T21:38:20.8715251Z 
2025-08-14T21:38:20.8716161Z dynamo/test_ctx_manager 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_ctx_manager_1.1_1cb3787e6f05a30a_.log
2025-08-14T21:38:20.8716898Z 
2025-08-14T21:38:20.8718981Z Running inductor/test_control_flow 1/1 ... [2025-08-14 21:38:20.871741]
2025-08-14T21:38:20.8719451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:20.8723107Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_control_flow.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:20.872075]
2025-08-14T21:38:27.4930858Z 
2025-08-14T21:38:27.4932242Z inductor/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_control_flow_1.1_b9310461b4dcd393_.log
2025-08-14T21:38:27.4933039Z 
2025-08-14T21:38:27.4936454Z Running inductor/test_padding 1/1 ... [2025-08-14 21:38:27.493446]
2025-08-14T21:38:27.4937126Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:27.4941388Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_padding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:27.493866]
2025-08-14T21:38:34.1588526Z 
2025-08-14T21:38:34.1589819Z inductor/test_padding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_padding_1.1_33d5396bea5775c2_.log
2025-08-14T21:38:34.1590507Z 
2025-08-14T21:38:34.1592632Z Running inductor/test_halide 1/1 ... [2025-08-14 21:38:34.159076]
2025-08-14T21:38:34.1593204Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:34.1596527Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_halide.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:34.159415]
2025-08-14T21:38:41.2523956Z 
2025-08-14T21:38:41.2525022Z inductor/test_halide 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_halide_1.1_1c3dfbd066711a3a_.log
2025-08-14T21:38:41.2525733Z 
2025-08-14T21:38:41.2528402Z Running inductor/test_aot_inductor_custom_ops 1/1 ... [2025-08-14 21:38:41.252667]
2025-08-14T21:38:41.2528974Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:41.2532011Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_custom_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:41.252989]
2025-08-14T21:38:48.3703908Z 
2025-08-14T21:38:48.3705270Z inductor/test_aot_inductor_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_custom_ops_1.1_9c0987a976c2d598_.log
2025-08-14T21:38:48.3706120Z 
2025-08-14T21:38:48.3707924Z Running inductor/test_flex_decoding 1/1 ... [2025-08-14 21:38:48.370587]
2025-08-14T21:38:48.3708483Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:48.3711737Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_decoding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:48.370893]
2025-08-14T21:38:51.4788960Z 
2025-08-14T21:38:51.4789926Z inductor/test_flex_decoding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_decoding_1.1_59b1d6351389bc22_.log
2025-08-14T21:38:51.4790672Z 
2025-08-14T21:38:51.4792627Z Running inductor/test_external_callables 1/1 ... [2025-08-14 21:38:51.479097]
2025-08-14T21:38:51.4793177Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:51.4796521Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_external_callables.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:51.479424]
2025-08-14T21:38:54.4925801Z 
2025-08-14T21:38:54.4927394Z inductor/test_external_callables 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_external_callables_1.1_37d08b56713dd4b9_.log
2025-08-14T21:38:54.4928894Z 
2025-08-14T21:38:54.4931252Z Running inductor/test_alignment 1/1 ... [2025-08-14 21:38:54.492943]
2025-08-14T21:38:54.4932209Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:38:54.4936699Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_alignment.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:38:54.493345]
2025-08-14T21:39:01.5477480Z 
2025-08-14T21:39:01.5478993Z inductor/test_alignment 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_alignment_1.1_b078e11d9ffec3e8_.log
2025-08-14T21:39:01.5480127Z 
2025-08-14T21:39:01.5482552Z Running inductor/test_subgraph_choice 1/1 ... [2025-08-14 21:39:01.548000]
2025-08-14T21:39:01.5483352Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:01.5487350Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:01.548411]
2025-08-14T21:39:08.2328354Z 
2025-08-14T21:39:08.2329340Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_e76921dadcef7734_.log
2025-08-14T21:39:08.2330123Z 
2025-08-14T21:39:08.2331993Z Running inductor/test_pad_mm 1/1 ... [2025-08-14 21:39:08.233044]
2025-08-14T21:39:08.2332435Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:08.2335859Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pad_mm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:08.233371]
2025-08-14T21:39:14.8203903Z 
2025-08-14T21:39:14.8205446Z inductor/test_pad_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pad_mm_1.1_a8ab672b83ae6da4_.log
2025-08-14T21:39:14.8206717Z 
2025-08-14T21:39:14.8209507Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-08-14 21:39:14.820736]
2025-08-14T21:39:14.8210259Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:14.8215046Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:14.821161]
2025-08-14T21:39:17.8496762Z 
2025-08-14T21:39:17.8497887Z dynamo/test_deque_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deque_reconstruct_1.1_bc2e3079b5b10eae_.log
2025-08-14T21:39:17.8498651Z 
2025-08-14T21:39:17.8500558Z Running inductor/test_cooperative_reductions 1/1 ... [2025-08-14 21:39:17.849850]
2025-08-14T21:39:17.8501070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:17.8504101Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cooperative_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:17.850182]
2025-08-14T21:39:24.4343546Z 
2025-08-14T21:39:24.4344618Z inductor/test_cooperative_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cooperative_reductions_1.1_5b31e7eee8e92c43_.log
2025-08-14T21:39:24.4345454Z 
2025-08-14T21:39:24.4347552Z Running inductor/test_inductor_annotations 1/1 ... [2025-08-14 21:39:24.434583]
2025-08-14T21:39:24.4348053Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:24.4351382Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_annotations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:24.434917]
2025-08-14T21:39:31.0447266Z 
2025-08-14T21:39:31.0448320Z inductor/test_inductor_annotations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_annotations_1.1_e13e94495c09db73_.log
2025-08-14T21:39:31.0449120Z 
2025-08-14T21:39:31.0451081Z Running inductor/test_inductor_utils 1/1 ... [2025-08-14 21:39:31.044925]
2025-08-14T21:39:31.0451555Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:31.0454220Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:31.045215]
2025-08-14T21:39:34.1232553Z 
2025-08-14T21:39:34.1233537Z inductor/test_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_utils_1.1_dc74bc56647cc893_.log
2025-08-14T21:39:34.1234306Z 
2025-08-14T21:39:34.1236179Z Running inductor/test_op_completeness 1/1 ... [2025-08-14 21:39:34.123450]
2025-08-14T21:39:34.1236651Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:34.1239767Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_op_completeness.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:34.123770]
2025-08-14T21:39:37.5323469Z 
2025-08-14T21:39:37.5324556Z inductor/test_op_completeness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_op_completeness_1.1_57384c3a6f8444b8_.log
2025-08-14T21:39:37.5325335Z 
2025-08-14T21:39:37.5327207Z Running inductor/test_fp8 1/1 ... [2025-08-14 21:39:37.532557]
2025-08-14T21:39:37.5327635Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:37.5331245Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fp8.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:37.532885]
2025-08-14T21:39:44.1587007Z 
2025-08-14T21:39:44.1587947Z inductor/test_fp8 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fp8_1.1_9dcdfccba95bc412_.log
2025-08-14T21:39:44.1588851Z 
2025-08-14T21:39:44.1591005Z Running inductor/test_debug_trace 1/1 ... [2025-08-14 21:39:44.158917]
2025-08-14T21:39:44.1591455Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:44.1594600Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_debug_trace.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:44.159244]
2025-08-14T21:39:51.2253286Z 
2025-08-14T21:39:51.2254325Z inductor/test_debug_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_debug_trace_1.1_b0e720d4d64aa556_.log
2025-08-14T21:39:51.2255117Z 
2025-08-14T21:39:51.2257759Z Running export/test_export_strict 1/1 ... [2025-08-14 21:39:51.225563]
2025-08-14T21:39:51.2258250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:51.2261164Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_strict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:51.225894]
2025-08-14T21:39:57.9784287Z 
2025-08-14T21:39:57.9785471Z export/test_export_strict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_strict_1.1_600dd87abf9cd238_.log
2025-08-14T21:39:57.9786190Z 
2025-08-14T21:39:57.9788511Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-08-14 21:39:57.978692]
2025-08-14T21:39:57.9789037Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:39:57.9792603Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:39:57.979042]
2025-08-14T21:40:04.6273428Z 
2025-08-14T21:40:04.6274564Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_c2ccefc25fdfc406_.log
2025-08-14T21:40:04.6275444Z 
2025-08-14T21:40:04.6277285Z Running inductor/test_combo_kernels 1/1 ... [2025-08-14 21:40:04.627556]
2025-08-14T21:40:04.6277757Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:04.6280793Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_combo_kernels.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:04.627871]
2025-08-14T21:40:11.7381490Z 
2025-08-14T21:40:11.7382970Z inductor/test_combo_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_combo_kernels_1.1_d00a6d0947172b8c_.log
2025-08-14T21:40:11.7384395Z 
2025-08-14T21:40:11.7387336Z Running dynamo/test_skip_guard_eval_unsafe 1/1 ... [2025-08-14 21:40:11.738525]
2025-08-14T21:40:11.7387857Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:11.7391188Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_guard_eval_unsafe.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:11.738883]
2025-08-14T21:40:15.0290335Z 
2025-08-14T21:40:15.0296287Z dynamo/test_skip_guard_eval_unsafe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_guard_eval_unsafe_1.1_84cd44a96960d4c5_.log
2025-08-14T21:40:15.0297568Z 
2025-08-14T21:40:15.0297956Z Running inductor/test_memory_planning 1/1 ... [2025-08-14 21:40:15.029316]
2025-08-14T21:40:15.0298757Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:15.0300839Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_memory_planning.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:15.029700]
2025-08-14T21:40:22.1317540Z 
2025-08-14T21:40:22.1318935Z inductor/test_memory_planning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_planning_1.1_91c883a575290bb6_.log
2025-08-14T21:40:22.1319777Z 
2025-08-14T21:40:22.1321060Z Running inductor/test_compile_worker 1/1 ... [2025-08-14 21:40:22.131934]
2025-08-14T21:40:22.1321580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:22.1324592Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_worker.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:22.132247]
2025-08-14T21:40:28.7641124Z 
2025-08-14T21:40:28.7642433Z inductor/test_compile_worker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_worker_1.1_f0bfd82a0977146b_.log
2025-08-14T21:40:28.7643317Z 
2025-08-14T21:40:28.7646121Z Running dynamo/test_frame_init 1/1 ... [2025-08-14 21:40:28.764370]
2025-08-14T21:40:28.7646849Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:28.7651125Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_frame_init.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:28.764789]
2025-08-14T21:40:31.7900233Z 
2025-08-14T21:40:31.7901153Z dynamo/test_frame_init 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_frame_init_1.1_c0baf39406d8b6f2_.log
2025-08-14T21:40:31.7902550Z 
2025-08-14T21:40:31.7904660Z Running dynamo/test_fx_passes_pre_grad 1/1 ... [2025-08-14 21:40:31.790278]
2025-08-14T21:40:31.7905197Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:31.7908760Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_fx_passes_pre_grad.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:31.790644]
2025-08-14T21:40:34.8297409Z 
2025-08-14T21:40:34.8298390Z dynamo/test_fx_passes_pre_grad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_passes_pre_grad_1.1_f1734b5b1cb788f7_.log
2025-08-14T21:40:34.8299150Z 
2025-08-14T21:40:34.8301581Z Running inductor/test_metrics 1/1 ... [2025-08-14 21:40:34.829990]
2025-08-14T21:40:34.8302078Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:34.8305982Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_metrics.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:34.830394]
2025-08-14T21:40:41.4731922Z 
2025-08-14T21:40:41.4732821Z inductor/test_metrics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_metrics_1.1_5037994bb6d5e2d4_.log
2025-08-14T21:40:41.4733500Z 
2025-08-14T21:40:41.4735568Z Running inductor/test_move_constructors_to_cuda 1/1 ... [2025-08-14 21:40:41.473392]
2025-08-14T21:40:41.4736160Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:41.4739486Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_move_constructors_to_cuda.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:41.473719]
2025-08-14T21:40:48.0416625Z 
2025-08-14T21:40:48.0418163Z inductor/test_move_constructors_to_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_move_constructors_to_cuda_1.1_deecc622311eeb68_.log
2025-08-14T21:40:48.0419085Z 
2025-08-14T21:40:48.0420414Z Running dynamo/test_inline_and_install 1/1 ... [2025-08-14 21:40:48.041851]
2025-08-14T21:40:48.0420876Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:48.0424815Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_inline_and_install.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:48.042204]
2025-08-14T21:40:51.3837840Z 
2025-08-14T21:40:51.3839008Z dynamo/test_inline_and_install 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_inline_and_install_1.1_41b400bf42892d42_.log
2025-08-14T21:40:51.3840322Z 
2025-08-14T21:40:51.3841895Z Running dynamo/test_skip_non_tensor 1/1 ... [2025-08-14 21:40:51.384007]
2025-08-14T21:40:51.3842341Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:51.3845242Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_non_tensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:51.384317]
2025-08-14T21:40:54.6231088Z 
2025-08-14T21:40:54.6232413Z dynamo/test_skip_non_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_non_tensor_1.1_116c370cadc74db1_.log
2025-08-14T21:40:54.6233371Z 
2025-08-14T21:40:54.6234926Z Running inductor/test_cutlass_evt 1/1 ... [2025-08-14 21:40:54.623304]
2025-08-14T21:40:54.6235585Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:40:54.6238820Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cutlass_evt.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:40:54.623634]
2025-08-14T21:41:01.2598782Z 
2025-08-14T21:41:01.2599880Z inductor/test_cutlass_evt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_evt_1.1_d4e0abb6f57d8117_.log
2025-08-14T21:41:01.2600607Z 
2025-08-14T21:41:01.2603349Z Running inductor/test_kernel_optimization 1/1 ... [2025-08-14 21:41:01.260103]
2025-08-14T21:41:01.2603924Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:01.2606678Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_kernel_optimization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:01.260445]
2025-08-14T21:41:07.9011897Z 
2025-08-14T21:41:07.9013154Z inductor/test_kernel_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_optimization_1.1_28eb359e467b5126_.log
2025-08-14T21:41:07.9014623Z 
2025-08-14T21:41:07.9016526Z Running export/test_export_with_inline_and_install 1/1 ... [2025-08-14 21:41:07.901446]
2025-08-14T21:41:07.9017164Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:07.9020371Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_with_inline_and_install.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:07.901783]
2025-08-14T21:41:14.5592252Z 
2025-08-14T21:41:14.5593438Z export/test_export_with_inline_and_install 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_with_inline_and_install_1.1_50d01fea7fad8f7c_.log
2025-08-14T21:41:14.5594408Z 
2025-08-14T21:41:14.5596099Z Running inductor/test_static_cuda_launcher 1/1 ... [2025-08-14 21:41:14.559435]
2025-08-14T21:41:14.5596664Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:14.5600294Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_static_cuda_launcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:14.559751]
2025-08-14T21:41:21.1692969Z 
2025-08-14T21:41:21.1694063Z inductor/test_static_cuda_launcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_static_cuda_launcher_1.1_1e79a4c0f74a9b06_.log
2025-08-14T21:41:21.1695094Z 
2025-08-14T21:41:21.1695326Z Running dynamo/test_pre_dispatch 1/1 ... [2025-08-14 21:41:21.169327]
2025-08-14T21:41:21.1695775Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:21.1699098Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_pre_dispatch.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:21.169657]
2025-08-14T21:41:24.2276391Z 
2025-08-14T21:41:24.2277383Z dynamo/test_pre_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_pre_dispatch_1.1_4cdb80dd6588219a_.log
2025-08-14T21:41:24.2278088Z 
2025-08-14T21:41:24.2280536Z Running dynamo/test_sdpa 1/1 ... [2025-08-14 21:41:24.227851]
2025-08-14T21:41:24.2281271Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:24.2283908Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sdpa.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:24.228161]
2025-08-14T21:41:27.5123178Z 
2025-08-14T21:41:27.5124330Z dynamo/test_sdpa 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sdpa_1.1_38474515d8fa57c4_.log
2025-08-14T21:41:27.5124978Z 
2025-08-14T21:41:27.5127059Z Running inductor/test_inplacing_pass 1/1 ... [2025-08-14 21:41:27.512517]
2025-08-14T21:41:27.5127735Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:27.5130868Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:27.512838]
2025-08-14T21:41:34.1570933Z 
2025-08-14T21:41:34.1571936Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_00d1cbd9589c4ca8_.log
2025-08-14T21:41:34.1572821Z 
2025-08-14T21:41:34.1573513Z Running dynamo/test_graph_region_tracker 1/1 ... [2025-08-14 21:41:34.157178]
2025-08-14T21:41:34.1574086Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:34.1577161Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_graph_region_tracker.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:34.157505]
2025-08-14T21:41:37.4219772Z 
2025-08-14T21:41:37.4220779Z dynamo/test_graph_region_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_graph_region_tracker_1.1_75226b8113688271_.log
2025-08-14T21:41:37.4221569Z 
2025-08-14T21:41:37.4223878Z Running inductor/test_fuzzer 1/1 ... [2025-08-14 21:41:37.422223]
2025-08-14T21:41:37.4224383Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:37.4228076Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fuzzer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:37.422581]
2025-08-14T21:41:44.0310489Z 
2025-08-14T21:41:44.0311421Z inductor/test_fuzzer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fuzzer_1.1_6c6670bbfb993a71_.log
2025-08-14T21:41:44.0312193Z 
2025-08-14T21:41:44.0314782Z Running dynamo/test_subgraphs 1/1 ... [2025-08-14 21:41:44.031304]
2025-08-14T21:41:44.0315481Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:44.0319200Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_subgraphs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:44.031674]
2025-08-14T21:41:47.3205617Z 
2025-08-14T21:41:47.3206775Z dynamo/test_subgraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_subgraphs_1.1_f685d7c5f006ffaa_.log
2025-08-14T21:41:47.3207569Z 
2025-08-14T21:41:47.3209840Z Running inductor/test_quantization 1/1 ... [2025-08-14 21:41:47.320791]
2025-08-14T21:41:47.3210380Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:47.3214003Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_quantization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:47.321183]
2025-08-14T21:41:53.9220800Z 
2025-08-14T21:41:53.9221859Z inductor/test_quantization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_quantization_1.1_e33478b6071a45de_.log
2025-08-14T21:41:53.9222675Z 
2025-08-14T21:41:53.9224726Z Running inductor/test_compile_subprocess 1/1 ... [2025-08-14 21:41:53.922297]
2025-08-14T21:41:53.9225286Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:41:53.9228602Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:41:53.922621]
2025-08-14T21:42:01.0285191Z 
2025-08-14T21:42:01.0286667Z inductor/test_compile_subprocess 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_1.1_bb9816ee131e3cf6_.log
2025-08-14T21:42:01.0287506Z 
2025-08-14T21:42:01.0289270Z Running dynamo/test_view 1/1 ... [2025-08-14 21:42:01.028710]
2025-08-14T21:42:01.0289887Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:01.0292885Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_view.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:01.029042]
2025-08-14T21:42:04.0729341Z 
2025-08-14T21:42:04.0730597Z dynamo/test_view 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_view_1.1_9993a6292daa235a_.log
2025-08-14T21:42:04.0731230Z 
2025-08-14T21:42:04.0732998Z Running dynamo/test_list 1/1 ... [2025-08-14 21:42:04.073125]
2025-08-14T21:42:04.0735885Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:04.0737288Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:04.073440]
2025-08-14T21:42:07.3891098Z 
2025-08-14T21:42:07.3892154Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_ec875e8c67999543_.log
2025-08-14T21:42:07.3892786Z 
2025-08-14T21:42:07.3894606Z Running inductor/test_loop_ordering 1/1 ... [2025-08-14 21:42:07.389278]
2025-08-14T21:42:07.3895269Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:07.3898648Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_loop_ordering.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:07.389598]
2025-08-14T21:42:14.0604561Z 
2025-08-14T21:42:14.0606088Z inductor/test_loop_ordering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_loop_ordering_1.1_648654f53599c935_.log
2025-08-14T21:42:14.0606891Z 
2025-08-14T21:42:14.0608554Z Running inductor/test_fxir_backend 1/1 ... [2025-08-14 21:42:14.060654]
2025-08-14T21:42:14.0609400Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:14.0612495Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fxir_backend.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:14.060999]
2025-08-14T21:42:20.6171807Z 
2025-08-14T21:42:20.6172921Z inductor/test_fxir_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fxir_backend_1.1_8735f1e8ed6f9a39_.log
2025-08-14T21:42:20.6173654Z 
2025-08-14T21:42:20.6175562Z Running dynamo/test_install_free_tensors 1/1 ... [2025-08-14 21:42:20.617386]
2025-08-14T21:42:20.6176057Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:20.6179458Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_install_free_tensors.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:20.617724]
2025-08-14T21:42:23.8396154Z 
2025-08-14T21:42:23.8397207Z dynamo/test_install_free_tensors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_install_free_tensors_1.1_eebec45188f92f6e_.log
2025-08-14T21:42:23.8398210Z 
2025-08-14T21:42:23.8400450Z Running dynamo/test_autograd_function 1/1 ... [2025-08-14 21:42:23.839825]
2025-08-14T21:42:23.8400931Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:23.8403885Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_autograd_function.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:23.840143]
2025-08-14T21:42:30.4587448Z 
2025-08-14T21:42:30.4588627Z dynamo/test_autograd_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_autograd_function_1.1_4353442d1b577934_.log
2025-08-14T21:42:30.4589447Z 
2025-08-14T21:42:30.4592221Z Running dynamo/test_config 1/1 ... [2025-08-14 21:42:30.458965]
2025-08-14T21:42:30.4592915Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:30.4596895Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_config.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:30.459370]
2025-08-14T21:42:33.7539035Z 
2025-08-14T21:42:33.7540347Z dynamo/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_config_1.1_8ca75a7964f8d001_.log
2025-08-14T21:42:33.7541575Z 
2025-08-14T21:42:33.7544780Z Running inductor/test_needs_exact_strides 1/1 ... [2025-08-14 21:42:33.754270]
2025-08-14T21:42:33.7545555Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:33.7550015Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_needs_exact_strides.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:33.754680]
2025-08-14T21:42:40.4453425Z 
2025-08-14T21:42:40.4454714Z inductor/test_needs_exact_strides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_needs_exact_strides_1.1_e269fe35cd43011e_.log
2025-08-14T21:42:40.4455624Z 
2025-08-14T21:42:40.4457598Z Running dynamo/test_compile 1/1 ... [2025-08-14 21:42:40.445565]
2025-08-14T21:42:40.4458036Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:40.4461310Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_compile.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:40.445902]
2025-08-14T21:42:43.6736069Z 
2025-08-14T21:42:43.6736995Z dynamo/test_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compile_1.1_7bff64d4404e111b_.log
2025-08-14T21:42:43.6737702Z 
2025-08-14T21:42:43.6740547Z Running inductor/test_graph_transform_observer 1/1 ... [2025-08-14 21:42:43.673891]
2025-08-14T21:42:43.6741061Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:43.6744691Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_graph_transform_observer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:43.674243]
2025-08-14T21:42:50.2605250Z 
2025-08-14T21:42:50.2606889Z inductor/test_graph_transform_observer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_graph_transform_observer_1.1_48d876ca94d7af92_.log
2025-08-14T21:42:50.2608021Z 
2025-08-14T21:42:50.2609554Z Running dynamo/test_unittest 1/1 ... [2025-08-14 21:42:50.260767]
2025-08-14T21:42:50.2610091Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:50.2613418Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_unittest.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:50.261122]
2025-08-14T21:42:53.4879507Z 
2025-08-14T21:42:53.4880555Z dynamo/test_unittest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unittest_1.1_856d56bff7826bb1_.log
2025-08-14T21:42:53.4881374Z 
2025-08-14T21:42:53.4883492Z Running dynamo/test_sources 1/1 ... [2025-08-14 21:42:53.488103]
2025-08-14T21:42:53.4884370Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:53.4887843Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:53.488475]
2025-08-14T21:42:56.5040640Z 
2025-08-14T21:42:56.5042261Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_2be10d5e518af0d3_.log
2025-08-14T21:42:56.5043490Z 
2025-08-14T21:42:56.5045967Z Running inductor/test_torchinductor_codegen_config_overrides 1/1 ... [2025-08-14 21:42:56.504371]
2025-08-14T21:42:56.5047139Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:42:56.5050962Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_codegen_config_overrides.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:42:56.504760]
2025-08-14T21:43:03.2269926Z 
2025-08-14T21:43:03.2272302Z inductor/test_torchinductor_codegen_config_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_config_overrides_1.1_982782caa1ee97ff_.log
2025-08-14T21:43:03.2274021Z 
2025-08-14T21:43:03.2275346Z Running dynamo/test_guard_serialization 1/1 ... [2025-08-14 21:43:03.227329]
2025-08-14T21:43:03.2276250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:03.2281456Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_guard_serialization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:03.227779]
2025-08-14T21:43:09.7888408Z 
2025-08-14T21:43:09.7889576Z dynamo/test_guard_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_guard_serialization_1.1_74f719146c41c120_.log
2025-08-14T21:43:09.7890435Z 
2025-08-14T21:43:09.7892355Z Running inductor/test_scatter_optimization 1/1 ... [2025-08-14 21:43:09.789055]
2025-08-14T21:43:09.7893193Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:09.7896336Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_scatter_optimization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:09.789412]
2025-08-14T21:43:16.3789661Z 
2025-08-14T21:43:16.3790897Z inductor/test_scatter_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_scatter_optimization_1.1_c5a137356a88ef25_.log
2025-08-14T21:43:16.3791831Z 
2025-08-14T21:43:16.3793486Z Running export/test_upgrader 1/1 ... [2025-08-14 21:43:16.379174]
2025-08-14T21:43:16.3794161Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:16.3797468Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:16.379506]
2025-08-14T21:43:19.4229874Z 
2025-08-14T21:43:19.4230963Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_b0c7995fd972b4e7_.log
2025-08-14T21:43:19.4232124Z 
2025-08-14T21:43:19.4232383Z Running dynamo/test_einops 1/1 ... [2025-08-14 21:43:19.423044]
2025-08-14T21:43:19.4232907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:19.4235673Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:19.423349]
2025-08-14T21:43:22.4551792Z 
2025-08-14T21:43:22.4552959Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_299bfcf7c2e55924_.log
2025-08-14T21:43:22.4553817Z 
2025-08-14T21:43:22.4555882Z Running export/test_nativert 1/1 ... [2025-08-14 21:43:22.455408]
2025-08-14T21:43:22.4556455Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:22.4559334Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_nativert.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:22.455713]
2025-08-14T21:43:29.0917524Z 
2025-08-14T21:43:29.0918889Z export/test_nativert 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_nativert_1.1_776ded7fa83a2818_.log
2025-08-14T21:43:29.0919613Z 
2025-08-14T21:43:29.0921248Z Running inductor/test_auto_functionalize 1/1 ... [2025-08-14 21:43:29.091980]
2025-08-14T21:43:29.0922015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:29.0926139Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:29.092333]
2025-08-14T21:43:32.3970147Z 
2025-08-14T21:43:32.3971433Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_3367b33bb9bc1526_.log
2025-08-14T21:43:32.3972260Z 
2025-08-14T21:43:32.3974359Z Running dynamo/test_export 1/1 ... [2025-08-14 21:43:32.397260]
2025-08-14T21:43:32.3975039Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:32.3978071Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:32.397570]
2025-08-14T21:43:35.7240046Z 
2025-08-14T21:43:35.7241005Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_083dd97cbe7c8df2_.log
2025-08-14T21:43:35.7241860Z 
2025-08-14T21:43:35.7244502Z Running dynamo/test_sets 1/1 ... [2025-08-14 21:43:35.724274]
2025-08-14T21:43:35.7245083Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:35.7248485Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sets.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:35.724617]
2025-08-14T21:43:39.0034609Z 
2025-08-14T21:43:39.0035597Z dynamo/test_sets 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sets_1.1_01ae7bdd642917fb_.log
2025-08-14T21:43:39.0036279Z 
2025-08-14T21:43:39.0038836Z Running dynamo/test_profiler 1/1 ... [2025-08-14 21:43:39.003732]
2025-08-14T21:43:39.0039484Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:39.0042994Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:39.004073]
2025-08-14T21:43:42.3345612Z 
2025-08-14T21:43:42.3347612Z dynamo/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_profiler_1.1_e0804c4f5b9fac74_.log
2025-08-14T21:43:42.3348853Z 
2025-08-14T21:43:42.3351063Z Running dynamo/test_optimizers 1/1 ... [2025-08-14 21:43:42.334898]
2025-08-14T21:43:42.3351987Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:42.3356791Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_optimizers.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:42.335341]
2025-08-14T21:43:45.5931682Z 
2025-08-14T21:43:45.5933161Z dynamo/test_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_optimizers_1.1_b65750e3538c3820_.log
2025-08-14T21:43:45.5934174Z 
2025-08-14T21:43:45.5934458Z Running dynamo/test_python_dispatcher 1/1 ... [2025-08-14 21:43:45.593214]
2025-08-14T21:43:45.5935261Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:45.5938741Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:45.593598]
2025-08-14T21:43:48.8375664Z 
2025-08-14T21:43:48.8376932Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_24d20326b7f85c50_.log
2025-08-14T21:43:48.8377789Z 
2025-08-14T21:43:48.8379569Z Running dynamo/test_package 1/1 ... [2025-08-14 21:43:48.837777]
2025-08-14T21:43:48.8380098Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:48.8390132Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:48.838106]
2025-08-14T21:43:55.3843183Z 
2025-08-14T21:43:55.3844378Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_6194cf4bddfb86b6_.log
2025-08-14T21:43:55.3845148Z 
2025-08-14T21:43:55.3847372Z Running dynamo/test_input_attr_tracking 1/1 ... [2025-08-14 21:43:55.384558]
2025-08-14T21:43:55.3847860Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:55.3850993Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_input_attr_tracking.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:55.384894]
2025-08-14T21:43:58.6629461Z 
2025-08-14T21:43:58.6630485Z dynamo/test_input_attr_tracking 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_input_attr_tracking_1.1_a14c2329e71752f5_.log
2025-08-14T21:43:58.6631327Z 
2025-08-14T21:43:58.6633297Z Running dynamo/test_callback 1/1 ... [2025-08-14 21:43:58.663174]
2025-08-14T21:43:58.6633757Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:43:58.6637171Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_callback.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:43:58.663501]
2025-08-14T21:44:05.2859773Z 
2025-08-14T21:44:05.2860667Z dynamo/test_callback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_callback_1.1_0deacb0c6e98ef94_.log
2025-08-14T21:44:05.2861582Z 
2025-08-14T21:44:05.2863502Z Running dynamo/test_aot_autograd_cache 1/1 ... [2025-08-14 21:44:05.286193]
2025-08-14T21:44:05.2863980Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:05.2867485Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_aot_autograd_cache.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:05.286533]
2025-08-14T21:44:11.9360309Z 
2025-08-14T21:44:11.9361338Z dynamo/test_aot_autograd_cache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_cache_1.1_8620b260560d109d_.log
2025-08-14T21:44:11.9362094Z 
2025-08-14T21:44:11.9363864Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-08-14 21:44:11.936222]
2025-08-14T21:44:11.9364410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:11.9367820Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:11.936563]
2025-08-14T21:44:15.1909868Z 
2025-08-14T21:44:15.1911225Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_e8919e5cc262f8c6_.log
2025-08-14T21:44:15.1912261Z 
2025-08-14T21:44:15.1913399Z Running dynamo/test_torchrec 1/1 ... [2025-08-14 21:44:15.191184]
2025-08-14T21:44:15.1913846Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:15.1917093Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_torchrec.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:15.191504]
2025-08-14T21:44:18.4936930Z 
2025-08-14T21:44:18.4937884Z dynamo/test_torchrec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_torchrec_1.1_109b8bae31094fc0_.log
2025-08-14T21:44:18.4938625Z 
2025-08-14T21:44:18.4940334Z Running dynamo/test_hooks 1/1 ... [2025-08-14 21:44:18.493879]
2025-08-14T21:44:18.4940761Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:18.4944269Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_hooks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:18.494205]
2025-08-14T21:44:21.7750643Z 
2025-08-14T21:44:21.7751766Z dynamo/test_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_hooks_1.1_644e5e445034aaeb_.log
2025-08-14T21:44:21.7752497Z 
2025-08-14T21:44:21.7754370Z Running dynamo/test_reorder_logs 1/1 ... [2025-08-14 21:44:21.775262]
2025-08-14T21:44:21.7754890Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:21.7758094Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_reorder_logs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:21.775595]
2025-08-14T21:44:25.0595097Z 
2025-08-14T21:44:25.0596125Z dynamo/test_reorder_logs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reorder_logs_1.1_8e5865b3e14068b7_.log
2025-08-14T21:44:25.0597128Z 
2025-08-14T21:44:25.0598637Z Running dynamo/test_comptime 1/1 ... [2025-08-14 21:44:25.059704]
2025-08-14T21:44:25.0599080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:25.0602723Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:25.060037]
2025-08-14T21:44:28.3559547Z 
2025-08-14T21:44:28.3560471Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_6e9e83cd6e785f20_.log
2025-08-14T21:44:28.3561152Z 
2025-08-14T21:44:28.3563232Z Running test_quantization 2/4 ... [2025-08-14 21:44:28.356157]
2025-08-14T21:44:28.3563651Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:28.3566698Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:28.356472]
2025-08-14T21:44:33.3775799Z 
2025-08-14T21:44:33.3777265Z test_quantization 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_2.4_2a341943a8790685_.log
2025-08-14T21:44:33.3778541Z Running 0 items in this shard:
2025-08-14T21:44:33.3778861Z 
2025-08-14T21:44:33.3779832Z Running test_quantization 3/4 ... [2025-08-14 21:44:33.377816]
2025-08-14T21:44:33.3780531Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:33.3784864Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'serial', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:33.378193]
2025-08-14T21:44:37.9486418Z 
2025-08-14T21:44:37.9487694Z test_quantization 3/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_3.4_de8f1ca15741d347_.log
2025-08-14T21:44:37.9489084Z Running 0 items in this shard:
2025-08-14T21:44:37.9489410Z 
2025-08-14T21:44:37.9491699Z Running test_quantization 4/4 ... [2025-08-14 21:44:37.948980]
2025-08-14T21:44:37.9492353Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:37.9497210Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'serial', '--shard-id=4', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:37.949398]
2025-08-14T21:44:42.5200355Z 
2025-08-14T21:44:42.5201557Z test_quantization 4/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_4.4_24e880a724e74156_.log
2025-08-14T21:44:42.5202398Z Running 0 items in this shard:
2025-08-14T21:44:42.5202592Z 
2025-08-14T21:44:42.5204393Z Running dynamo/cpython/3_13/test_defaultdict 1/1 ... [2025-08-14 21:44:42.520267]
2025-08-14T21:44:42.5204952Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:42.5208354Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_defaultdict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:42.520594]
2025-08-14T21:44:45.6562068Z 
2025-08-14T21:44:45.6563235Z dynamo/cpython/3_13/test_defaultdict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_defaultdict_1.1_c40947f9b65c594d_.log
2025-08-14T21:44:45.6564183Z Running 0 items in this shard:
2025-08-14T21:44:45.6564397Z 
2025-08-14T21:44:45.6566188Z Running test_transformers 2/3 ... [2025-08-14 21:44:45.656410]
2025-08-14T21:44:45.6566870Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:45.6569838Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:45.656747]
2025-08-14T21:44:50.5775498Z 
2025-08-14T21:44:50.5776472Z test_transformers 2/3 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_2.3_c75bce45d0189720_.log
2025-08-14T21:44:50.5777296Z Running 0 items in this shard:
2025-08-14T21:44:50.5777545Z 
2025-08-14T21:44:50.5779429Z Running test_transformers 3/3 ... [2025-08-14 21:44:50.577777]
2025-08-14T21:44:50.5779897Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:50.5783260Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:50.578104]
2025-08-14T21:44:55.4990351Z 
2025-08-14T21:44:55.4991217Z test_transformers 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_3.3_2b04db3957245b2e_.log
2025-08-14T21:44:55.4992077Z Running 0 items in this shard:
2025-08-14T21:44:55.4992299Z 
2025-08-14T21:44:55.4994792Z Running test_ao_sparsity 1/1 ... [2025-08-14 21:44:55.499307]
2025-08-14T21:44:55.4995215Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:55.4999073Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ao_sparsity.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:55.499659]
2025-08-14T21:44:59.0688110Z 
2025-08-14T21:44:59.0689321Z test_ao_sparsity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ao_sparsity_1.1_9635e60127a046f7_.log
2025-08-14T21:44:59.0690080Z Running 0 items in this shard:
2025-08-14T21:44:59.0690275Z 
2025-08-14T21:44:59.0692456Z Running test_license 1/1 ... [2025-08-14 21:44:59.069072]
2025-08-14T21:44:59.0693107Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:44:59.0696540Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_license.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:44:59.069395]
2025-08-14T21:45:02.2884423Z 
2025-08-14T21:45:02.2885561Z test_license 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_license_1.1_003dc56c06358a31_.log
2025-08-14T21:45:02.2886283Z Running 0 items in this shard:
2025-08-14T21:45:02.2886707Z 
2025-08-14T21:45:02.2888232Z Running torch_np/test_binary_ufuncs 1/1 ... [2025-08-14 21:45:02.288666]
2025-08-14T21:45:02.2888883Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:02.2892448Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_binary_ufuncs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:02.289000]
2025-08-14T21:45:05.5579220Z 
2025-08-14T21:45:05.5580487Z torch_np/test_binary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_binary_ufuncs_1.1_57274a1d55f45e57_.log
2025-08-14T21:45:05.5581341Z Running 0 items in this shard:
2025-08-14T21:45:05.5581545Z 
2025-08-14T21:45:05.5583207Z Running xpu/test_fusion 1/1 ... [2025-08-14 21:45:05.558142]
2025-08-14T21:45:05.5583890Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:05.5587803Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_fusion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:05.558527]
2025-08-14T21:45:08.7197353Z 
2025-08-14T21:45:08.7198494Z xpu/test_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_fusion_1.1_469c4116b0781987_.log
2025-08-14T21:45:08.7199491Z Running 0 items in this shard:
2025-08-14T21:45:08.7199683Z 
2025-08-14T21:45:08.7201677Z Running torch_np/test_unary_ufuncs 1/1 ... [2025-08-14 21:45:08.719982]
2025-08-14T21:45:08.7202322Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:08.7205564Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_unary_ufuncs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:08.720310]
2025-08-14T21:45:11.8888733Z 
2025-08-14T21:45:11.8890051Z torch_np/test_unary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_unary_ufuncs_1.1_a2c2b05cc5236b4b_.log
2025-08-14T21:45:11.8890889Z Running 0 items in this shard:
2025-08-14T21:45:11.8891080Z 
2025-08-14T21:45:11.8892596Z Running test_foreach 1/1 ... [2025-08-14 21:45:11.889099]
2025-08-14T21:45:11.8893242Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:11.8896571Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_foreach.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:11.889432]
2025-08-14T21:45:20.4153409Z 
2025-08-14T21:45:20.4154599Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_3300edf4bdede3a5_.log
2025-08-14T21:45:20.4155330Z Running 0 items in this shard:
2025-08-14T21:45:20.4155542Z 
2025-08-14T21:45:20.4158135Z Running test_expanded_weights 1/1 ... [2025-08-14 21:45:20.415613]
2025-08-14T21:45:20.4158778Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:20.4162181Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_expanded_weights.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:20.415955]
2025-08-14T21:45:24.6860310Z 
2025-08-14T21:45:24.6861930Z test_expanded_weights 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_expanded_weights_1.1_61ea711e727b18d3_.log
2025-08-14T21:45:24.6862789Z Running 0 items in this shard:
2025-08-14T21:45:24.6862982Z 
2025-08-14T21:45:24.6864798Z Running typing/test_python_operators 1/1 ... [2025-08-14 21:45:24.686293]
2025-08-14T21:45:24.6865335Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:24.6869026Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'typing/test_python_operators.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:24.686663]
2025-08-14T21:45:27.9052403Z 
2025-08-14T21:45:27.9053423Z typing/test_python_operators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/typing.test_python_operators_1.1_95051ed3583e6655_.log
2025-08-14T21:45:27.9054296Z Running 0 items in this shard:
2025-08-14T21:45:27.9054509Z 
2025-08-14T21:45:27.9056584Z Running test_fx_experimental 1/1 ... [2025-08-14 21:45:27.905505]
2025-08-14T21:45:27.9057016Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:27.9060902Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_experimental.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:27.905860]
2025-08-14T21:45:32.4762845Z 
2025-08-14T21:45:32.4763719Z test_fx_experimental 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_experimental_1.1_29921693c66b195d_.log
2025-08-14T21:45:32.4764504Z Running 0 items in this shard:
2025-08-14T21:45:32.4764697Z 
2025-08-14T21:45:32.4766754Z Running test_file_check 1/1 ... [2025-08-14 21:45:32.476517]
2025-08-14T21:45:32.4767369Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:32.4770905Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_file_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:32.476863]
2025-08-14T21:45:35.6455116Z 
2025-08-14T21:45:35.6456026Z test_file_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_file_check_1.1_87c8afa100772e78_.log
2025-08-14T21:45:35.6456754Z Running 0 items in this shard:
2025-08-14T21:45:35.6456957Z 
2025-08-14T21:45:35.6459364Z Running torch_np/test_dtype 1/1 ... [2025-08-14 21:45:35.645768]
2025-08-14T21:45:35.6459794Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:35.6462854Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_dtype.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:35.646090]
2025-08-14T21:45:38.8648658Z 
2025-08-14T21:45:38.8649565Z torch_np/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_dtype_1.1_692afa5ffa65987d_.log
2025-08-14T21:45:38.8650341Z Running 0 items in this shard:
2025-08-14T21:45:38.8650534Z 
2025-08-14T21:45:38.8652321Z Running higher_order_ops/test_with_effects 1/1 ... [2025-08-14 21:45:38.865062]
2025-08-14T21:45:38.8652874Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:38.8656591Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:38.865419]
2025-08-14T21:45:42.6349861Z 
2025-08-14T21:45:42.6351861Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_6e7eb00014eebc15_.log
2025-08-14T21:45:42.6353490Z Running 0 items in this shard:
2025-08-14T21:45:42.6353761Z 
2025-08-14T21:45:42.6355719Z Running test_native_functions 1/1 ... [2025-08-14 21:45:42.635372]
2025-08-14T21:45:42.6356388Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:42.6361431Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_functions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:42.635796]
2025-08-14T21:45:45.8043518Z 
2025-08-14T21:45:45.8044899Z test_native_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_functions_1.1_74cf40a6adf40a49_.log
2025-08-14T21:45:45.8046330Z Running 0 items in this shard:
2025-08-14T21:45:45.8046679Z 
2025-08-14T21:45:45.8049681Z Running functorch/test_minifier 1/1 ... [2025-08-14 21:45:45.804768]
2025-08-14T21:45:45.8050420Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:45.8055113Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_minifier.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:45.805187]
2025-08-14T21:45:49.2242313Z 
2025-08-14T21:45:49.2243738Z functorch/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_minifier_1.1_5cb3cd5fd9ffb3c3_.log
2025-08-14T21:45:49.2245517Z Running 0 items in this shard:
2025-08-14T21:45:49.2245813Z 
2025-08-14T21:45:49.2247955Z Running test_flop_counter 1/1 ... [2025-08-14 21:45:49.224609]
2025-08-14T21:45:49.2248595Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:49.2253597Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_flop_counter.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:49.225033]
2025-08-14T21:45:52.5439955Z 
2025-08-14T21:45:52.5441275Z test_flop_counter 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_flop_counter_1.1_ed0d95f4a1a84d30_.log
2025-08-14T21:45:52.5442625Z Running 0 items in this shard:
2025-08-14T21:45:52.5442986Z 
2025-08-14T21:45:52.5445905Z Running torch_np/test_nep50_examples 1/1 ... [2025-08-14 21:45:52.544386]
2025-08-14T21:45:52.5446649Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:52.5451069Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_nep50_examples.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:52.544800]
2025-08-14T21:45:55.9137600Z 
2025-08-14T21:45:55.9138614Z torch_np/test_nep50_examples 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_nep50_examples_1.1_564172ca556962a4_.log
2025-08-14T21:45:55.9139467Z Running 0 items in this shard:
2025-08-14T21:45:55.9139656Z 
2025-08-14T21:45:55.9141788Z Running higher_order_ops/test_invoke_quant 1/1 ... [2025-08-14 21:45:55.913996]
2025-08-14T21:45:55.9142265Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:45:55.9145663Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_quant.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:45:55.914339]
2025-08-14T21:46:02.7881089Z 
2025-08-14T21:46:02.7882248Z higher_order_ops/test_invoke_quant 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_quant_1.1_84926d6a7c4e8b41_.log
2025-08-14T21:46:02.7883183Z Running 0 items in this shard:
2025-08-14T21:46:02.7883374Z 
2025-08-14T21:46:02.7885832Z Running test_per_overload_api 1/1 ... [2025-08-14 21:46:02.788356]
2025-08-14T21:46:02.7886274Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:02.7889586Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_per_overload_api.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:02.788719]
2025-08-14T21:46:05.9572946Z 
2025-08-14T21:46:05.9574065Z test_per_overload_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_per_overload_api_1.1_b2c8b521494acb62_.log
2025-08-14T21:46:05.9575513Z Running 0 items in this shard:
2025-08-14T21:46:05.9575884Z 
2025-08-14T21:46:05.9577209Z Running test_tensorexpr_pybind 1/1 ... [2025-08-14 21:46:05.957522]
2025-08-14T21:46:05.9577731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:05.9581800Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr_pybind.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:05.957937]
2025-08-14T21:46:09.1765653Z 
2025-08-14T21:46:09.1766617Z test_tensorexpr_pybind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_pybind_1.1_67d4b16c70eaeba6_.log
2025-08-14T21:46:09.1767636Z Running 0 items in this shard:
2025-08-14T21:46:09.1767828Z 
2025-08-14T21:46:09.1769796Z Running test_pytree 1/1 ... [2025-08-14 21:46:09.176797]
2025-08-14T21:46:09.1770251Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:09.1773551Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pytree.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:09.177125]
2025-08-14T21:46:12.3958121Z 
2025-08-14T21:46:12.3958988Z test_pytree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pytree_1.1_b056bb54f4a8dfe2_.log
2025-08-14T21:46:12.3959702Z Running 0 items in this shard:
2025-08-14T21:46:12.3959896Z 
2025-08-14T21:46:12.3962479Z Running test_fx_passes 1/1 ... [2025-08-14 21:46:12.396090]
2025-08-14T21:46:12.3962935Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:12.3967105Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_passes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:12.396472]
2025-08-14T21:46:15.6151420Z 
2025-08-14T21:46:15.6152467Z test_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_passes_1.1_9cfc0e9cb944fdf8_.log
2025-08-14T21:46:15.6153226Z Running 0 items in this shard:
2025-08-14T21:46:15.6153431Z 
2025-08-14T21:46:15.6155351Z Running test_module_tracker 1/1 ... [2025-08-14 21:46:15.615380]
2025-08-14T21:46:15.6155820Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:15.6159373Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_module_tracker.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:15.615715]
2025-08-14T21:46:18.7843284Z 
2025-08-14T21:46:18.7844473Z test_module_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_module_tracker_1.1_ea168a5d3c358ced_.log
2025-08-14T21:46:18.7845321Z Running 0 items in this shard:
2025-08-14T21:46:18.7845514Z 
2025-08-14T21:46:18.7847802Z Running test_typing 1/1 ... [2025-08-14 21:46:18.784576]
2025-08-14T21:46:18.7848227Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:18.7851740Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_typing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:18.784941]
2025-08-14T21:46:22.0036333Z 
2025-08-14T21:46:22.0037443Z test_typing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_typing_1.1_d2abd7995cfc1485_.log
2025-08-14T21:46:22.0038175Z Running 0 items in this shard:
2025-08-14T21:46:22.0038378Z 
2025-08-14T21:46:22.0040740Z Running test_openmp 1/1 ... [2025-08-14 21:46:22.003913]
2025-08-14T21:46:22.0041192Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:22.0045140Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_openmp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:22.004290]
2025-08-14T21:46:25.2230393Z 
2025-08-14T21:46:25.2231248Z test_openmp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openmp_1.1_c0f38697ed6ba722_.log
2025-08-14T21:46:25.2232039Z Running 0 items in this shard:
2025-08-14T21:46:25.2232232Z 
2025-08-14T21:46:25.2234808Z Running torch_np/numpy_tests/core/test_scalarinherit 1/1 ... [2025-08-14 21:46:25.223312]
2025-08-14T21:46:25.2235402Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:25.2239107Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarinherit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:25.223680]
2025-08-14T21:46:28.4425043Z 
2025-08-14T21:46:28.4427036Z torch_np/numpy_tests/core/test_scalarinherit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarinherit_1.1_9f041816c674505e_.log
2025-08-14T21:46:28.4428936Z Running 0 items in this shard:
2025-08-14T21:46:28.4429251Z 
2025-08-14T21:46:28.4430394Z Running functorch/test_ac_knapsack 1/1 ... [2025-08-14 21:46:28.442863]
2025-08-14T21:46:28.4431124Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:28.4436318Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_knapsack.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:28.443314]
2025-08-14T21:46:31.7121077Z 
2025-08-14T21:46:31.7122268Z functorch/test_ac_knapsack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_knapsack_1.1_e984eac796264403_.log
2025-08-14T21:46:31.7123188Z Running 0 items in this shard:
2025-08-14T21:46:31.7123383Z 
2025-08-14T21:46:31.7125368Z Running backends/xeon/test_launch 1/1 ... [2025-08-14 21:46:31.712372]
2025-08-14T21:46:31.7125826Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:31.7129427Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'backends/xeon/test_launch.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:31.712724]
2025-08-14T21:46:34.9314364Z 
2025-08-14T21:46:34.9315844Z backends/xeon/test_launch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/backends.xeon.test_launch_1.1_5f70f97b2fe01678_.log
2025-08-14T21:46:34.9317366Z Running 0 items in this shard:
2025-08-14T21:46:34.9317633Z 
2025-08-14T21:46:34.9320333Z Running test_nestedtensor 1/4 ... [2025-08-14 21:46:34.931762]
2025-08-14T21:46:34.9321030Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:34.9325687Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nestedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:34.932207]
2025-08-14T21:46:39.7529747Z 
2025-08-14T21:46:39.7531090Z test_nestedtensor 1/4 was successful, full logs can be found in artifacts with path test/test-reports/test_nestedtensor_1.4_3f5d600fe46846bd_.log
2025-08-14T21:46:39.7532471Z Running 0 items in this shard:
2025-08-14T21:46:39.7532826Z 
2025-08-14T21:46:39.7535873Z Running test_namedtensor 1/1 ... [2025-08-14 21:46:39.753368]
2025-08-14T21:46:39.7536576Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:39.7540840Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_namedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:39.753778]
2025-08-14T21:46:43.0224829Z 
2025-08-14T21:46:43.0225776Z test_namedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtensor_1.1_b3996843848adf81_.log
2025-08-14T21:46:43.0226515Z Running 0 items in this shard:
2025-08-14T21:46:43.0226722Z 
2025-08-14T21:46:43.0229138Z Running torch_np/test_ufuncs_basic 1/1 ... [2025-08-14 21:46:43.022757]
2025-08-14T21:46:43.0229597Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:43.0232966Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ufuncs_basic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:43.023085]
2025-08-14T21:46:46.2918006Z 
2025-08-14T21:46:46.2918930Z torch_np/test_ufuncs_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ufuncs_basic_1.1_13dc3178aa8f2d59_.log
2025-08-14T21:46:46.2919767Z Running 0 items in this shard:
2025-08-14T21:46:46.2920220Z 
2025-08-14T21:46:46.2922348Z Running test_meta 1/1 ... [2025-08-14 21:46:46.292054]
2025-08-14T21:46:46.2922732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:46.2926189Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_meta.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:46.292415]
2025-08-14T21:46:57.5217582Z 
2025-08-14T21:46:57.5218378Z test_meta 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_meta_1.1_c4a977b2376b5daf_.log
2025-08-14T21:46:57.5219054Z Running 0 items in this shard:
2025-08-14T21:46:57.5219256Z 
2025-08-14T21:46:57.5221477Z Running test_utils_filelock 1/1 ... [2025-08-14 21:46:57.521986]
2025-08-14T21:46:57.5221923Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:46:57.5225608Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_filelock.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:46:57.522336]
2025-08-14T21:47:00.6908745Z 
2025-08-14T21:47:00.6909798Z test_utils_filelock 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_filelock_1.1_e4f45b00f6ede09d_.log
2025-08-14T21:47:00.6910585Z Running 0 items in this shard:
2025-08-14T21:47:00.6910814Z 
2025-08-14T21:47:00.6913582Z Running torch_np/test_random 1/1 ... [2025-08-14 21:47:00.691123]
2025-08-14T21:47:00.6914044Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:00.6917390Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_random.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:00.691467]
2025-08-14T21:47:03.9602322Z 
2025-08-14T21:47:03.9603792Z torch_np/test_random 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_random_1.1_1f2269a5575f747c_.log
2025-08-14T21:47:03.9604598Z Running 0 items in this shard:
2025-08-14T21:47:03.9604789Z 
2025-08-14T21:47:03.9606834Z Running profiler/test_kineto 1/1 ... [2025-08-14 21:47:03.960472]
2025-08-14T21:47:03.9607432Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:03.9611249Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:03.960802]
2025-08-14T21:47:07.1293717Z 
2025-08-14T21:47:07.1294927Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_5d021c3308588d15_.log
2025-08-14T21:47:07.1295720Z Running 0 items in this shard:
2025-08-14T21:47:07.1295935Z 
2025-08-14T21:47:07.1297738Z Running test_compile_benchmark_util 1/1 ... [2025-08-14 21:47:07.129594]
2025-08-14T21:47:07.1298364Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:07.1301758Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_compile_benchmark_util.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:07.129925]
2025-08-14T21:47:10.5989234Z 
2025-08-14T21:47:10.5990588Z test_compile_benchmark_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_compile_benchmark_util_1.1_27298c5489a827b1_.log
2025-08-14T21:47:10.5991429Z Running 0 items in this shard:
2025-08-14T21:47:10.5991719Z 
2025-08-14T21:47:10.5993472Z Running test_jiterator 1/1 ... [2025-08-14 21:47:10.599175]
2025-08-14T21:47:10.5994133Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:10.5997687Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jiterator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:10.599506]
2025-08-14T21:47:13.7445689Z 
2025-08-14T21:47:13.7446830Z test_jiterator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jiterator_1.1_33c6d6c73eaf4c00_.log
2025-08-14T21:47:13.7447590Z Running 0 items in this shard:
2025-08-14T21:47:13.7447794Z 
2025-08-14T21:47:13.7449682Z Running test_optim 1/1 ... [2025-08-14 21:47:13.744795]
2025-08-14T21:47:13.7450301Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:13.7453750Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:13.745126]
2025-08-14T21:47:18.1153122Z 
2025-08-14T21:47:18.1154151Z test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_1.1_efe29e1834117d68_.log
2025-08-14T21:47:18.1155358Z Running 0 items in this shard:
2025-08-14T21:47:18.1155660Z 
2025-08-14T21:47:18.1157279Z Running test_decomp 1/1 ... [2025-08-14 21:47:18.115543]
2025-08-14T21:47:18.1157933Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:18.1161110Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:18.115866]
2025-08-14T21:47:23.9381188Z 
2025-08-14T21:47:23.9382327Z test_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.1_c743083d0c623bf7_.log
2025-08-14T21:47:23.9383039Z Running 0 items in this shard:
2025-08-14T21:47:23.9383249Z 
2025-08-14T21:47:23.9385194Z Running torch_np/test_basic 1/1 ... [2025-08-14 21:47:23.938341]
2025-08-14T21:47:23.9385837Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:23.9388763Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_basic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:23.938675]
2025-08-14T21:47:27.2574514Z 
2025-08-14T21:47:27.2575537Z torch_np/test_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_basic_1.1_fa1e584f22a30998_.log
2025-08-14T21:47:27.2576336Z Running 0 items in this shard:
2025-08-14T21:47:27.2576529Z 
2025-08-14T21:47:27.2578430Z Running lazy/test_bindings 1/1 ... [2025-08-14 21:47:27.257654]
2025-08-14T21:47:27.2579073Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:27.2582622Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_bindings.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:27.258005]
2025-08-14T21:47:30.5267621Z 
2025-08-14T21:47:30.5268786Z lazy/test_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_bindings_1.1_4cf07b4ac26b3905_.log
2025-08-14T21:47:30.5269567Z Running 0 items in this shard:
2025-08-14T21:47:30.5269782Z 
2025-08-14T21:47:30.5272607Z Running test_legacy_vmap 1/1 ... [2025-08-14 21:47:30.527009]
2025-08-14T21:47:30.5273337Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:30.5276004Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_legacy_vmap.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:30.527345]
2025-08-14T21:47:33.7962147Z 
2025-08-14T21:47:33.7963465Z test_legacy_vmap 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_legacy_vmap_1.1_e3f606b14e98e685_.log
2025-08-14T21:47:33.7964814Z Running 0 items in this shard:
2025-08-14T21:47:33.7965155Z 
2025-08-14T21:47:33.7968083Z Running test_modules 1/2 ... [2025-08-14 21:47:33.796575]
2025-08-14T21:47:33.7968732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:33.7973364Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:33.796993]
2025-08-14T21:47:38.5179413Z 
2025-08-14T21:47:38.5180260Z test_modules 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.2_1a18c16db2c29bdb_.log
2025-08-14T21:47:38.5180976Z Running 0 items in this shard:
2025-08-14T21:47:38.5181190Z 
2025-08-14T21:47:38.5183829Z Running test_modules 2/2 ... [2025-08-14 21:47:38.518209]
2025-08-14T21:47:38.5184311Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:38.5188077Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_modules.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:38.518578]
2025-08-14T21:47:43.2393487Z 
2025-08-14T21:47:43.2394376Z test_modules 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_2.2_e1d8e6a65774af4b_.log
2025-08-14T21:47:43.2395087Z Running 0 items in this shard:
2025-08-14T21:47:43.2395292Z 
2025-08-14T21:47:43.2397681Z Running xpu/test_conv 1/1 ... [2025-08-14 21:47:43.239599]
2025-08-14T21:47:43.2398081Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:43.2401641Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:43.239919]
2025-08-14T21:47:46.8147454Z 
2025-08-14T21:47:46.8148319Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_48af30b538dd4b96_.log
2025-08-14T21:47:46.8149043Z Running 0 items in this shard:
2025-08-14T21:47:46.8149234Z 
2025-08-14T21:47:46.8151833Z Running test_ops_jit 2/2 ... [2025-08-14 21:47:46.814984]
2025-08-14T21:47:46.8152244Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:46.8155562Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:46.815343]
2025-08-14T21:47:51.1855496Z 
2025-08-14T21:47:51.1856699Z test_ops_jit 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_2.2_0d0178b520a147f4_.log
2025-08-14T21:47:51.1857394Z Running 0 items in this shard:
2025-08-14T21:47:51.1857601Z 
2025-08-14T21:47:51.1859186Z Running test_fx_reinplace_pass 1/1 ... [2025-08-14 21:47:51.185753]
2025-08-14T21:47:51.1859837Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:51.1863508Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_reinplace_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:51.186083]
2025-08-14T21:47:54.3546500Z 
2025-08-14T21:47:54.3547726Z test_fx_reinplace_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_reinplace_pass_1.1_aa5267b6b9369934_.log
2025-08-14T21:47:54.3548536Z Running 0 items in this shard:
2025-08-14T21:47:54.3548730Z 
2025-08-14T21:47:54.3550949Z Running nn/test_multihead_attention 1/1 ... [2025-08-14 21:47:54.354886]
2025-08-14T21:47:54.3551667Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:54.3554897Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:54.355234]
2025-08-14T21:47:57.5238781Z 
2025-08-14T21:47:57.5240020Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_57fbc7c17be3503e_.log
2025-08-14T21:47:57.5240878Z Running 0 items in this shard:
2025-08-14T21:47:57.5241086Z 
2025-08-14T21:47:57.5243237Z Running functorch/test_aot_joint_with_descriptors 1/1 ... [2025-08-14 21:47:57.524118]
2025-08-14T21:47:57.5243860Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:47:57.5247155Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aot_joint_with_descriptors.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:47:57.524443]
2025-08-14T21:48:00.9434353Z 
2025-08-14T21:48:00.9435683Z functorch/test_aot_joint_with_descriptors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aot_joint_with_descriptors_1.1_35a3df65ac5078c3_.log
2025-08-14T21:48:00.9437308Z Running 0 items in this shard:
2025-08-14T21:48:00.9437587Z 
2025-08-14T21:48:00.9438288Z Running test_pruning_op 1/1 ... [2025-08-14 21:48:00.943636]
2025-08-14T21:48:00.9438679Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:00.9442175Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pruning_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:00.943987]
2025-08-14T21:48:04.1626351Z 
2025-08-14T21:48:04.1627453Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_06921947e1057db4_.log
2025-08-14T21:48:04.1628199Z Running 0 items in this shard:
2025-08-14T21:48:04.1628392Z 
2025-08-14T21:48:04.1630858Z Running lazy/test_functionalization 1/1 ... [2025-08-14 21:48:04.162898]
2025-08-14T21:48:04.1631427Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:04.1634983Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_functionalization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:04.163269]
2025-08-14T21:48:07.3819665Z 
2025-08-14T21:48:07.3820382Z lazy/test_functionalization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_functionalization_1.1_a6a9be90550ff488_.log
2025-08-14T21:48:07.3821255Z Running 0 items in this shard:
2025-08-14T21:48:07.3821449Z 
2025-08-14T21:48:07.3823713Z Running functorch/test_ac 1/1 ... [2025-08-14 21:48:07.382215]
2025-08-14T21:48:07.3824187Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:07.3828047Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:07.382571]
2025-08-14T21:48:13.9670655Z 
2025-08-14T21:48:13.9671992Z functorch/test_ac 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_1.1_b773f0661559a8ad_.log
2025-08-14T21:48:13.9672652Z 
2025-08-14T21:48:13.9674918Z Running test_ops_fwd_gradients 1/2 ... [2025-08-14 21:48:13.967299]
2025-08-14T21:48:13.9675593Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:13.9679214Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:13.967678]
2025-08-14T21:48:18.5881521Z 
2025-08-14T21:48:18.5882794Z test_ops_fwd_gradients 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_1.2_87298ca42f8dd656_.log
2025-08-14T21:48:18.5883594Z Running 0 items in this shard:
2025-08-14T21:48:18.5883809Z 
2025-08-14T21:48:18.5885965Z Running test_ops_fwd_gradients 2/2 ... [2025-08-14 21:48:18.588397]
2025-08-14T21:48:18.5886571Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:18.5889893Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:18.588734]
2025-08-14T21:48:23.2093298Z 
2025-08-14T21:48:23.2094303Z test_ops_fwd_gradients 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_2.2_f5dee9baffe2c2b2_.log
2025-08-14T21:48:23.2095218Z Running 0 items in this shard:
2025-08-14T21:48:23.2095414Z 
2025-08-14T21:48:23.2097484Z Running test_hub 1/1 ... [2025-08-14 21:48:23.209582]
2025-08-14T21:48:23.2097913Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:23.2101463Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_hub.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:23.209922]
2025-08-14T21:48:26.3786743Z 
2025-08-14T21:48:26.3787868Z test_hub 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_hub_1.1_23798eb315928355_.log
2025-08-14T21:48:26.3788567Z Running 0 items in this shard:
2025-08-14T21:48:26.3788757Z 
2025-08-14T21:48:26.3791115Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-08-14 21:48:26.378883]
2025-08-14T21:48:26.3791714Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:26.3795024Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:26.379242]
2025-08-14T21:48:29.5478806Z 
2025-08-14T21:48:29.5479901Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_989428a8a5d97e9c_.log
2025-08-14T21:48:29.5480811Z Running 0 items in this shard:
2025-08-14T21:48:29.5481026Z 
2025-08-14T21:48:29.5482554Z Running test_stateless 1/1 ... [2025-08-14 21:48:29.548104]
2025-08-14T21:48:29.5483052Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:29.5487097Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_stateless.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:29.548452]
2025-08-14T21:48:32.7670242Z 
2025-08-14T21:48:32.7671333Z test_stateless 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_stateless_1.1_eb6da774fd6ffb6a_.log
2025-08-14T21:48:32.7672409Z Running 0 items in this shard:
2025-08-14T21:48:32.7672601Z 
2025-08-14T21:48:32.7674464Z Running distributions/test_constraints 1/1 ... [2025-08-14 21:48:32.767263]
2025-08-14T21:48:32.7675111Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:32.7678537Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_constraints.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:32.767596]
2025-08-14T21:48:35.9362183Z 
2025-08-14T21:48:35.9363771Z distributions/test_constraints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_constraints_1.1_330cc8d59020995c_.log
2025-08-14T21:48:35.9365305Z Running 0 items in this shard:
2025-08-14T21:48:35.9365626Z 
2025-08-14T21:48:35.9367228Z Running profiler/test_record_function 1/1 ... [2025-08-14 21:48:35.936466]
2025-08-14T21:48:35.9368043Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:35.9370732Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_record_function.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:35.936813]
2025-08-14T21:48:39.1554452Z 
2025-08-14T21:48:39.1555679Z profiler/test_record_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_record_function_1.1_a37947f050eabfb8_.log
2025-08-14T21:48:39.1556565Z Running 0 items in this shard:
2025-08-14T21:48:39.1556759Z 
2025-08-14T21:48:39.1558667Z Running nn/test_lazy_modules 1/1 ... [2025-08-14 21:48:39.155669]
2025-08-14T21:48:39.1559100Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:39.1562269Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:39.156011]
2025-08-14T21:48:42.3247170Z 
2025-08-14T21:48:42.3248432Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_67df572349956891_.log
2025-08-14T21:48:42.3249214Z Running 0 items in this shard:
2025-08-14T21:48:42.3250657Z 
2025-08-14T21:48:42.3251292Z Running test_jit_fuser_te 1/1 ... [2025-08-14 21:48:42.324915]
2025-08-14T21:48:42.3251725Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:42.3254358Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_fuser_te.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:42.325237]
2025-08-14T21:48:48.4979212Z 
2025-08-14T21:48:48.4980008Z test_jit_fuser_te 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_fuser_te_1.1_1c21a3258c012d5e_.log
2025-08-14T21:48:48.4980762Z Running 0 items in this shard:
2025-08-14T21:48:48.4980968Z 
2025-08-14T21:48:48.4983297Z Running test_segment_reductions 1/1 ... [2025-08-14 21:48:48.498166]
2025-08-14T21:48:48.4983746Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:48.4987192Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:48.498514]
2025-08-14T21:48:51.7172416Z 
2025-08-14T21:48:51.7173683Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_c805a1a383057af0_.log
2025-08-14T21:48:51.7174533Z Running 0 items in this shard:
2025-08-14T21:48:51.7174724Z 
2025-08-14T21:48:51.7176487Z Running test_import_stats 1/1 ... [2025-08-14 21:48:51.717465]
2025-08-14T21:48:51.7177155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:51.7180441Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:51.717800]
2025-08-14T21:48:54.8863125Z 
2025-08-14T21:48:54.8864047Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_6638b92e9c6efec2_.log
2025-08-14T21:48:54.8864806Z Running 0 items in this shard:
2025-08-14T21:48:54.8865000Z 
2025-08-14T21:48:54.8867609Z Running test_masked 1/1 ... [2025-08-14 21:48:54.886597]
2025-08-14T21:48:54.8868007Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:54.8871882Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_masked.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:54.886965]
2025-08-14T21:48:59.1071387Z 
2025-08-14T21:48:59.1072281Z test_masked 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_masked_1.1_37c2da238051bede_.log
2025-08-14T21:48:59.1072976Z Running 0 items in this shard:
2025-08-14T21:48:59.1073221Z 
2025-08-14T21:48:59.1074606Z Running test_cuda_sanitizer 1/1 ... [2025-08-14 21:48:59.107291]
2025-08-14T21:48:59.1075031Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:48:59.1079133Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_sanitizer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:48:59.107700]
2025-08-14T21:49:02.3460366Z 
2025-08-14T21:49:02.3461670Z test_cuda_sanitizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_sanitizer_1.1_6d8ea40fd9468212_.log
2025-08-14T21:49:02.3463090Z Running 0 items in this shard:
2025-08-14T21:49:02.3463435Z 
2025-08-14T21:49:02.3466887Z Running test_monitor 1/1 ... [2025-08-14 21:49:02.346420]
2025-08-14T21:49:02.3467507Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:02.3471451Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:02.346797]
2025-08-14T21:49:05.5154052Z 
2025-08-14T21:49:05.5154913Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_ee45d520def4b8f4_.log
2025-08-14T21:49:05.5155614Z Running 0 items in this shard:
2025-08-14T21:49:05.5156079Z 
2025-08-14T21:49:05.5158015Z Running profiler/test_cpp_thread 1/1 ... [2025-08-14 21:49:05.515636]
2025-08-14T21:49:05.5158485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:05.5161921Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:05.515972]
2025-08-14T21:49:09.7361796Z 
2025-08-14T21:49:09.7363287Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_a77bfbb10403dfbf_.log
2025-08-14T21:49:09.7364779Z Running 0 items in this shard:
2025-08-14T21:49:09.7365072Z 
2025-08-14T21:49:09.7367364Z Running test_subclass 1/1 ... [2025-08-14 21:49:09.736522]
2025-08-14T21:49:09.7367805Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:09.7371091Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_subclass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:09.736885]
2025-08-14T21:49:12.9053976Z 
2025-08-14T21:49:12.9054831Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_1ef042cd490c337a_.log
2025-08-14T21:49:12.9055543Z Running 0 items in this shard:
2025-08-14T21:49:12.9055978Z 
2025-08-14T21:49:12.9058626Z Running profiler/test_profiler 1/1 ... [2025-08-14 21:49:12.905695]
2025-08-14T21:49:12.9059126Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:12.9062431Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:12.906042]
2025-08-14T21:49:16.3250740Z 
2025-08-14T21:49:16.3252018Z profiler/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_1.1_13042650aa6b472d_.log
2025-08-14T21:49:16.3259159Z Running 10 items in this shard: test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_basic_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_basic_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_close_in_scope_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_close_in_scope_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_complex_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_complex_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_multiple_preexisting_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_multiple_preexisting_work_in_main_thread_True, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_open_in_scope_work_in_main_thread_False, test/profiler/test_profiler.py::TestProfiler::test_source_multithreaded_open_in_scope_work_in_main_thread_True
2025-08-14T21:49:16.3264205Z 
2025-08-14T21:49:16.3264465Z Running functorch/test_vmap_registrations 1/1 ... [2025-08-14 21:49:16.325331]
2025-08-14T21:49:16.3264955Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:16.3266294Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:16.325691]
2025-08-14T21:49:19.6945155Z 
2025-08-14T21:49:19.6946848Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_cc77371062f69c51_.log
2025-08-14T21:49:19.6947838Z Running 0 items in this shard:
2025-08-14T21:49:19.6948095Z 
2025-08-14T21:49:19.6949271Z Running nn/test_pruning 1/1 ... [2025-08-14 21:49:19.694760]
2025-08-14T21:49:19.6949724Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:19.6953481Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_pruning.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:19.695106]
2025-08-14T21:49:22.9138065Z 
2025-08-14T21:49:22.9138975Z nn/test_pruning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pruning_1.1_4ec7aff167d06293_.log
2025-08-14T21:49:22.9139785Z Running 0 items in this shard:
2025-08-14T21:49:22.9139991Z 
2025-08-14T21:49:22.9142140Z Running test_itt 1/1 ... [2025-08-14 21:49:22.914048]
2025-08-14T21:49:22.9142578Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:22.9146025Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_itt.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:22.914380]
2025-08-14T21:49:26.0830400Z 
2025-08-14T21:49:26.0831332Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_2dff8c6c34109644_.log
2025-08-14T21:49:26.0832380Z Running 0 items in this shard:
2025-08-14T21:49:26.0832572Z 
2025-08-14T21:49:26.0834457Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-08-14 21:49:26.083279]
2025-08-14T21:49:26.0834952Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:26.0838261Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:26.083605]
2025-08-14T21:49:29.4022742Z 
2025-08-14T21:49:29.4023804Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_32c783a222ded1a8_.log
2025-08-14T21:49:29.4024736Z Running 0 items in this shard:
2025-08-14T21:49:29.4024965Z 
2025-08-14T21:49:29.4026817Z Running test_sympy_utils 1/1 ... [2025-08-14 21:49:29.402526]
2025-08-14T21:49:29.4027248Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:29.4030677Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:29.402845]
2025-08-14T21:49:32.6715368Z 
2025-08-14T21:49:32.6716282Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_f2c829d4f1fd4dc0_.log
2025-08-14T21:49:32.6717031Z Running 0 items in this shard:
2025-08-14T21:49:32.6717237Z 
2025-08-14T21:49:32.6718986Z Running torch_np/test_indexing 1/1 ... [2025-08-14 21:49:32.671734]
2025-08-14T21:49:32.6719424Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:32.6722858Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:32.672062]
2025-08-14T21:49:35.8908788Z 
2025-08-14T21:49:35.8909843Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_2f5317e3dd448103_.log
2025-08-14T21:49:35.8910648Z Running 0 items in this shard:
2025-08-14T21:49:35.8913918Z 
2025-08-14T21:49:35.8914321Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-08-14 21:49:35.891172]
2025-08-14T21:49:35.8914854Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:35.8917397Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:35.891521]
2025-08-14T21:49:39.2103453Z 
2025-08-14T21:49:39.2104974Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_5be21d38a7efe197_.log
2025-08-14T21:49:39.2105967Z Running 0 items in this shard:
2025-08-14T21:49:39.2106160Z 
2025-08-14T21:49:39.2108036Z Running test_jit 1/1 ... [2025-08-14 21:49:39.210630]
2025-08-14T21:49:39.2108731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:39.2112343Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:39.211021]
2025-08-14T21:49:44.2433881Z 
2025-08-14T21:49:44.2434648Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_b74f028a20b887c1_.log
2025-08-14T21:49:44.2435547Z Running 0 items in this shard:
2025-08-14T21:49:44.2435739Z 
2025-08-14T21:49:44.2438358Z Running nn/test_packed_sequence 1/1 ... [2025-08-14 21:49:44.243670]
2025-08-14T21:49:44.2438787Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:44.2442204Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:44.244014]
2025-08-14T21:49:47.4126329Z 
2025-08-14T21:49:47.4127244Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_cbcd9820143adeb7_.log
2025-08-14T21:49:47.4128052Z Running 0 items in this shard:
2025-08-14T21:49:47.4128246Z 
2025-08-14T21:49:47.4130832Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-08-14 21:49:47.412895]
2025-08-14T21:49:47.4131514Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:47.4134262Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:47.413194]
2025-08-14T21:49:50.6317615Z 
2025-08-14T21:49:50.6318966Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_a713de628057d971_.log
2025-08-14T21:49:50.6320239Z Running 0 items in this shard:
2025-08-14T21:49:50.6320493Z 
2025-08-14T21:49:50.6321820Z Running functorch/test_ops 1/8 ... [2025-08-14 21:49:50.632004]
2025-08-14T21:49:50.6322235Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:50.6325902Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:50.632345]
2025-08-14T21:49:57.0050997Z 
2025-08-14T21:49:57.0051877Z functorch/test_ops 1/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_1.8_c82ffa744ee598bd_.log
2025-08-14T21:49:57.0052864Z Running 0 items in this shard:
2025-08-14T21:49:57.0053060Z 
2025-08-14T21:49:57.0055251Z Running functorch/test_ops 5/8 ... [2025-08-14 21:49:57.005351]
2025-08-14T21:49:57.0055741Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:49:57.0059082Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'serial', '--shard-id=5', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:49:57.005696]
2025-08-14T21:50:03.4288799Z 
2025-08-14T21:50:03.4290021Z functorch/test_ops 5/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_5.8_6b3eda528db070f7_.log
2025-08-14T21:50:03.4290796Z Running 0 items in this shard:
2025-08-14T21:50:03.4291001Z 
2025-08-14T21:50:03.4293202Z Running functorch/test_ops 6/8 ... [2025-08-14 21:50:03.429153]
2025-08-14T21:50:03.4293887Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:03.4297658Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'serial', '--shard-id=6', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:03.429501]
2025-08-14T21:50:09.7525458Z 
2025-08-14T21:50:09.7526769Z functorch/test_ops 6/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_6.8_cf6ea08d0023c59a_.log
2025-08-14T21:50:09.7527872Z Running 0 items in this shard:
2025-08-14T21:50:09.7528095Z 
2025-08-14T21:50:09.7529258Z Running functorch/test_ops 7/8 ... [2025-08-14 21:50:09.752736]
2025-08-14T21:50:09.7529915Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:09.7533365Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'serial', '--shard-id=7', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:09.753078]
2025-08-14T21:50:16.0759746Z 
2025-08-14T21:50:16.0761050Z functorch/test_ops 7/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_7.8_e1da095d14bd4461_.log
2025-08-14T21:50:16.0761819Z Running 0 items in this shard:
2025-08-14T21:50:16.0762014Z 
2025-08-14T21:50:16.0764109Z Running functorch/test_aotdispatch 3/6 ... [2025-08-14 21:50:16.076221]
2025-08-14T21:50:16.0764737Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:16.0768224Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=3', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:16.076576]
2025-08-14T21:50:21.2475220Z 
2025-08-14T21:50:21.2476431Z functorch/test_aotdispatch 3/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_3.6_869ab3067871f427_.log
2025-08-14T21:50:21.2477703Z Running 0 items in this shard:
2025-08-14T21:50:21.2478123Z 
2025-08-14T21:50:21.2480410Z Running functorch/test_aotdispatch 4/6 ... [2025-08-14 21:50:21.247851]
2025-08-14T21:50:21.2480878Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:21.2484306Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=4', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:21.248186]
2025-08-14T21:50:26.4196067Z 
2025-08-14T21:50:26.4197030Z functorch/test_aotdispatch 4/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_4.6_2ee55227b5a56b3e_.log
2025-08-14T21:50:26.4197873Z Running 0 items in this shard:
2025-08-14T21:50:26.4198089Z 
2025-08-14T21:50:26.8282781Z Uploading artifacts took 0.41 seconds
2025-08-14T21:50:26.8286095Z Running functorch/test_aotdispatch 5/6 ... [2025-08-14 21:50:26.828395]
2025-08-14T21:50:26.8286596Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:26.8290086Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=5', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:26.828756]
2025-08-14T21:50:31.9999867Z 
2025-08-14T21:50:32.0001003Z functorch/test_aotdispatch 5/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_5.6_5d258fcc29b74591_.log
2025-08-14T21:50:32.0001864Z Running 0 items in this shard:
2025-08-14T21:50:32.0002058Z 
2025-08-14T21:50:32.0004026Z Running optim/test_swa_utils 1/1 ... [2025-08-14 21:50:32.000232]
2025-08-14T21:50:32.0004460Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:32.0008009Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:32.000580]
2025-08-14T21:50:35.0270821Z 
2025-08-14T21:50:35.0272001Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_d1f26c8dcf7250e8_.log
2025-08-14T21:50:35.0272742Z 
2025-08-14T21:50:35.0274967Z Running functorch/test_vmap 2/2 ... [2025-08-14 21:50:35.027329]
2025-08-14T21:50:35.0275414Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:35.0279164Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:35.027708]
2025-08-14T21:50:39.7986066Z 
2025-08-14T21:50:39.7987230Z functorch/test_vmap 2/2 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_2.2_853a6fb1be14297f_.log
2025-08-14T21:50:39.7988038Z Running 0 items in this shard:
2025-08-14T21:50:39.7988233Z 
2025-08-14T21:50:39.7989921Z Running nn/test_load_state_dict 1/1 ... [2025-08-14 21:50:39.798804]
2025-08-14T21:50:39.7990363Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:39.7994388Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:39.799178]
2025-08-14T21:50:42.9679342Z 
2025-08-14T21:50:42.9680244Z nn/test_load_state_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_load_state_dict_1.1_d4057b19f200fa6e_.log
2025-08-14T21:50:42.9681045Z Running 0 items in this shard:
2025-08-14T21:50:42.9681234Z 
2025-08-14T21:50:42.9683443Z Running test_shape_ops 1/1 ... [2025-08-14 21:50:42.968197]
2025-08-14T21:50:42.9683904Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:42.9687580Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_shape_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:42.968560]
2025-08-14T21:50:46.2374312Z 
2025-08-14T21:50:46.2375891Z test_shape_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_shape_ops_1.1_29cfbac54b4d73cc_.log
2025-08-14T21:50:46.2377233Z Running 0 items in this shard:
2025-08-14T21:50:46.2377555Z 
2025-08-14T21:50:46.2380107Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-08-14 21:50:46.237801]
2025-08-14T21:50:46.2380900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:46.2385727Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:46.238228]
2025-08-14T21:50:49.4572521Z 
2025-08-14T21:50:49.4573768Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_e676adc5e8b5c5e2_.log
2025-08-14T21:50:49.4574852Z Running 0 items in this shard:
2025-08-14T21:50:49.4575048Z 
2025-08-14T21:50:49.4575337Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-08-14 21:50:49.457239]
2025-08-14T21:50:49.4575856Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:49.4578319Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:49.457589]
2025-08-14T21:50:52.6762009Z 
2025-08-14T21:50:52.6763117Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_dfa79f277c501121_.log
2025-08-14T21:50:52.6764131Z Running 0 items in this shard:
2025-08-14T21:50:52.6764396Z 
2025-08-14T21:50:52.6765885Z Running test_type_info 1/1 ... [2025-08-14 21:50:52.676417]
2025-08-14T21:50:52.6766525Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:52.6769727Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_info.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:52.676768]
2025-08-14T21:50:55.8953638Z 
2025-08-14T21:50:55.8954893Z test_type_info 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_info_1.1_6d72c82f6c0b093e_.log
2025-08-14T21:50:55.8955625Z Running 0 items in this shard:
2025-08-14T21:50:55.8955831Z 
2025-08-14T21:50:55.8957795Z Running test_dataloader 1/1 ... [2025-08-14 21:50:55.895603]
2025-08-14T21:50:55.8958489Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:55.8961831Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dataloader.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:55.895933]
2025-08-14T21:50:59.1646164Z 
2025-08-14T21:50:59.1647082Z test_dataloader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dataloader_1.1_7a1412b6c7899590_.log
2025-08-14T21:50:59.1647872Z Running 0 items in this shard:
2025-08-14T21:50:59.1648063Z 
2025-08-14T21:50:59.1650438Z Running test_jit_llga_fuser 1/1 ... [2025-08-14 21:50:59.164876]
2025-08-14T21:50:59.1650930Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:50:59.1654434Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_llga_fuser.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:50:59.165235]
2025-08-14T21:51:02.5843061Z 
2025-08-14T21:51:02.5844281Z test_jit_llga_fuser 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_llga_fuser_1.1_e29933b5566fc6c3_.log
2025-08-14T21:51:02.5845303Z Running 0 items in this shard:
2025-08-14T21:51:02.5846322Z 
2025-08-14T21:51:02.5846736Z Running torch_np/test_function_base 1/1 ... [2025-08-14 21:51:02.584497]
2025-08-14T21:51:02.5847399Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:02.5850867Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_function_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:02.584813]
2025-08-14T21:51:05.7532366Z 
2025-08-14T21:51:05.7533642Z torch_np/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_function_base_1.1_72dfde232bcc2191_.log
2025-08-14T21:51:05.7534482Z Running 0 items in this shard:
2025-08-14T21:51:05.7534689Z 
2025-08-14T21:51:05.7536225Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-08-14 21:51:05.753445]
2025-08-14T21:51:05.7536915Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:05.7539979Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:05.753750]
2025-08-14T21:51:08.9724159Z 
2025-08-14T21:51:08.9725581Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_563eb80f93344127_.log
2025-08-14T21:51:08.9726789Z Running 0 items in this shard:
2025-08-14T21:51:08.9726998Z 
2025-08-14T21:51:08.9728312Z Running torch_np/test_scalars_0D_arrays 1/1 ... [2025-08-14 21:51:08.972650]
2025-08-14T21:51:08.9728784Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:08.9732382Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_scalars_0D_arrays.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:08.973013]
2025-08-14T21:51:12.1917710Z 
2025-08-14T21:51:12.1918695Z torch_np/test_scalars_0D_arrays 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_scalars_0D_arrays_1.1_c7b6af5097ef13b6_.log
2025-08-14T21:51:12.1919595Z Running 0 items in this shard:
2025-08-14T21:51:12.1919795Z 
2025-08-14T21:51:12.1921567Z Running nn/test_module_hooks 1/1 ... [2025-08-14 21:51:12.192006]
2025-08-14T21:51:12.1921994Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:12.1925547Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_module_hooks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:12.192336]
2025-08-14T21:51:15.4110347Z 
2025-08-14T21:51:15.4111337Z nn/test_module_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_module_hooks_1.1_fd59a723db6752e5_.log
2025-08-14T21:51:15.4112292Z Running 0 items in this shard:
2025-08-14T21:51:15.4112486Z 
2025-08-14T21:51:15.4114474Z Running test_numa_binding 1/1 ... [2025-08-14 21:51:15.411286]
2025-08-14T21:51:15.4114900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:15.4118581Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numa_binding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:15.411619]
2025-08-14T21:51:18.5803826Z 
2025-08-14T21:51:18.5804781Z test_numa_binding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numa_binding_1.1_6e69ed1024228674_.log
2025-08-14T21:51:18.5805628Z Running 0 items in this shard:
2025-08-14T21:51:18.5805830Z 
2025-08-14T21:51:18.5808174Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-08-14 21:51:18.580609]
2025-08-14T21:51:18.5808717Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:18.5812240Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:18.580984]
2025-08-14T21:51:21.7996140Z 
2025-08-14T21:51:21.7997247Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_6a14074c747d8848_.log
2025-08-14T21:51:21.7998217Z Running 0 items in this shard:
2025-08-14T21:51:21.7998408Z 
2025-08-14T21:51:21.8001002Z Running torch_np/test_ndarray_methods 1/1 ... [2025-08-14 21:51:21.799932]
2025-08-14T21:51:21.8001500Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:21.8005046Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:21.800292]
2025-08-14T21:51:25.0190157Z 
2025-08-14T21:51:25.0191163Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_58e594a16de8f644_.log
2025-08-14T21:51:25.0192326Z Running 0 items in this shard:
2025-08-14T21:51:25.0192516Z 
2025-08-14T21:51:25.0194742Z Running lazy/test_debug_util 1/1 ... [2025-08-14 21:51:25.019307]
2025-08-14T21:51:25.0195174Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:25.0198909Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:25.019678]
2025-08-14T21:51:28.2382857Z 
2025-08-14T21:51:28.2383679Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_b788b6d5609b966d_.log
2025-08-14T21:51:28.2384463Z Running 0 items in this shard:
2025-08-14T21:51:28.2384655Z 
2025-08-14T21:51:28.2387026Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-08-14 21:51:28.238525]
2025-08-14T21:51:28.2387608Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:28.2390740Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:28.238851]
2025-08-14T21:51:31.4574381Z 
2025-08-14T21:51:31.4575490Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_368eb0cacffda660_.log
2025-08-14T21:51:31.4576439Z Running 0 items in this shard:
2025-08-14T21:51:31.4576649Z 
2025-08-14T21:51:31.4578064Z Running torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-08-14 21:51:31.457656]
2025-08-14T21:51:31.4578592Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:31.4582064Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/linalg/test_linalg.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:31.457983]
2025-08-14T21:51:34.7767324Z 
2025-08-14T21:51:34.7768389Z torch_np/numpy_tests/linalg/test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.linalg.test_linalg_1.1_c0d7b6db5733c25d_.log
2025-08-14T21:51:34.7769576Z Running 0 items in this shard:
2025-08-14T21:51:34.7769770Z 
2025-08-14T21:51:34.7771358Z Running test_sparse_csr 1/1 ... [2025-08-14 21:51:34.776973]
2025-08-14T21:51:34.7771812Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:34.7775628Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_csr.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:34.777316]
2025-08-14T21:51:40.0487425Z 
2025-08-14T21:51:40.0488314Z test_sparse_csr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_csr_1.1_5870219c2abbc4dd_.log
2025-08-14T21:51:40.0489055Z Running 0 items in this shard:
2025-08-14T21:51:40.0489249Z 
2025-08-14T21:51:40.0491144Z Running test_view_ops 1/1 ... [2025-08-14 21:51:40.048953]
2025-08-14T21:51:40.0491556Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:40.0494851Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_view_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:40.049288]
2025-08-14T21:51:43.4183367Z 
2025-08-14T21:51:43.4184234Z test_view_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_view_ops_1.1_30293bf1dd3a8eed_.log
2025-08-14T21:51:43.4185199Z Running 0 items in this shard:
2025-08-14T21:51:43.4185392Z 
2025-08-14T21:51:43.4187712Z Running test_accelerator 1/1 ... [2025-08-14 21:51:43.418603]
2025-08-14T21:51:43.4188125Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:43.4191950Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_accelerator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:43.418967]
2025-08-14T21:51:46.4301407Z 
2025-08-14T21:51:46.4302305Z test_accelerator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_accelerator_1.1_59040fe0a05cab0c_.log
2025-08-14T21:51:46.4302933Z 
2025-08-14T21:51:46.4305557Z Running profiler/test_memory_profiler 1/1 ... [2025-08-14 21:51:46.430392]
2025-08-14T21:51:46.4306061Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:46.4309792Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_memory_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:46.430745]
2025-08-14T21:51:49.6496014Z 
2025-08-14T21:51:49.6497010Z profiler/test_memory_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_memory_profiler_1.1_75b5cafc706ab1b8_.log
2025-08-14T21:51:49.6497905Z Running 0 items in this shard:
2025-08-14T21:51:49.6498112Z 
2025-08-14T21:51:49.6500134Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-08-14 21:51:49.649824]
2025-08-14T21:51:49.6500657Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:49.6504116Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:49.650177]
2025-08-14T21:51:52.8688293Z 
2025-08-14T21:51:52.8689342Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_fe4c52510a6a8419_.log
2025-08-14T21:51:52.8690285Z Running 0 items in this shard:
2025-08-14T21:51:52.8690511Z 
2025-08-14T21:51:52.8692456Z Running test_function_schema 1/1 ... [2025-08-14 21:51:52.869088]
2025-08-14T21:51:52.8693138Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:52.8696591Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_function_schema.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:52.869441]
2025-08-14T21:51:56.0380654Z 
2025-08-14T21:51:56.0381752Z test_function_schema 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_function_schema_1.1_e9eb1031f42fe68d_.log
2025-08-14T21:51:56.0382567Z Running 0 items in this shard:
2025-08-14T21:51:56.0382760Z 
2025-08-14T21:51:56.0385153Z Running torch_np/numpy_tests/lib/test_index_tricks 1/1 ... [2025-08-14 21:51:56.038337]
2025-08-14T21:51:56.0385748Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:56.0389508Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_index_tricks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:56.038690]
2025-08-14T21:51:59.2573242Z 
2025-08-14T21:51:59.2575173Z torch_np/numpy_tests/lib/test_index_tricks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_index_tricks_1.1_ce233d67da6e4a9c_.log
2025-08-14T21:51:59.2576939Z Running 0 items in this shard:
2025-08-14T21:51:59.2577490Z 
2025-08-14T21:51:59.2579342Z Running test_scatter_gather_ops 1/1 ... [2025-08-14 21:51:59.257741]
2025-08-14T21:51:59.2580029Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:51:59.2584725Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_scatter_gather_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:51:59.258153]
2025-08-14T21:52:02.5268659Z 
2025-08-14T21:52:02.5270100Z test_scatter_gather_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_scatter_gather_ops_1.1_332115ba78896232_.log
2025-08-14T21:52:02.5271405Z Running 0 items in this shard:
2025-08-14T21:52:02.5271816Z 
2025-08-14T21:52:02.5272984Z Running test_serialization 1/1 ... [2025-08-14 21:52:02.527117]
2025-08-14T21:52:02.5273678Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:02.5279033Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_serialization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:02.527577]
2025-08-14T21:52:26.1274565Z 
2025-08-14T21:52:26.1275503Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_269c3f6b53306ecf_.log
2025-08-14T21:52:26.1277040Z Running 2 items in this shard: test/test_serialization.py::TestSerialization::test_serialization_2gb_file, test/test_serialization.py::TestSerialization::test_serialization_4gb_file
2025-08-14T21:52:26.1288406Z 
2025-08-14T21:52:26.1288867Z Running torch_np/numpy_tests/core/test_dlpack 1/1 ... [2025-08-14 21:52:26.126664]
2025-08-14T21:52:26.1289607Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:26.1291311Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dlpack.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:26.128451]
2025-08-14T21:52:31.4050746Z 
2025-08-14T21:52:31.4052126Z torch_np/numpy_tests/core/test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dlpack_1.1_007bd76ee6ca4949_.log
2025-08-14T21:52:31.4053099Z Running 0 items in this shard:
2025-08-14T21:52:31.4053307Z 
2025-08-14T21:52:31.4055573Z Running test_xnnpack_integration 1/1 ... [2025-08-14 21:52:31.405314]
2025-08-14T21:52:31.4056072Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:31.4059171Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_xnnpack_integration.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:31.405645]
2025-08-14T21:52:34.6241427Z 
2025-08-14T21:52:34.6242543Z test_xnnpack_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_xnnpack_integration_1.1_c278d059cc8a75c8_.log
2025-08-14T21:52:34.6243605Z Running 0 items in this shard:
2025-08-14T21:52:34.6244000Z 
2025-08-14T21:52:34.6246976Z Running torch_np/numpy_tests/fft/test_helper 1/1 ... [2025-08-14 21:52:34.624475]
2025-08-14T21:52:34.6247649Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:34.6251063Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_helper.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:34.624836]
2025-08-14T21:52:37.8434601Z 
2025-08-14T21:52:37.8435941Z torch_np/numpy_tests/fft/test_helper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_helper_1.1_68f438ce8c19963f_.log
2025-08-14T21:52:37.8437108Z Running 0 items in this shard:
2025-08-14T21:52:37.8437349Z 
2025-08-14T21:52:37.8438551Z Running test_mkldnn 1/1 ... [2025-08-14 21:52:37.843656]
2025-08-14T21:52:37.8439192Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:37.8442443Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:37.843989]
2025-08-14T21:52:41.4633479Z 
2025-08-14T21:52:41.4634842Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_6135fd160e937ed3_.log
2025-08-14T21:52:41.4635649Z Running 0 items in this shard:
2025-08-14T21:52:41.4635863Z 
2025-08-14T21:52:41.4638336Z Running test_unary_ufuncs 1/1 ... [2025-08-14 21:52:41.463644]
2025-08-14T21:52:41.4638773Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:41.4642197Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_unary_ufuncs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:41.464002]
2025-08-14T21:52:50.0464163Z 
2025-08-14T21:52:50.0465117Z test_unary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_unary_ufuncs_1.1_9dbeedcd87f7afa9_.log
2025-08-14T21:52:50.0466090Z Running 0 items in this shard:
2025-08-14T21:52:50.0466290Z 
2025-08-14T21:52:50.0466713Z Running test_jit_autocast 1/1 ... [2025-08-14 21:52:50.046512]
2025-08-14T21:52:50.0467119Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:50.0470787Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_autocast.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:50.046858]
2025-08-14T21:52:54.9208781Z 
2025-08-14T21:52:54.9209829Z test_jit_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_autocast_1.1_2d09b733b6396adc_.log
2025-08-14T21:52:54.9210597Z Running 0 items in this shard:
2025-08-14T21:52:54.9210793Z 
2025-08-14T21:52:54.9213165Z Running test_dlpack 1/1 ... [2025-08-14 21:52:54.921153]
2025-08-14T21:52:54.9213574Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:54.9217041Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dlpack.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:54.921488]
2025-08-14T21:52:58.1417013Z 
2025-08-14T21:52:58.1418638Z test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dlpack_1.1_e44f99db041d10cb_.log
2025-08-14T21:52:58.1419927Z Running 0 items in this shard:
2025-08-14T21:52:58.1420225Z 
2025-08-14T21:52:58.1422577Z Running profiler/test_profiler_tree 1/1 ... [2025-08-14 21:52:58.142038]
2025-08-14T21:52:58.1423311Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:52:58.1427986Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler_tree.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:52:58.142463]
2025-08-14T21:53:01.3112685Z 
2025-08-14T21:53:01.3114184Z profiler/test_profiler_tree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_tree_1.1_eeba5625a5d725df_.log
2025-08-14T21:53:01.3115749Z Running 0 items in this shard:
2025-08-14T21:53:01.3116103Z 
2025-08-14T21:53:01.3119161Z Running torch_np/numpy_tests/core/test_scalar_ctors 1/1 ... [2025-08-14 21:53:01.311681]
2025-08-14T21:53:01.3120284Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:01.3124093Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalar_ctors.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:01.312098]
2025-08-14T21:53:04.5811775Z 
2025-08-14T21:53:04.5813346Z torch_np/numpy_tests/core/test_scalar_ctors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalar_ctors_1.1_0999f5fec2f0d1f3_.log
2025-08-14T21:53:04.5814345Z Running 0 items in this shard:
2025-08-14T21:53:04.5814543Z 
2025-08-14T21:53:04.5816135Z Running profiler/test_torch_tidy 1/1 ... [2025-08-14 21:53:04.581428]
2025-08-14T21:53:04.5816591Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:04.5820027Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_torch_tidy.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:04.581766]
2025-08-14T21:53:07.8004524Z 
2025-08-14T21:53:07.8005765Z profiler/test_torch_tidy 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_torch_tidy_1.1_56c818fba8401a56_.log
2025-08-14T21:53:07.8006622Z Running 0 items in this shard:
2025-08-14T21:53:07.8006886Z 
2025-08-14T21:53:07.8007910Z Running torch_np/test_reductions 1/1 ... [2025-08-14 21:53:07.800630]
2025-08-14T21:53:07.8008552Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:07.8012266Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:07.800977]
2025-08-14T21:53:11.0696702Z 
2025-08-14T21:53:11.0697923Z torch_np/test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_reductions_1.1_b37092eb7bb341f9_.log
2025-08-14T21:53:11.0698758Z Running 0 items in this shard:
2025-08-14T21:53:11.0698969Z 
2025-08-14T21:53:11.0700841Z Running lazy/test_reuse_ir 1/1 ... [2025-08-14 21:53:11.069890]
2025-08-14T21:53:11.0701465Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:11.0704776Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_reuse_ir.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:11.070214]
2025-08-14T21:53:14.2887579Z 
2025-08-14T21:53:14.2888948Z lazy/test_reuse_ir 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_reuse_ir_1.1_ea1992245e3ce615_.log
2025-08-14T21:53:14.2889741Z Running 0 items in this shard:
2025-08-14T21:53:14.2889944Z 
2025-08-14T21:53:14.2891981Z Running test_functional_autograd_benchmark 1/1 ... [2025-08-14 21:53:14.289004]
2025-08-14T21:53:14.2892530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:14.2895820Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_functional_autograd_benchmark.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:14.289319]
2025-08-14T21:53:17.5079421Z 
2025-08-14T21:53:17.5080742Z test_functional_autograd_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functional_autograd_benchmark_1.1_d92993704becb8bd_.log
2025-08-14T21:53:17.5081666Z Running 0 items in this shard:
2025-08-14T21:53:17.5081861Z 
2025-08-14T21:53:17.5083714Z Running test_prims 1/1 ... [2025-08-14 21:53:17.508186]
2025-08-14T21:53:17.5084388Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:17.5087811Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_prims.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:17.508522]
2025-08-14T21:53:21.7284147Z 
2025-08-14T21:53:21.7285237Z test_prims 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_prims_1.1_90b2d48464481fa6_.log
2025-08-14T21:53:21.7286161Z Running 0 items in this shard:
2025-08-14T21:53:21.7286355Z 
2025-08-14T21:53:21.7288302Z Running profiler/test_python_tracer 1/1 ... [2025-08-14 21:53:21.728647]
2025-08-14T21:53:21.7288945Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:21.7292666Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_python_tracer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:21.729013]
2025-08-14T21:53:24.8981466Z 
2025-08-14T21:53:24.8982507Z profiler/test_python_tracer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_python_tracer_1.1_5db537cf52dd183e_.log
2025-08-14T21:53:24.8983491Z Running 0 items in this shard:
2025-08-14T21:53:24.8983706Z 
2025-08-14T21:53:27.4967000Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:27.4969902Z   import pkg_resources
2025-08-14T21:53:27.5027090Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:27.5028635Z   import pkg_resources
2025-08-14T21:53:27.5447244Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:27.5448987Z   import pkg_resources
2025-08-14T21:53:27.8779663Z Running inductor/test_cudagraph_trees 1/1 ... [2025-08-14 21:53:27.877545]
2025-08-14T21:53:27.8780273Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:27.8782606Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cudagraph_trees.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:27.877929]
2025-08-14T21:53:27.8796525Z Running dynamo/test_repros 1/1 ... [2025-08-14 21:53:27.879410]
2025-08-14T21:53:27.8797196Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:27.8798018Z Running inductor/test_compiled_optimizers 1/1 ... [2025-08-14 21:53:27.879617]
2025-08-14T21:53:27.8799679Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:27.8801816Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_repros.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:27.879791]
2025-08-14T21:53:27.8804534Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compiled_optimizers.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:27.880001]
2025-08-14T21:53:31.4716893Z 
2025-08-14T21:53:31.4718034Z dynamo/test_repros 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_repros_1.1_a4744ad7ba6dcc3d_.log
2025-08-14T21:53:31.4718715Z 
2025-08-14T21:53:34.8697451Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:34.8700604Z   import pkg_resources
2025-08-14T21:53:34.9957561Z Running dynamo/test_logging 1/1 ... [2025-08-14 21:53:34.995351]
2025-08-14T21:53:34.9958317Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:34.9961125Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:34.995760]
2025-08-14T21:53:35.6445058Z 
2025-08-14T21:53:35.6446158Z inductor/test_cudagraph_trees 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_1.1_307e15f36f411d46_.log
2025-08-14T21:53:35.6447016Z 
2025-08-14T21:53:37.7836241Z 
2025-08-14T21:53:37.7837911Z inductor/test_compiled_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_optimizers_1.1_df0f68c6d9536968_.log
2025-08-14T21:53:37.7839374Z 
2025-08-14T21:53:38.9556527Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:38.9559330Z   import pkg_resources
2025-08-14T21:53:39.1025104Z Running inductor/test_triton_kernels 1/1 ... [2025-08-14 21:53:39.102111]
2025-08-14T21:53:39.1025974Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:39.1027678Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_triton_kernels.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:39.102487]
2025-08-14T21:53:41.1127025Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:41.1128587Z   import pkg_resources
2025-08-14T21:53:41.2404224Z Running inductor/test_torchbind 1/1 ... [2025-08-14 21:53:41.239889]
2025-08-14T21:53:41.2405072Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:41.2410508Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchbind.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:41.240334]
2025-08-14T21:53:42.1327713Z 
2025-08-14T21:53:42.1329118Z dynamo/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_logging_1.1_46162de053514ce0_.log
2025-08-14T21:53:42.1330341Z 
2025-08-14T21:53:45.4371759Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:45.4375143Z   import pkg_resources
2025-08-14T21:53:45.5630299Z Running inductor/test_aot_inductor_package 1/1 ... [2025-08-14 21:53:45.562635]
2025-08-14T21:53:45.5630973Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:45.5633008Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:45.563003]
2025-08-14T21:53:46.4604851Z 
2025-08-14T21:53:46.4606085Z inductor/test_triton_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_kernels_1.1_250af7d55b62aa18_.log
2025-08-14T21:53:46.4606928Z 
2025-08-14T21:53:48.6485985Z 
2025-08-14T21:53:48.6487375Z inductor/test_torchbind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchbind_1.1_c3744911aea94e3f_.log
2025-08-14T21:53:48.6488205Z 
2025-08-14T21:53:49.7847208Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:49.7848888Z   import pkg_resources
2025-08-14T21:53:49.9348860Z Running dynamo/test_utils 1/1 ... [2025-08-14 21:53:49.934504]
2025-08-14T21:53:49.9349709Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:49.9357774Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:49.935411]
2025-08-14T21:53:52.0863925Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:52.0866757Z   import pkg_resources
2025-08-14T21:53:52.2121562Z Running dynamo/test_error_messages 1/1 ... [2025-08-14 21:53:52.211713]
2025-08-14T21:53:52.2122551Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:52.2125040Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_error_messages.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:52.212109]
2025-08-14T21:53:52.8555741Z 
2025-08-14T21:53:52.8557222Z inductor/test_aot_inductor_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_package_1.1_715e2c155a1c2a76_.log
2025-08-14T21:53:52.8558363Z 
2025-08-14T21:53:53.2485439Z 
2025-08-14T21:53:53.2486742Z dynamo/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_utils_1.1_505b6a4103afd968_.log
2025-08-14T21:53:53.2487392Z 
2025-08-14T21:53:55.7965726Z 
2025-08-14T21:53:55.7966718Z dynamo/test_error_messages 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_error_messages_1.1_cacfc2594b0d3663_.log
2025-08-14T21:53:55.7967481Z 
2025-08-14T21:53:56.1206824Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:56.1209216Z   import pkg_resources
2025-08-14T21:53:56.2471382Z Running dynamo/test_exceptions 1/1 ... [2025-08-14 21:53:56.246764]
2025-08-14T21:53:56.2472626Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:56.2475302Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_exceptions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:56.247197]
2025-08-14T21:53:56.5781923Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:56.5784986Z   import pkg_resources
2025-08-14T21:53:56.7226829Z Running dynamo/test_structured_trace 1/1 ... [2025-08-14 21:53:56.722231]
2025-08-14T21:53:56.7227757Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:56.7229838Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_structured_trace.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:56.722593]
2025-08-14T21:53:59.1813627Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:53:59.1815186Z   import pkg_resources
2025-08-14T21:53:59.3087319Z Running inductor/test_cudagraph_trees_expandable_segments 1/1 ... [2025-08-14 21:53:59.308320]
2025-08-14T21:53:59.3088467Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:53:59.3090952Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cudagraph_trees_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:53:59.308691]
2025-08-14T21:53:59.7621421Z 
2025-08-14T21:53:59.7622791Z dynamo/test_exceptions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_exceptions_1.1_696df1305be80a8f_.log
2025-08-14T21:54:03.1417048Z 
2025-08-14T21:54:03.1419301Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:03.1420869Z   import pkg_resources
2025-08-14T21:54:03.2766942Z Running test_ops 6/8 ... [2025-08-14 21:54:03.276290]
2025-08-14T21:54:03.2767941Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:03.2769924Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'not serial', '--shard-id=6', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:03.276655]
2025-08-14T21:54:03.8703455Z 
2025-08-14T21:54:03.8704768Z dynamo/test_structured_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_structured_trace_1.1_c1736e25522afdf2_.log
2025-08-14T21:54:03.8706264Z 
2025-08-14T21:54:06.7303345Z 
2025-08-14T21:54:06.7305181Z inductor/test_cudagraph_trees_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_expandable_segments_1.1_1cf3c3439e62d145_.log
2025-08-14T21:54:06.7306174Z 
2025-08-14T21:54:07.1836706Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:07.1838500Z   import pkg_resources
2025-08-14T21:54:07.3105969Z Running inductor/test_torchinductor 1/1 ... [2025-08-14 21:54:07.310211]
2025-08-14T21:54:07.3106568Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:07.3108925Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:07.310590]
2025-08-14T21:54:10.0326589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:10.0329501Z   import pkg_resources
2025-08-14T21:54:10.1571073Z Running inductor/test_torchinductor_codegen_dynamic_shapes 1/1 ... [2025-08-14 21:54:10.156666]
2025-08-14T21:54:10.1572125Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:10.1574348Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_codegen_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:10.157053]
2025-08-14T21:54:15.0687752Z 
2025-08-14T21:54:15.0688993Z inductor/test_torchinductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_1.1_b04e4dd10db9cb4f_.log
2025-08-14T21:54:15.0689751Z 
2025-08-14T21:54:17.9800152Z 
2025-08-14T21:54:17.9801964Z inductor/test_torchinductor_codegen_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_dynamic_shapes_1.1_c2f83eb57f5003a4_.log
2025-08-14T21:54:17.9803667Z 
2025-08-14T21:54:18.3821556Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:18.3825390Z   import pkg_resources
2025-08-14T21:54:18.5087565Z Running inductor/test_cpu_repro 1/1 ... [2025-08-14 21:54:18.508320]
2025-08-14T21:54:18.5088407Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:18.5091230Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_repro.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:18.508675]
2025-08-14T21:54:21.2824009Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:21.2826838Z   import pkg_resources
2025-08-14T21:54:21.4075815Z Running inductor/test_kernel_benchmark 1/1 ... [2025-08-14 21:54:21.407196]
2025-08-14T21:54:21.4076670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:21.4079726Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_kernel_benchmark.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:21.407615]
2025-08-14T21:54:26.0708563Z 
2025-08-14T21:54:26.0710344Z inductor/test_cpu_repro 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_repro_1.1_3f071722763a693c_.log
2025-08-14T21:54:26.0711550Z 
2025-08-14T21:54:28.5696748Z 
2025-08-14T21:54:28.5698362Z inductor/test_kernel_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_benchmark_1.1_7a236d27c2d747d0_.log
2025-08-14T21:54:28.5700132Z 
2025-08-14T21:54:29.3249030Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:29.3251926Z   import pkg_resources
2025-08-14T21:54:29.4500953Z Running inductor/test_pattern_matcher 1/1 ... [2025-08-14 21:54:29.449673]
2025-08-14T21:54:29.4501787Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:29.4503966Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pattern_matcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:29.450051]
2025-08-14T21:54:31.7958753Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:31.7961709Z   import pkg_resources
2025-08-14T21:54:31.9189915Z Running inductor/test_perf 1/1 ... [2025-08-14 21:54:31.918558]
2025-08-14T21:54:31.9190747Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:31.9192941Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_perf.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:31.918928]
2025-08-14T21:54:36.6144516Z 
2025-08-14T21:54:36.6146081Z inductor/test_pattern_matcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pattern_matcher_1.1_26f2b431a14b7a08_.log
2025-08-14T21:54:36.6146962Z 
2025-08-14T21:54:39.2994481Z 
2025-08-14T21:54:39.2996160Z inductor/test_perf 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_perf_1.1_862894332b3766dd_.log
2025-08-14T21:54:39.2997448Z 
2025-08-14T21:54:39.9436692Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:39.9438271Z   import pkg_resources
2025-08-14T21:54:40.0699503Z Running dynamo/test_modules 1/1 ... [2025-08-14 21:54:40.069539]
2025-08-14T21:54:40.0700267Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:40.0702691Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:40.069942]
2025-08-14T21:54:42.5845492Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:42.7082367Z   import pkg_resources
2025-08-14T21:54:42.7083262Z Running inductor/test_coordinate_descent_tuner 1/1 ... [2025-08-14 21:54:42.707812]
2025-08-14T21:54:42.7084482Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:42.7086595Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_coordinate_descent_tuner.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:42.708195]
2025-08-14T21:54:47.2228085Z 
2025-08-14T21:54:47.2229584Z dynamo/test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_modules_1.1_a526a002a8d53460_.log
2025-08-14T21:54:47.2230792Z 
2025-08-14T21:54:50.1085745Z 
2025-08-14T21:54:50.1087238Z inductor/test_coordinate_descent_tuner 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_coordinate_descent_tuner_1.1_febd3e2156e0299a_.log
2025-08-14T21:54:50.1088337Z 
2025-08-14T21:54:50.5788729Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:50.5790304Z   import pkg_resources
2025-08-14T21:54:50.7049656Z Running inductor/test_select_algorithm 1/1 ... [2025-08-14 21:54:50.704591]
2025-08-14T21:54:50.7050318Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:50.7052394Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_select_algorithm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:50.704964]
2025-08-14T21:54:53.5118883Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:54:53.5121981Z   import pkg_resources
2025-08-14T21:54:53.6615944Z Running inductor/test_compiled_autograd 1/1 ... [2025-08-14 21:54:53.661088]
2025-08-14T21:54:53.6616875Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:54:53.6619155Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compiled_autograd.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:54:53.661448]
2025-08-14T21:54:58.3906969Z 
2025-08-14T21:54:58.3908727Z inductor/test_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_select_algorithm_1.1_1ad6b7dedc0c0c3a_.log
2025-08-14T21:54:58.3910072Z 
2025-08-14T21:55:01.7473955Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:01.7476219Z   import pkg_resources
2025-08-14T21:55:01.8782834Z Running inductor/test_group_batch_fusion 1/1 ... [2025-08-14 21:55:01.877857]
2025-08-14T21:55:01.8784560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:01.8786944Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_group_batch_fusion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:01.878285]
2025-08-14T21:55:02.8430010Z 
2025-08-14T21:55:02.8431643Z inductor/test_compiled_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_autograd_1.1_3fca9f1cf5335cd5_.log
2025-08-14T21:55:02.8432661Z 
2025-08-14T21:55:06.1372806Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:06.1376244Z   import pkg_resources
2025-08-14T21:55:06.2611603Z Running inductor/test_split_cat_fx_passes 1/1 ... [2025-08-14 21:55:06.260721]
2025-08-14T21:55:06.2612430Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:06.2615686Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_split_cat_fx_passes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:06.261194]
2025-08-14T21:55:09.4324566Z 
2025-08-14T21:55:09.4326264Z inductor/test_group_batch_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_group_batch_fusion_1.1_37570afa2c9c2827_.log
2025-08-14T21:55:09.4327812Z 
2025-08-14T21:55:12.8662141Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:12.8663714Z   import pkg_resources
2025-08-14T21:55:12.9963825Z Running inductor/test_snode_runtime 1/1 ... [2025-08-14 21:55:12.995993]
2025-08-14T21:55:12.9964332Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:12.9967033Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_snode_runtime.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:12.996421]
2025-08-14T21:55:13.7789358Z 
2025-08-14T21:55:13.7790931Z inductor/test_split_cat_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_split_cat_fx_passes_1.1_28175f83e73b5725_.log
2025-08-14T21:55:13.7791860Z 
2025-08-14T21:55:17.0653344Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:17.0656176Z   import pkg_resources
2025-08-14T21:55:17.1902879Z Running inductor/test_config 1/1 ... [2025-08-14 21:55:17.189904]
2025-08-14T21:55:17.1903668Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:17.1906458Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_config.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:17.190299]
2025-08-14T21:55:20.4192813Z 
2025-08-14T21:55:20.4194273Z inductor/test_snode_runtime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_snode_runtime_1.1_9d30cde308a51fb8_.log
2025-08-14T21:55:20.4195538Z 
2025-08-14T21:55:23.7946400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:23.7949356Z   import pkg_resources
2025-08-14T21:55:23.9208393Z Running dynamo/test_after_aot 1/1 ... [2025-08-14 21:55:23.920422]
2025-08-14T21:55:23.9209756Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:23.9211777Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:23.920826]
2025-08-14T21:55:24.7993326Z 
2025-08-14T21:55:24.7994576Z inductor/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_config_1.1_b2635f55cb8ba72a_.log
2025-08-14T21:55:24.7995327Z 
2025-08-14T21:55:27.4404248Z 
2025-08-14T21:55:27.4405618Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_fd86556f5d7fb80f_.log
2025-08-14T21:55:28.1300338Z 
2025-08-14T21:55:28.1302410Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:28.1303968Z   import pkg_resources
2025-08-14T21:55:28.2559933Z Running inductor/test_binary_folding 1/1 ... [2025-08-14 21:55:28.255600]
2025-08-14T21:55:28.2560820Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:28.2563335Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:28.255962]
2025-08-14T21:55:30.6469872Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:30.6472828Z   import pkg_resources
2025-08-14T21:55:30.7719192Z Running dynamo/test_cudagraphs 1/1 ... [2025-08-14 21:55:30.771524]
2025-08-14T21:55:30.7720020Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:30.7723071Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:30.771906]
2025-08-14T21:55:34.2232031Z 
2025-08-14T21:55:34.2233305Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_9891ad38e9f9212f_.log
2025-08-14T21:55:34.2234051Z 
2025-08-14T21:55:35.7996130Z 
2025-08-14T21:55:35.7997334Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_21f004bbdfdb1cd1_.log
2025-08-14T21:55:35.7998644Z 
2025-08-14T21:55:37.6572031Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:37.6573762Z   import pkg_resources
2025-08-14T21:55:37.8246405Z Running dynamo/test_ctx_manager 1/1 ... [2025-08-14 21:55:37.824153]
2025-08-14T21:55:37.8247168Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:37.8249482Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_ctx_manager.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:37.824582]
2025-08-14T21:55:39.2256663Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:39.2259367Z   import pkg_resources
2025-08-14T21:55:39.3524892Z Running inductor/test_control_flow 1/1 ... [2025-08-14 21:55:39.352082]
2025-08-14T21:55:39.3525745Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:39.3527770Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_control_flow.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:39.352435]
2025-08-14T21:55:45.1888618Z 
2025-08-14T21:55:45.1890459Z dynamo/test_ctx_manager 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_ctx_manager_1.1_c4d85a64e72c6344_.log
2025-08-14T21:55:45.1891727Z 
2025-08-14T21:55:47.2061657Z 
2025-08-14T21:55:47.2063080Z inductor/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_control_flow_1.1_9c77b927eb3d9827_.log
2025-08-14T21:55:47.2063832Z 
2025-08-14T21:55:48.8192114Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:48.8195036Z   import pkg_resources
2025-08-14T21:55:49.0012327Z Running inductor/test_padding 1/1 ... [2025-08-14 21:55:49.000787]
2025-08-14T21:55:49.0020637Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:49.0022865Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_padding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:49.001278]
2025-08-14T21:55:50.5804178Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:50.5805756Z   import pkg_resources
2025-08-14T21:55:50.7042563Z Running inductor/test_halide 1/1 ... [2025-08-14 21:55:50.703831]
2025-08-14T21:55:50.7043155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:55:50.7045852Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_halide.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:55:50.704239]
2025-08-14T21:55:56.5240004Z 
2025-08-14T21:55:56.5241429Z inductor/test_padding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_padding_1.1_65baebba2c2096e8_.log
2025-08-14T21:55:56.5242638Z 
2025-08-14T21:55:58.4266340Z 
2025-08-14T21:55:58.4267927Z inductor/test_halide 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_halide_1.1_d6408498693c1f1b_.log
2025-08-14T21:55:58.4269281Z 
2025-08-14T21:55:59.9926101Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:55:59.9929436Z   import pkg_resources
2025-08-14T21:56:00.1260467Z Running inductor/test_aot_inductor_custom_ops 1/1 ... [2025-08-14 21:56:00.125615]
2025-08-14T21:56:00.1261375Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:00.1263779Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_custom_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:00.125988]
2025-08-14T21:56:02.2403691Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:02.2406718Z   import pkg_resources
2025-08-14T21:56:02.4347058Z Running inductor/test_flex_decoding 1/1 ... [2025-08-14 21:56:02.434216]
2025-08-14T21:56:02.4348031Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:02.4351789Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_decoding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:02.434744]
2025-08-14T21:56:06.1746848Z 
2025-08-14T21:56:06.1748643Z inductor/test_flex_decoding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_decoding_1.1_0d06a141789d81c3_.log
2025-08-14T21:56:06.1750008Z 
2025-08-14T21:56:09.6140498Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:09.6142236Z   import pkg_resources
2025-08-14T21:56:09.7415880Z Running inductor/test_external_callables 1/1 ... [2025-08-14 21:56:09.741142]
2025-08-14T21:56:09.7416720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:09.7420166Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_external_callables.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:09.741583]
2025-08-14T21:56:10.1262214Z 
2025-08-14T21:56:10.1264274Z inductor/test_aot_inductor_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_custom_ops_1.1_0042f42943a142bf_.log
2025-08-14T21:56:10.1266080Z 
2025-08-14T21:56:13.3488670Z 
2025-08-14T21:56:13.3490817Z inductor/test_external_callables 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_external_callables_1.1_6ecb0c40b811e1f6_.log
2025-08-14T21:56:13.3492264Z 
2025-08-14T21:56:13.9217767Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:13.9220225Z   import pkg_resources
2025-08-14T21:56:14.1015341Z Running inductor/test_alignment 1/1 ... [2025-08-14 21:56:14.101059]
2025-08-14T21:56:14.1016244Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:14.1020157Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_alignment.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:14.101516]
2025-08-14T21:56:17.3668821Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:17.3671133Z   import pkg_resources
2025-08-14T21:56:17.5560631Z Running inductor/test_subgraph_choice 1/1 ... [2025-08-14 21:56:17.554983]
2025-08-14T21:56:17.5561889Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:17.5563989Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:17.555433]
2025-08-14T21:56:22.5407503Z 
2025-08-14T21:56:22.5409545Z inductor/test_alignment 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_alignment_1.1_2c00063900f1da26_.log
2025-08-14T21:56:22.5411069Z 
2025-08-14T21:56:25.6730324Z 
2025-08-14T21:56:25.6732517Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_50ab492f7b3591bc_.log
2025-08-14T21:56:25.6733975Z 
2025-08-14T21:56:26.7890982Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:26.7894480Z   import pkg_resources
2025-08-14T21:56:26.9859828Z Running inductor/test_pad_mm 1/1 ... [2025-08-14 21:56:26.985519]
2025-08-14T21:56:26.9861716Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:26.9864459Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pad_mm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:26.985970]
2025-08-14T21:56:29.3893855Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:29.3897787Z   import pkg_resources
2025-08-14T21:56:29.5181043Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-08-14 21:56:29.517679]
2025-08-14T21:56:29.5181992Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:29.5185511Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:29.518090]
2025-08-14T21:56:32.8401684Z 
2025-08-14T21:56:32.8403457Z dynamo/test_deque_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deque_reconstruct_1.1_1fe630b787b97381_.log
2025-08-14T21:56:32.8406819Z 
2025-08-14T21:56:36.4043681Z 
2025-08-14T21:56:36.4045022Z inductor/test_pad_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pad_mm_1.1_97841174f891fc67_.log
2025-08-14T21:56:36.4045769Z 
2025-08-14T21:56:36.7285773Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:36.7288828Z   import pkg_resources
2025-08-14T21:56:36.9189260Z Running inductor/test_cooperative_reductions 1/1 ... [2025-08-14 21:56:36.918472]
2025-08-14T21:56:36.9190259Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:36.9193768Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cooperative_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:36.919026]
2025-08-14T21:56:40.2081655Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:40.2085022Z   import pkg_resources
2025-08-14T21:56:40.3364373Z Running inductor/test_inductor_annotations 1/1 ... [2025-08-14 21:56:40.335954]
2025-08-14T21:56:40.3365818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:40.3370642Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_annotations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:40.336371]
2025-08-14T21:56:46.2657017Z 
2025-08-14T21:56:46.2659164Z inductor/test_cooperative_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cooperative_reductions_1.1_381db5ed91fc3f42_.log
2025-08-14T21:56:46.2669770Z 
2025-08-14T21:56:48.1657745Z 
2025-08-14T21:56:48.1659408Z inductor/test_inductor_annotations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_annotations_1.1_c42bf724a5bd2a73_.log
2025-08-14T21:56:48.1660992Z 
2025-08-14T21:56:50.5319464Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:50.5322962Z   import pkg_resources
2025-08-14T21:56:50.6558615Z Running inductor/test_inductor_utils 1/1 ... [2025-08-14 21:56:50.655390]
2025-08-14T21:56:50.6559995Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:50.6564517Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:50.655813]
2025-08-14T21:56:52.8210887Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:52.8214122Z   import pkg_resources
2025-08-14T21:56:53.0078326Z Running inductor/test_op_completeness 1/1 ... [2025-08-14 21:56:53.006862]
2025-08-14T21:56:53.0079232Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:53.0081466Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_op_completeness.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:53.007313]
2025-08-14T21:56:53.9597669Z 
2025-08-14T21:56:53.9598866Z inductor/test_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_utils_1.1_336dac9e9d5b17ce_.log
2025-08-14T21:56:53.9599693Z 
2025-08-14T21:56:57.6802772Z 
2025-08-14T21:56:57.6805042Z inductor/test_op_completeness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_op_completeness_1.1_f2ff33d16f48941b_.log
2025-08-14T21:56:57.6807121Z 
2025-08-14T21:56:57.9349749Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:56:57.9353756Z   import pkg_resources
2025-08-14T21:56:58.1203627Z Running inductor/test_fp8 1/1 ... [2025-08-14 21:56:58.119876]
2025-08-14T21:56:58.1207358Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:56:58.1212915Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fp8.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:56:58.120344]
2025-08-14T21:57:01.0990371Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:01.0996623Z   import pkg_resources
2025-08-14T21:57:01.2815737Z Running inductor/test_debug_trace 1/1 ... [2025-08-14 21:57:01.280946]
2025-08-14T21:57:01.2816897Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:01.2819051Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_debug_trace.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:01.281432]
2025-08-14T21:57:06.0764706Z 
2025-08-14T21:57:06.0766227Z inductor/test_fp8 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fp8_1.1_e03988b195a6f3e2_.log
2025-08-14T21:57:06.0767476Z 
2025-08-14T21:57:10.3667388Z 
2025-08-14T21:57:10.3669486Z inductor/test_debug_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_debug_trace_1.1_0e00a8adff5131d3_.log
2025-08-14T21:57:10.3671054Z 
2025-08-14T21:57:10.4816135Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:10.4820837Z   import pkg_resources
2025-08-14T21:57:10.6626391Z Running export/test_export_strict 1/1 ... [2025-08-14 21:57:10.662207]
2025-08-14T21:57:10.6628326Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:10.6631277Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_strict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:10.662655]
2025-08-14T21:57:13.6495396Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:13.6498592Z   import pkg_resources
2025-08-14T21:57:13.7740314Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-08-14 21:57:13.773540]
2025-08-14T21:57:13.7741240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:13.7743643Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:13.773936]
2025-08-14T21:57:19.0315177Z 
2025-08-14T21:57:19.0316722Z export/test_export_strict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_strict_1.1_1a8abfdc508001d3_.log
2025-08-14T21:57:19.0318442Z 
2025-08-14T21:57:22.0497755Z 
2025-08-14T21:57:22.0499976Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_d71cf43da2db0cb8_.log
2025-08-14T21:57:22.0501836Z 
2025-08-14T21:57:23.0765250Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:23.0768684Z   import pkg_resources
2025-08-14T21:57:23.2059528Z Running inductor/test_combo_kernels 1/1 ... [2025-08-14 21:57:23.205464]
2025-08-14T21:57:23.2060890Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:23.2063199Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_combo_kernels.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:23.205934]
2025-08-14T21:57:26.1758334Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:26.1761181Z   import pkg_resources
2025-08-14T21:57:26.3036258Z Running dynamo/test_skip_guard_eval_unsafe 1/1 ... [2025-08-14 21:57:26.303188]
2025-08-14T21:57:26.3036966Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:26.3039488Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_guard_eval_unsafe.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:26.303566]
2025-08-14T21:57:30.6258300Z 
2025-08-14T21:57:30.6260047Z dynamo/test_skip_guard_eval_unsafe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_guard_eval_unsafe_1.1_5e9c651b458d6630_.log
2025-08-14T21:57:30.6260934Z 
2025-08-14T21:57:32.3817677Z 
2025-08-14T21:57:32.3819808Z inductor/test_combo_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_combo_kernels_1.1_c6c4368eefa4c181_.log
2025-08-14T21:57:32.3821542Z 
2025-08-14T21:57:34.1936622Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:34.1938175Z   import pkg_resources
2025-08-14T21:57:34.3201832Z Running inductor/test_memory_planning 1/1 ... [2025-08-14 21:57:34.319537]
2025-08-14T21:57:34.3202785Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:34.3204763Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_memory_planning.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:34.319947]
2025-08-14T21:57:35.9273293Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:35.9276545Z   import pkg_resources
2025-08-14T21:57:36.0529028Z Running inductor/test_compile_worker 1/1 ... [2025-08-14 21:57:36.052402]
2025-08-14T21:57:36.0530227Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:36.0532574Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_worker.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:36.052805]
2025-08-14T21:57:42.8973049Z 
2025-08-14T21:57:42.8974609Z inductor/test_memory_planning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_planning_1.1_e8eb247f188fcacd_.log
2025-08-14T21:57:42.8975402Z 
2025-08-14T21:57:44.4534561Z 
2025-08-14T21:57:44.4536224Z inductor/test_compile_worker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_worker_1.1_56900ca6d9ecbabd_.log
2025-08-14T21:57:44.4537323Z 
2025-08-14T21:57:46.7519953Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:46.7523038Z   import pkg_resources
2025-08-14T21:57:46.9377227Z Running dynamo/test_frame_init 1/1 ... [2025-08-14 21:57:46.936750]
2025-08-14T21:57:46.9378090Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:46.9380204Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_frame_init.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:46.937189]
2025-08-14T21:57:48.4685161Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:48.4687950Z   import pkg_resources
2025-08-14T21:57:48.5939444Z Running dynamo/test_fx_passes_pre_grad 1/1 ... [2025-08-14 21:57:48.593549]
2025-08-14T21:57:48.5940323Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:48.5943118Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_fx_passes_pre_grad.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:48.593937]
2025-08-14T21:57:50.2735884Z 
2025-08-14T21:57:50.2737325Z dynamo/test_frame_init 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_frame_init_1.1_df5d10d17e5af8ce_.log
2025-08-14T21:57:50.2738676Z 
2025-08-14T21:57:51.8822035Z 
2025-08-14T21:57:51.8823671Z dynamo/test_fx_passes_pre_grad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_passes_pre_grad_1.1_d3327247098d38a1_.log
2025-08-14T21:57:51.8827110Z 
2025-08-14T21:57:54.2298629Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:54.2301982Z   import pkg_resources
2025-08-14T21:57:54.4328567Z Running inductor/test_metrics 1/1 ... [2025-08-14 21:57:54.432408]
2025-08-14T21:57:54.4330349Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:54.4333109Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_metrics.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:54.432865]
2025-08-14T21:57:55.9347102Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:57:55.9349937Z   import pkg_resources
2025-08-14T21:57:56.1169069Z Running inductor/test_move_constructors_to_cuda 1/1 ... [2025-08-14 21:57:56.116392]
2025-08-14T21:57:56.1170024Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:57:56.1172416Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_move_constructors_to_cuda.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:57:56.116821]
2025-08-14T21:58:02.2431578Z 
2025-08-14T21:58:02.2433097Z inductor/test_metrics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_metrics_1.1_86719ed22a81add3_.log
2025-08-14T21:58:02.2434279Z 
2025-08-14T21:58:04.8505529Z 
2025-08-14T21:58:04.8507413Z inductor/test_move_constructors_to_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_move_constructors_to_cuda_1.1_bfda23a67af964f0_.log
2025-08-14T21:58:04.8508813Z 
2025-08-14T21:58:06.7476923Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:06.7481541Z   import pkg_resources
2025-08-14T21:58:06.9426039Z Running dynamo/test_inline_and_install 1/1 ... [2025-08-14 21:58:06.942166]
2025-08-14T21:58:06.9429600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:06.9432188Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_inline_and_install.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:06.942640]
2025-08-14T21:58:08.6269778Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:08.6273252Z   import pkg_resources
2025-08-14T21:58:08.7584004Z Running dynamo/test_skip_non_tensor 1/1 ... [2025-08-14 21:58:08.757757]
2025-08-14T21:58:08.7585019Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:08.7587516Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_skip_non_tensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:08.758217]
2025-08-14T21:58:11.8611198Z 
2025-08-14T21:58:11.8612792Z dynamo/test_inline_and_install 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_inline_and_install_1.1_75898b57ac437520_.log
2025-08-14T21:58:11.8617960Z 
2025-08-14T21:58:13.0552301Z 
2025-08-14T21:58:13.0554240Z dynamo/test_skip_non_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_skip_non_tensor_1.1_13a3a6dfe7be21c7_.log
2025-08-14T21:58:13.0556856Z 
2025-08-14T21:58:15.9605910Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:15.9609517Z   import pkg_resources
2025-08-14T21:58:16.1239850Z Running inductor/test_cutlass_evt 1/1 ... [2025-08-14 21:58:16.123578]
2025-08-14T21:58:16.1240717Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:16.1242832Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cutlass_evt.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:16.123963]
2025-08-14T21:58:16.3556321Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:16.3557934Z   import pkg_resources
2025-08-14T21:58:16.4830880Z Running inductor/test_kernel_optimization 1/1 ... [2025-08-14 21:58:16.482675]
2025-08-14T21:58:16.4831465Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:16.4834197Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_kernel_optimization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:16.483085]
2025-08-14T21:58:23.9975518Z 
2025-08-14T21:58:23.9978962Z inductor/test_cutlass_evt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_evt_1.1_d6389ab70637f558_.log
2025-08-14T21:58:23.9980668Z 
2025-08-14T21:58:26.1164004Z 
2025-08-14T21:58:26.1165994Z inductor/test_kernel_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_optimization_1.1_d0ec033a8f3ee14b_.log
2025-08-14T21:58:26.1167901Z 
2025-08-14T21:58:27.8310196Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:27.8313549Z   import pkg_resources
2025-08-14T21:58:28.0006340Z Running export/test_export_with_inline_and_install 1/1 ... [2025-08-14 21:58:28.000115]
2025-08-14T21:58:28.0007603Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:28.0010016Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_with_inline_and_install.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:28.000455]
2025-08-14T21:58:30.4261758Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:30.4264722Z   import pkg_resources
2025-08-14T21:58:30.5629151Z Running inductor/test_static_cuda_launcher 1/1 ... [2025-08-14 21:58:30.562425]
2025-08-14T21:58:30.5630136Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:30.5633379Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_static_cuda_launcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:30.562853]
2025-08-14T21:58:37.5693704Z 
2025-08-14T21:58:37.5699811Z export/test_export_with_inline_and_install 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_with_inline_and_install_1.1_50df0c9345600f70_.log
2025-08-14T21:58:37.5707567Z 
2025-08-14T21:58:40.0356236Z 
2025-08-14T21:58:40.0357762Z inductor/test_static_cuda_launcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_static_cuda_launcher_1.1_07b37a91fc999ec4_.log
2025-08-14T21:58:40.0358584Z 
2025-08-14T21:58:41.6623139Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:41.6626587Z   import pkg_resources
2025-08-14T21:58:41.7921265Z Running dynamo/test_pre_dispatch 1/1 ... [2025-08-14 21:58:41.791644]
2025-08-14T21:58:41.7924055Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:41.7926426Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_pre_dispatch.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:41.792114]
2025-08-14T21:58:44.0040681Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:44.0043518Z   import pkg_resources
2025-08-14T21:58:44.1272425Z Running dynamo/test_sdpa 1/1 ... [2025-08-14 21:58:44.126857]
2025-08-14T21:58:44.1273249Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:44.1275745Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sdpa.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:44.127248]
2025-08-14T21:58:45.3347828Z 
2025-08-14T21:58:45.3349320Z dynamo/test_pre_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_pre_dispatch_1.1_12d9e443dc4432e9_.log
2025-08-14T21:58:45.3350332Z 
2025-08-14T21:58:48.4048961Z 
2025-08-14T21:58:48.4053820Z dynamo/test_sdpa 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sdpa_1.1_95450f9b111ec26e_.log
2025-08-14T21:58:48.4055884Z 
2025-08-14T21:58:49.5148904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:49.5152323Z   import pkg_resources
2025-08-14T21:58:49.7107332Z Running inductor/test_inplacing_pass 1/1 ... [2025-08-14 21:58:49.710288]
2025-08-14T21:58:49.7108535Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:49.7113062Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:49.710888]
2025-08-14T21:58:51.9600695Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:51.9604263Z   import pkg_resources
2025-08-14T21:58:52.0862611Z Running dynamo/test_graph_region_tracker 1/1 ... [2025-08-14 21:58:52.085818]
2025-08-14T21:58:52.0864781Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:58:52.0867449Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_graph_region_tracker.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:58:52.086247]
2025-08-14T21:58:56.0639085Z 
2025-08-14T21:58:56.0641234Z dynamo/test_graph_region_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_graph_region_tracker_1.1_34fcef00b03c8164_.log
2025-08-14T21:58:56.0643140Z 
2025-08-14T21:58:59.5400343Z 
2025-08-14T21:58:59.5402387Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_e1f020c85a2b129f_.log
2025-08-14T21:58:59.5404250Z 
2025-08-14T21:58:59.9819943Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:58:59.9823290Z   import pkg_resources
2025-08-14T21:59:00.1721499Z Running inductor/test_fuzzer 1/1 ... [2025-08-14 21:59:00.171660]
2025-08-14T21:59:00.1722877Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:00.1725822Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fuzzer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:00.172112]
2025-08-14T21:59:03.6118210Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:03.6121507Z   import pkg_resources
2025-08-14T21:59:03.7428572Z Running dynamo/test_subgraphs 1/1 ... [2025-08-14 21:59:03.742361]
2025-08-14T21:59:03.7429683Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:03.7434722Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_subgraphs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:03.742814]
2025-08-14T21:59:07.7358317Z 
2025-08-14T21:59:07.7359784Z dynamo/test_subgraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_subgraphs_1.1_b3bf3e50241ce698_.log
2025-08-14T21:59:07.7361100Z 
2025-08-14T21:59:08.6997732Z 
2025-08-14T21:59:08.6999157Z inductor/test_fuzzer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fuzzer_1.1_4be76eb3d565fb0f_.log
2025-08-14T21:59:08.7000308Z 
2025-08-14T21:59:11.1347727Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:11.1351226Z   import pkg_resources
2025-08-14T21:59:11.2579502Z Running inductor/test_quantization 1/1 ... [2025-08-14 21:59:11.257562]
2025-08-14T21:59:11.2580083Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:11.2582944Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_quantization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:11.257961]
2025-08-14T21:59:12.1687621Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:12.1689403Z   import pkg_resources
2025-08-14T21:59:12.2917181Z Running inductor/test_compile_subprocess 1/1 ... [2025-08-14 21:59:12.291353]
2025-08-14T21:59:12.2917732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:12.2920335Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:12.291712]
2025-08-14T21:59:19.3777998Z 
2025-08-14T21:59:19.3779942Z inductor/test_quantization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_quantization_1.1_60e6322a24ee71a1_.log
2025-08-14T21:59:19.3781702Z 
2025-08-14T21:59:21.9124444Z 
2025-08-14T21:59:21.9125969Z inductor/test_compile_subprocess 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_1.1_30f3c58ed06d355e_.log
2025-08-14T21:59:21.9127259Z 
2025-08-14T21:59:22.8159426Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:22.8162167Z   import pkg_resources
2025-08-14T21:59:22.9469262Z Running dynamo/test_view 1/1 ... [2025-08-14 21:59:22.946491]
2025-08-14T21:59:22.9469772Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:22.9472635Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_view.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:22.946936]
2025-08-14T21:59:25.3090331Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:25.3092045Z   import pkg_resources
2025-08-14T21:59:25.4364581Z Running dynamo/test_list 1/1 ... [2025-08-14 21:59:25.436063]
2025-08-14T21:59:25.4365378Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:25.4368076Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:25.436490]
2025-08-14T21:59:26.4374431Z 
2025-08-14T21:59:26.4375757Z dynamo/test_view 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_view_1.1_44e61e7d06d41118_.log
2025-08-14T21:59:26.4376498Z 
2025-08-14T21:59:29.1332161Z 
2025-08-14T21:59:29.1333373Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_171af1a94bb9eb47_.log
2025-08-14T21:59:29.1334439Z 
2025-08-14T21:59:30.0595233Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:30.0599458Z   import pkg_resources
2025-08-14T21:59:30.2456198Z Running inductor/test_loop_ordering 1/1 ... [2025-08-14 21:59:30.245046]
2025-08-14T21:59:30.2457406Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:30.2461208Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_loop_ordering.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:30.245593]
2025-08-14T21:59:33.4529475Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:33.4531047Z   import pkg_resources
2025-08-14T21:59:33.5795179Z Running inductor/test_fxir_backend 1/1 ... [2025-08-14 21:59:33.579181]
2025-08-14T21:59:33.5795720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:33.5798315Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_fxir_backend.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:33.579533]
2025-08-14T21:59:39.5316883Z 
2025-08-14T21:59:39.5318106Z inductor/test_loop_ordering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_loop_ordering_1.1_ac47af9e6fa9f414_.log
2025-08-14T21:59:39.5319103Z 
2025-08-14T21:59:41.6390930Z 
2025-08-14T21:59:41.6392182Z inductor/test_fxir_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fxir_backend_1.1_f15b98d277116cee_.log
2025-08-14T21:59:41.6392948Z 
2025-08-14T21:59:42.9818547Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:42.9821375Z   import pkg_resources
2025-08-14T21:59:43.1153071Z Running dynamo/test_install_free_tensors 1/1 ... [2025-08-14 21:59:43.114826]
2025-08-14T21:59:43.1153896Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:43.1156643Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_install_free_tensors.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:43.115275]
2025-08-14T21:59:45.0957774Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:45.0959470Z   import pkg_resources
2025-08-14T21:59:45.2244473Z Running dynamo/test_autograd_function 1/1 ... [2025-08-14 21:59:45.224008]
2025-08-14T21:59:45.2245164Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:45.2247447Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_autograd_function.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:45.224428]
2025-08-14T21:59:46.8085954Z 
2025-08-14T21:59:46.8088227Z dynamo/test_install_free_tensors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_install_free_tensors_1.1_ef424bf01f28ed48_.log
2025-08-14T21:59:46.8089593Z 
2025-08-14T21:59:50.3710239Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:50.3713662Z   import pkg_resources
2025-08-14T21:59:50.5090235Z Running dynamo/test_config 1/1 ... [2025-08-14 21:59:50.508503]
2025-08-14T21:59:50.5090902Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:50.5097860Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_config.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:50.509104]
2025-08-14T21:59:53.1898514Z 
2025-08-14T21:59:53.1900117Z dynamo/test_autograd_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_autograd_function_1.1_3065a366f6775b4e_.log
2025-08-14T21:59:53.1901538Z 
2025-08-14T21:59:54.1265086Z 
2025-08-14T21:59:54.1266640Z dynamo/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_config_1.1_41d90846b8ee8d76_.log
2025-08-14T21:59:54.1272327Z 
2025-08-14T21:59:57.2656453Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:57.2659823Z   import pkg_resources
2025-08-14T21:59:57.4505986Z Running inductor/test_needs_exact_strides 1/1 ... [2025-08-14 21:59:57.449727]
2025-08-14T21:59:57.4506977Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:57.4509378Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_needs_exact_strides.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:57.450177]
2025-08-14T21:59:57.8601912Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T21:59:57.8605559Z   import pkg_resources
2025-08-14T21:59:58.0146565Z Running dynamo/test_compile 1/1 ... [2025-08-14 21:59:58.014179]
2025-08-14T21:59:58.0147384Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T21:59:58.0150201Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_compile.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 21:59:58.014641]
2025-08-14T22:00:02.9578131Z 
2025-08-14T22:00:02.9579888Z dynamo/test_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compile_1.1_6be419340e474410_.log
2025-08-14T22:00:02.9581059Z 
2025-08-14T22:00:07.1934190Z 
2025-08-14T22:00:07.1936183Z inductor/test_needs_exact_strides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_needs_exact_strides_1.1_b3f8a7d0cb127576_.log
2025-08-14T22:00:07.2024324Z 
2025-08-14T22:00:07.5047635Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:07.5051012Z   import pkg_resources
2025-08-14T22:00:07.6976784Z Running inductor/test_graph_transform_observer 1/1 ... [2025-08-14 22:00:07.696529]
2025-08-14T22:00:07.6977789Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:07.6980436Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_graph_transform_observer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:07.697006]
2025-08-14T22:00:11.0013677Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:11.0015216Z   import pkg_resources
2025-08-14T22:00:11.1272773Z Running dynamo/test_unittest 1/1 ... [2025-08-14 22:00:11.126918]
2025-08-14T22:00:11.1273251Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:11.1276732Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_unittest.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:11.127344]
2025-08-14T22:00:15.0399591Z 
2025-08-14T22:00:15.0400565Z dynamo/test_unittest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unittest_1.1_e9e5fa84fa9643ef_.log
2025-08-14T22:00:15.0401258Z 
2025-08-14T22:00:16.0573303Z 
2025-08-14T22:00:16.0575001Z inductor/test_graph_transform_observer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_graph_transform_observer_1.1_7779f14f625dfe08_.log
2025-08-14T22:00:16.0575937Z 
2025-08-14T22:00:18.5388603Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:18.5391610Z   import pkg_resources
2025-08-14T22:00:18.6645278Z Running dynamo/test_sources 1/1 ... [2025-08-14 22:00:18.664080]
2025-08-14T22:00:18.6646049Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:18.6648228Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:18.664468]
2025-08-14T22:00:19.3649716Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:19.3652496Z   import pkg_resources
2025-08-14T22:00:19.4899838Z Running inductor/test_torchinductor_codegen_config_overrides 1/1 ... [2025-08-14 22:00:19.489550]
2025-08-14T22:00:19.4900993Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:19.4903234Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_codegen_config_overrides.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:19.489897]
2025-08-14T22:00:21.9395161Z 
2025-08-14T22:00:21.9396540Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_daf7ca6288a862a6_.log
2025-08-14T22:00:21.9398058Z 
2025-08-14T22:00:25.2460040Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:25.2463201Z   import pkg_resources
2025-08-14T22:00:25.3730444Z Running dynamo/test_guard_serialization 1/1 ... [2025-08-14 22:00:25.372617]
2025-08-14T22:00:25.3731160Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:25.3732920Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_guard_serialization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:25.372977]
2025-08-14T22:00:26.8933715Z 
2025-08-14T22:00:26.8935620Z inductor/test_torchinductor_codegen_config_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_config_overrides_1.1_2307b476cef3b496_.log
2025-08-14T22:00:26.8937407Z 
2025-08-14T22:00:30.3211349Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:30.3214304Z   import pkg_resources
2025-08-14T22:00:30.4481526Z Running inductor/test_scatter_optimization 1/1 ... [2025-08-14 22:00:30.447737]
2025-08-14T22:00:30.4482067Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:30.4484655Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_scatter_optimization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:30.448176]
2025-08-14T22:00:32.6954648Z 
2025-08-14T22:00:32.6956559Z dynamo/test_guard_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_guard_serialization_1.1_6ecf977cb3004d4b_.log
2025-08-14T22:00:32.6958441Z 
2025-08-14T22:00:36.2167455Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:36.2170474Z   import pkg_resources
2025-08-14T22:00:36.3446820Z Running export/test_upgrader 1/1 ... [2025-08-14 22:00:36.343725]
2025-08-14T22:00:36.3447494Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:36.3449008Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:36.344158]
2025-08-14T22:00:39.8956252Z 
2025-08-14T22:00:39.8959915Z inductor/test_scatter_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_scatter_optimization_1.1_abec67cacede120f_.log
2025-08-14T22:00:39.8961554Z 
2025-08-14T22:00:41.0732072Z 
2025-08-14T22:00:41.0733847Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_f6d89f2db696bf73_.log
2025-08-14T22:00:41.0739888Z 
2025-08-14T22:00:43.7866764Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:43.7870059Z   import pkg_resources
2025-08-14T22:00:43.9176960Z Running dynamo/test_einops 1/1 ... [2025-08-14 22:00:43.916734]
2025-08-14T22:00:43.9177422Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:43.9178958Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:43.917196]
2025-08-14T22:00:45.1704620Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:45.1707540Z   import pkg_resources
2025-08-14T22:00:45.3025344Z Running export/test_nativert 1/1 ... [2025-08-14 22:00:45.302107]
2025-08-14T22:00:45.3026093Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:45.3028504Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_nativert.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:45.302529]
2025-08-14T22:00:47.4575635Z 
2025-08-14T22:00:47.4577024Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_27250f8c259ab847_.log
2025-08-14T22:00:47.4578316Z 
2025-08-14T22:00:51.8679196Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:51.8682053Z   import pkg_resources
2025-08-14T22:00:52.0496827Z Running inductor/test_auto_functionalize 1/1 ... [2025-08-14 22:00:52.048853]
2025-08-14T22:00:52.0497659Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:52.0499987Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:52.049430]
2025-08-14T22:00:53.7763473Z 
2025-08-14T22:00:53.7765129Z export/test_nativert 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_nativert_1.1_61cd8f6c01549477_.log
2025-08-14T22:00:53.7766257Z 
2025-08-14T22:00:55.9254866Z 
2025-08-14T22:00:55.9257090Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_6f8aa4f6f5f866d9_.log
2025-08-14T22:00:55.9258667Z 
2025-08-14T22:00:57.2609325Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:00:57.2612357Z   import pkg_resources
2025-08-14T22:00:57.3859173Z Running dynamo/test_export 1/1 ... [2025-08-14 22:00:57.385472]
2025-08-14T22:00:57.3860342Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:00:57.3862925Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:00:57.385895]
2025-08-14T22:01:00.5960178Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:00.5963315Z   import pkg_resources
2025-08-14T22:01:00.7991235Z Running dynamo/test_sets 1/1 ... [2025-08-14 22:01:00.798649]
2025-08-14T22:01:00.7996731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:00.7998727Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sets.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:00.799124]
2025-08-14T22:01:01.1020070Z 
2025-08-14T22:01:01.1021465Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_f798d846c16d877a_.log
2025-08-14T22:01:01.1022815Z 
2025-08-14T22:01:04.5199026Z 
2025-08-14T22:01:04.5200523Z dynamo/test_sets 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sets_1.1_6537b48181cbc435_.log
2025-08-14T22:01:04.5201752Z 
2025-08-14T22:01:04.8015961Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:04.8018839Z   import pkg_resources
2025-08-14T22:01:04.9365358Z Running dynamo/test_profiler 1/1 ... [2025-08-14 22:01:04.936096]
2025-08-14T22:01:04.9366318Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:04.9370320Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:04.936533]
2025-08-14T22:01:07.9815941Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:07.9818826Z   import pkg_resources
2025-08-14T22:01:08.1118785Z Running dynamo/test_optimizers 1/1 ... [2025-08-14 22:01:08.111315]
2025-08-14T22:01:08.1120091Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:08.1125253Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_optimizers.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:08.111742]
2025-08-14T22:01:09.1478838Z 
2025-08-14T22:01:09.1480523Z dynamo/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_profiler_1.1_023fba9e7bcb097f_.log
2025-08-14T22:01:09.1482115Z 
2025-08-14T22:01:11.7967632Z 
2025-08-14T22:01:11.7969304Z dynamo/test_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_optimizers_1.1_cc506e6deb95cdaa_.log
2025-08-14T22:01:11.7970717Z 
2025-08-14T22:01:12.4361139Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:12.4362968Z   import pkg_resources
2025-08-14T22:01:12.5649990Z Running dynamo/test_python_dispatcher 1/1 ... [2025-08-14 22:01:12.564653]
2025-08-14T22:01:12.5650497Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:12.5654212Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:12.565027]
2025-08-14T22:01:15.0752872Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:15.0755654Z   import pkg_resources
2025-08-14T22:01:15.2006270Z Running dynamo/test_package 1/1 ... [2025-08-14 22:01:15.200207]
2025-08-14T22:01:15.2007121Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:15.2009636Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:15.200621]
2025-08-14T22:01:16.1365628Z 
2025-08-14T22:01:16.1367168Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_e5034b0d1670afb9_.log
2025-08-14T22:01:16.1368573Z 
2025-08-14T22:01:19.5692941Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:19.5695801Z   import pkg_resources
2025-08-14T22:01:19.6971279Z Running dynamo/test_input_attr_tracking 1/1 ... [2025-08-14 22:01:19.696688]
2025-08-14T22:01:19.6972090Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:19.6974736Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_input_attr_tracking.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:19.697119]
2025-08-14T22:01:22.5306035Z 
2025-08-14T22:01:22.5308236Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_91deb54272b11310_.log
2025-08-14T22:01:22.5309989Z 
2025-08-14T22:01:23.1687985Z 
2025-08-14T22:01:23.1689948Z dynamo/test_input_attr_tracking 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_input_attr_tracking_1.1_14e7cfafdeec138d_.log
2025-08-14T22:01:23.1691490Z 
2025-08-14T22:01:26.8962574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:26.8965483Z   import pkg_resources
2025-08-14T22:01:27.0334237Z Running dynamo/test_callback 1/1 ... [2025-08-14 22:01:27.032966]
2025-08-14T22:01:27.0334901Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:27.0337610Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_callback.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:27.033435]
2025-08-14T22:01:27.3570631Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:27.3572459Z   import pkg_resources
2025-08-14T22:01:27.5383258Z Running dynamo/test_aot_autograd_cache 1/1 ... [2025-08-14 22:01:27.537868]
2025-08-14T22:01:27.5384570Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:27.5394811Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_aot_autograd_cache.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:27.538980]
2025-08-14T22:01:34.9268425Z 
2025-08-14T22:01:34.9269991Z dynamo/test_callback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_callback_1.1_662e5a12d95a5cb6_.log
2025-08-14T22:01:36.4596352Z 
2025-08-14T22:01:36.4596372Z 
2025-08-14T22:01:36.4597795Z dynamo/test_aot_autograd_cache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_cache_1.1_5e9b86e7a022d813_.log
2025-08-14T22:01:36.4598632Z 
2025-08-14T22:01:38.4146876Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:38.4149931Z   import pkg_resources
2025-08-14T22:01:38.5804063Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-08-14 22:01:38.580005]
2025-08-14T22:01:38.5804785Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:38.5806544Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:38.580375]
2025-08-14T22:01:39.9445570Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:39.9448693Z   import pkg_resources
2025-08-14T22:01:40.0826125Z Running dynamo/test_torchrec 1/1 ... [2025-08-14 22:01:40.082213]
2025-08-14T22:01:40.0828385Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:40.0831033Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_torchrec.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:40.082699]
2025-08-14T22:01:42.2705240Z 
2025-08-14T22:01:42.2706492Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_1f2d3ef3b7b2258e_.log
2025-08-14T22:01:42.2707433Z 
2025-08-14T22:01:43.6611352Z 
2025-08-14T22:01:43.6612717Z dynamo/test_torchrec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_torchrec_1.1_801f1d6d26385e60_.log
2025-08-14T22:01:43.6613956Z 
2025-08-14T22:01:45.6365808Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:45.6368672Z   import pkg_resources
2025-08-14T22:01:45.7671796Z Running dynamo/test_hooks 1/1 ... [2025-08-14 22:01:45.766730]
2025-08-14T22:01:45.7673011Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:45.7675552Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_hooks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:45.767228]
2025-08-14T22:01:47.3114723Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:47.3116273Z   import pkg_resources
2025-08-14T22:01:47.4395942Z Running dynamo/test_reorder_logs 1/1 ... [2025-08-14 22:01:47.438646]
2025-08-14T22:01:47.4396848Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:47.4399039Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_reorder_logs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:47.439061]
2025-08-14T22:01:50.0411287Z 
2025-08-14T22:01:50.0412293Z dynamo/test_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_hooks_1.1_55c89a2904b3b734_.log
2025-08-14T22:01:50.0413345Z 
2025-08-14T22:01:51.0500128Z 
2025-08-14T22:01:51.0501963Z dynamo/test_reorder_logs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reorder_logs_1.1_8de29959a82d6ac3_.log
2025-08-14T22:01:51.0503313Z 
2025-08-14T22:01:53.4599041Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:53.4602592Z   import pkg_resources
2025-08-14T22:01:53.5894463Z Running dynamo/test_comptime 1/1 ... [2025-08-14 22:01:53.588991]
2025-08-14T22:01:53.5896345Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:53.5898767Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:53.589423]
2025-08-14T22:01:54.4840109Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:01:54.4843039Z   import pkg_resources
2025-08-14T22:01:54.6121122Z Running test_quantization 2/4 ... [2025-08-14 22:01:54.611407]
2025-08-14T22:01:54.6122651Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:01:54.6124576Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'not serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:01:54.611848]
2025-08-14T22:01:58.0885126Z 
2025-08-14T22:01:58.0886925Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_61bc04915a2b21d2_.log
2025-08-14T22:01:58.0888481Z 
2025-08-14T22:02:02.8255271Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:02:02.8258649Z   import pkg_resources
2025-08-14T22:02:03.0214979Z Running test_quantization 3/4 ... [2025-08-14 22:02:03.020728]
2025-08-14T22:02:03.0215822Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:02:03.0217966Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'not serial', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:02:03.021203]
2025-08-14T22:02:26.7635995Z 
2025-08-14T22:02:26.7637238Z test_ops 6/8 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_6.8_144e8cd25cea85b1_.log
2025-08-14T22:02:27.0510503Z Running 4241 items in this shard: test/test_ops.py::TestCommonCPU::test_compare_cpu___rand___cpu_int64, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_bool_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_float_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_constant_pad_nd_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_geometric_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_logspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_masked_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_new_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_log_softmax_with_dtype_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_tensorsolve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log10_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log1p_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_or_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_norm_fro_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ormqr_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_erfcx_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__unsafe_masked_index_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmv_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_alias_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argsort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bernoulli_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bincount_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_left_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bucketize_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cartesian_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cartesian_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cdouble_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_char_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_max_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_combinations_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cummin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagflat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_digamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_digamma_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_permuted_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_erfc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expm1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_rfft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_float_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_floor_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_gradient_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isposinf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_inv_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_hermitian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_tensorinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logical_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mH_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_var_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_matrix_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_min_reduction_with_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_movedim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_mv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_empty_strided_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_ones_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cosine_embedding_loss_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_elu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_constant_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_outer_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_3_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rad2deg_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_reciprocal_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_remainder_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_repeat_interleave_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_neg_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_amax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_searchsorted_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_hann_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signbit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_i0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_list_args_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_square_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_multiple_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tensor_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trace_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_trace_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_transpose_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_triu_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unsqueeze_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_var_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_vdot_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_view_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_zeros_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_add_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_addr_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_bitwise_or_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_bool_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_byte_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_cat_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_combinations_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_conj_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_digamma_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_dsplit_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_flatten_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_float_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_gather_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_hsplit_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_index_select_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_isposinf_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_lgamma_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_logical_not_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_logit_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_long_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_min_reduction_with_dim_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_native_dropout_backward_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_ne_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_nn_functional_cosine_embedding_loss_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_nn_functional_pixel_shuffle_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_permute_copy_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_polygamma_polygamma_n_2_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_real_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scatter_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_select_scatter_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_sort_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_airy_ai_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_hermite_polynomial_he_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_i0e_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_modified_bessel_i0_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_scaled_modified_bessel_k1_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_xlog1py_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_sqrt_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_square_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_t_copy_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_tanh_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_unbind_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_unfold_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_unique_consecutive_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_unsqueeze_cpu_bool, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_H_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples___radd___cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples___rand___cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples___rdiv___cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples___rpow___cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples__chunk_cat_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples__unsafe_masked_index_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_add_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addbmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addbmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addcmul_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addmm_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_addmv_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_alias_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_allclose_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_any_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_arange_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_argwhere_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_atleast_3d_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_block_diag_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_tensors_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_broadcast_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cholesky_solve_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_chunk_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clamp_max_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_clone_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_column_stack_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_conj_physical_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_constant_pad_nd_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_cosh_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_linear_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_constant_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_reflect_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pad_replicate_negative_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_pairwise_distance_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_softsign_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_threshold_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_normal_number_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_outer_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_pca_lowrank_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_pow_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rand_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_ravel_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_repeat_interleave_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_resize__cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_rot90_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sgn_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_signal_windows_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_sinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_slice_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_slice_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_bessel_y0_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_bessel_y1_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_chebyshev_polynomial_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_erfcx_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_hermite_polynomial_he_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_legendre_polynomial_p_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_ndtr_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_std_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_stft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_svd_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_t_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_take_along_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_tanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_to_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trace_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_trapz_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_triu_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_unfold_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_unsafe_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_var_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_var_unbiased_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_vdot_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_view_copy_cpu_complex64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_xlogy_cpu_int64, test/test_ops.py::TestCommonCPU::test_noncontiguous_samples_zeros_like_cpu_complex64, test/test_ops.py::TestCommonCPU::test_numpy_ref_aminmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_argwhere_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_equal_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_equal_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_item_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_jiterator_2inputs_2outputs_cpu_complex128, test/test_ops.py::TestCommonCPU::test_numpy_ref_linalg_cross_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_linalg_tensorsolve_cpu_complex128, test/test_ops.py::TestCommonCPU::test_numpy_ref_meshgrid_variadic_tensors_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_native_layer_norm_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_nn_functional_pairwise_distance_cpu_complex128, test/test_ops.py::TestCommonCPU::test_numpy_ref_roll_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_searchsorted_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_signal_windows_general_cosine_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_signal_windows_general_hamming_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_tensor_split_cpu_complex128, test/test_ops.py::TestCommonCPU::test_numpy_ref_tile_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_tril_indices_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_triu_indices_cpu_int64, test/test_ops.py::TestCommonCPU::test_numpy_ref_view_copy_cpu_complex128, test/test_ops.py::TestCommonCPU::test_numpy_ref_view_copy_cpu_float64, test/test_ops.py::TestCommonCPU::test_numpy_ref_view_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_out__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs__conversions_float_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs__conversions_long_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_any_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_atleast_1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_bitwise_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_out__refs_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_constant_pad_nd_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_cos_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_cosh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_cumsum_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_diag_embed_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_empty_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_erfinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_fft_irfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_hsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_isneginf_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_isposinf_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_istft_cpu_complex64, test/test_ops.py::TestCommonCPU::test_out__refs_linalg_diagonal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_logical_not_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_narrow_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_nn_functional_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_ones_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_reciprocal_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_roll_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_sgn_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_special_multigammaln_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_std_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_out__refs_view_as_cpu_float32, 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test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_nn_functional_pad_reflect_cpu_float32, 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test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_softmax_with_dtype_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_sort_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_entr_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_sub_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_transpose_copy_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_zeros_cpu_float32, test/test_ops.py::TestMathBitsCPU::test_conj_view___getitem___cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs__conversions_float_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs__conversions_int_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_addr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_atan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_constant_pad_nd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_eq_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_expand_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_fft_hfftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_fft_ifft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_index_fill_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_lerp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_linspace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_log10_cpu_complex64, 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test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_t_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_take_along_dim_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unbind_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unfold_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_unsqueeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_abs_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_argwhere_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_conj_physical_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_constant_pad_nd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_einsum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_eq_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_hfftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifftshift_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flip_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fliplr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_put_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_2inputs_2outputs_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_diagonal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_ldl_factor_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_ldl_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lstsq_grad_oriented_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_power_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_matrix_rank_hermitian_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_multi_dot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_pinv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_tensorinv_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_vecdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logaddexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_matmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_normalize_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_replicate_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_replicate_negative_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pixel_unshuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_t_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tril_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_true_divide_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unbind_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unflatten_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_vdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_zero__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_T_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___rdiv___cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view___rmul___cpu_complex128, 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test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_and_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_or_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logical_xor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logspace_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_meshgrid_variadic_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_pow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_renorm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_special_log_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_t_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unbind_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unsqueeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_var_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_var_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addcdiv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_allclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_bool_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_char_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diag_embed_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_dist_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expand_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_irfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_put_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cross_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_pinv_singular_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_vector_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_not_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_cumprod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_matmul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_movedim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_mv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ne_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_pow_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resolve_neg_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rsqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_list_args_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sum_to_size_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_t_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_take_along_dim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tile_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_to_sparse_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_transpose_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_transpose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_triangular_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unfold_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_contiguous_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_count_nonzero_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_no_rounding_mode_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_trunc_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_exp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_expm1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_hfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_rfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_flipud_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_floor_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_igammac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_lgamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_vector_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_log_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_meshgrid_variadic_tensors_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_gelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_margin_ranking_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_normal__in_place_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_normal_number_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_pow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rad2deg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_renorm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_repeat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_entr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sqrt_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_trace_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_transpose_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_transpose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_view_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_xlogy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_zeros_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_addbmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_allclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_angle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_char_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clamp_min_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_combinations_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_conj_physical_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cumprod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diff_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_permuted_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_exponential_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ifftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_ihfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_frac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_frexp_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_hstack_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_igamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_index_reduce_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_int_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_isinf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_jiterator_unary_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_kthvalue_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_lgamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_cholesky_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_inv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_inv_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_lu_factor_ex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_matrix_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_log_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_long_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_amin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_argmin_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_masked_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_min_reduction_with_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mode_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nanmean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_cross_entropy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_ctc_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_embedding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_fractional_max_pool2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardswish_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_hardtanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_nll_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_normalize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pad_replicate_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_pairwise_distance_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_rms_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_smooth_l1_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_softshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_nn_functional_tanhshrink_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_norm_fro_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_normal_in_place_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_normal_number_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_permute_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_polar_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_prod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_quantile_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_rot90_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_round_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_scatter_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_select_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_general_hamming_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_signal_windows_kaiser_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_sinc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_entr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_special_hermite_polynomial_h_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_list_args_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_split_with_sizes_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_squeeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_squeeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_std_mean_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tile_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_tril_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_true_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unflatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unfold_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_uniform_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unique_consecutive_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsqueeze_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_unsqueeze_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_vstack_cpu_float64, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs__conversions_cdouble_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs__conversions_char_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs__conversions_complex_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_abs_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_alias_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_amin_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_bitwise_not_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_bitwise_xor_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_cauchy__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_chunk_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_clamp_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_cumsum__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_deg2rad_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_diag_embed_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_diagonal_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_eq__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_eq_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_erfc__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_fft_ifft_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_fft_ifftn_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_fft_irfft2_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_frac_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_ge__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_igammac__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_index_fill__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_is_complex_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_isnan_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_isposinf_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_mul__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_mvlgamma__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_narrow_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_new_empty_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_new_ones_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_nn_functional_glu_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_nn_functional_hardtanh_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_nn_functional_mish_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_reshape_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_rsqrt__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_rtruediv_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_sin__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_softmax_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_decomp_table_op__refs_special_xlog1py_cpu, 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test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_broadcast_tensors_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_ceil_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_clamp_min__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_copysign__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_copysign_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_diagonal_scatter_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_digamma__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_fft_fftn_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_frac__cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_full_cpu, 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test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_i0e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_var_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___radd___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__native_batch_norm_legit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cov_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_elu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_stft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_empty_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_full_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polar_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_pow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rad2deg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_airy_ai_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_zeta_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_multiple_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_transpose_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rdiv___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__chunk_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_all_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bitwise_right_shift_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_vector_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_xor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softsign_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randn_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_reshape_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_resize_as__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_searchsorted_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_entr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_i1e_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unravel_index_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_bool, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_uint8, test/test_ops.py::TestTagsCPU::test_tags_T_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rdiv___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___ror___cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_bfloat16_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_char_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_bitwise_or_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_broadcast_shapes_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_chunk_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diag_embed_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diagonal_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_equal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expand_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_fftn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_hfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_rfft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fmin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_heaviside_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_hypot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_vector_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logaddexp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_not_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_xor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logsumexp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_lt_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_movedim_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_mul_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_permute_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_randn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_ravel_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_rot90_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_rsqrt_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_sinc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_std_mean_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_take_along_dim_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_tril_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_true_divide_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_unsqueeze_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_view_as_complex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_view_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_where_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_addcdiv_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_amax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_amin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_argwhere_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_atan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_atanh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cholesky_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_combinations_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_conj_physical_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cumsum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_diagflat_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_diff_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_dsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_einsum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_empty_strided_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_erf_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_expand_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_expm1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_hfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_rfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fill_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_flatten_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_frac_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_gcd_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_hash_tensor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_hsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_hypot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_igamma_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_put_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_reduce_amin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_jiterator_binary_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_inv_ex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lu_factor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_matrix_rank_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_vecdot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_vector_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linspace_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_logaddexp2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_logical_xor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_median_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nan_to_num_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nansum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_new_zeros_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_permute_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_positive_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_rad2deg_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_repeat_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_scatter_add_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sigmoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_signbit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_i1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_i1e_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_i1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_xlog1py_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_mean_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_svd_lowrank_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unfold_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unique_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_cpu_float32
2025-08-14T22:02:27.2812816Z 
2025-08-14T22:02:33.4079434Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:02:33.4082378Z   import pkg_resources
2025-08-14T22:02:33.6092884Z Running test_quantization 4/4 ... [2025-08-14 22:02:33.608810]
2025-08-14T22:02:33.6094160Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:02:33.6099720Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'not serial', '--shard-id=4', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:02:33.609592]
2025-08-14T22:11:33.4768745Z 
2025-08-14T22:11:33.4770633Z test_quantization 4/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_4.4_9e349845b7120a1e_.log
2025-08-14T22:11:33.5021571Z Running 341 items in this shard: test/test_quantization.py::TestQuantizedOps::test_adaptive_avg_pool, test/test_quantization.py::TestQuantizedOps::test_adaptive_avg_pool2d_nhwc, test/test_quantization.py::TestQuantizedOps::test_adaptive_avg_pool3d_ndhwc, test/test_quantization.py::TestQuantizedOps::test_add_scalar_relu, test/test_quantization.py::TestQuantizedOps::test_avg_pool3d, test/test_quantization.py::TestQuantizedOps::test_custom_module_lstm, test/test_quantization.py::TestQuantizedOps::test_custom_module_multi_head_attention, test/test_quantization.py::TestQuantizedOps::test_hardswish, test/test_quantization.py::TestQuantizedOps::test_instance_norm, test/test_quantization.py::TestQuantizedOps::test_int8_add_onednn, test/test_quantization.py::TestQuantizedOps::test_linear_bias_unpack, test/test_quantization.py::TestQuantizedOps::test_max_pool1d, test/test_quantization.py::TestQuantizedOps::test_max_pool2d, test/test_quantization.py::TestQuantizedOps::test_mean, test/test_quantization.py::TestQuantizedOps::test_qadd_broadcast, test/test_quantization.py::TestQuantizedOps::test_qadd_relu_different_qparams, test/test_quantization.py::TestQuantizedOps::test_qclamp, test/test_quantization.py::TestQuantizedOps::test_qmatmul, test/test_quantization.py::TestQuantizedOps::test_qprelu, test/test_quantization.py::TestQuantizedOps::test_qsoftmax, test/test_quantization.py::TestQuantizedOps::test_qthreshold, test/test_quantization.py::TestQuantizedOps::test_qtopk, test/test_quantization.py::TestQNNPackOps::test_hardtanh, test/test_quantization.py::TestQuantizedLinear::test_qlinear, test/test_quantization.py::TestQuantizedLinear::test_qlinear_gelu_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_relu_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_sum_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_tanh, test/test_quantization.py::TestQuantizedLinear::test_wrapped_quantized_linear_prepacked, test/test_quantization.py::TestQuantizedConv::test_conv_transpose_reorder_issue_onednn, test/test_quantization.py::TestQuantizedConv::test_qconv1d_cudnn, test/test_quantization.py::TestQuantizedConv::test_qconv1d_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_add, test/test_quantization.py::TestQuantizedConv::test_qconv2d_sum_relu_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv2d_swish_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_unpack, test/test_quantization.py::TestQuantizedConv::test_qconv_transpose3d, test/test_quantization.py::TestDynamicQuantizedOps::test_dynamic_conv3d, test/test_quantization.py::TestDynamicQuantizedOps::test_dynamic_convtranspose2d, test/test_quantization.py::TestDynamicQuantizedOps::test_qlstmGRU, test/test_quantization.py::TestDynamicQuantizedOps::test_qrnncell, test/test_quantization.py::TestComparatorOps::test_compare_tensor_scalar, test/test_quantization.py::TestPadding::test_reflection_pad1d, test/test_quantization.py::TestPadding::test_reflection_pad2d, test/test_quantization.py::TestQuantizedFunctionalOps::test_relu_api, test/test_quantization.py::TestFakeQuantizeOps::test_fake_quantize_per_channel_affine_scale_dtypes, test/test_quantization.py::TestFakeQuantizeOps::test_fake_quantize_per_tensor_affine_inf, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_channel, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_tensor, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_tensor_cachemask_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_backward_per_channel_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_forward_per_channel_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_forward_per_tensor_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_numerical_consistency_per_channel, test/test_quantization.py::TestQuantizedTensor::test_choose_qparams_optimized, test/test_quantization.py::TestQuantizedTensor::test_compare_per_channel_device_numerics, test/test_quantization.py::TestQuantizedTensor::test_compare_per_tensor_device_numerics, test/test_quantization.py::TestQuantizedTensor::test_decomposed_choose_qparams_per_token_asymmetric_backward, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_tensor_bfloat16_input, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_token, test/test_quantization.py::TestQuantizedTensor::test_jit_serialization, test/test_quantization.py::TestQuantizedTensor::test_per_channel_qtensor_creation_cpu, test/test_quantization.py::TestQuantizedTensor::test_per_tensor_qtensor_to_memory_format, test/test_quantization.py::TestQuantizedTensor::test_qtensor_creation, test/test_quantization.py::TestQuantizedTensor::test_qtensor_cuda, test/test_quantization.py::TestQuantizedTensor::test_qtensor_masked_fill_cpu, test/test_quantization.py::TestQuantizedTensor::test_qtensor_per_channel_load_save, test/test_quantization.py::TestQuantizedTensor::test_qtensor_permute, test/test_quantization.py::TestQuantizedTensor::test_qtensor_quant_dequant, test/test_quantization.py::TestQuantizedTensor::test_qtensor_sub_byte_aligned_cols, test/test_quantization.py::TestQuantizedTensor::test_torch_qtensor_deepcopy, test/test_quantization.py::TestFakeQuantize::test_fq_serializable_per_channel, test/test_quantization.py::TestObserver::test_histogram_observer_handle_OOM_due_to_close_min_max_value, test/test_quantization.py::TestObserver::test_histogram_observer_handle_close_to_infinity, test/test_quantization.py::TestObserver::test_observer_qparams_respects_device_affinity, test/test_quantization.py::TestObserver::test_per_channel_observers_load_state_dict, test/test_quantization.py::TestObserver::test_save_load_state_dict_script, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm2d, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm3d_serialization, test/test_quantization.py::TestStaticQuantizedModule::test_conv3d_api, test/test_quantization.py::TestStaticQuantizedModule::test_dropout, test/test_quantization.py::TestStaticQuantizedModule::test_embedding_api, test/test_quantization.py::TestStaticQuantizedModule::test_embedding_bag_api, test/test_quantization.py::TestStaticQuantizedModule::test_linear_relu, test/test_quantization.py::TestStaticQuantizedModule::test_relu, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_conv1d, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_convtranspose3d, test/test_quantization.py::TestDynamicQuantizedModule::test_gru_api, test/test_quantization.py::TestReferenceQuantizedModule::test_linear_decomposed_weight_custom_qmin_qmax, test/test_quantization.py::TestReferenceQuantizedModule::test_rnn_cell, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_against_reference, test/test_quantization.py::TestDistributed::test_observers_preserve_buffers, test/test_quantization.py::TestDistributed::test_qat_convbn_fused_syncbn_replacement, test/test_quantization.py::TestDistributed::test_qat_data_parallel, test/test_quantization.py::TestFusedObsFakeQuantModule::test_compare_fused_obs_fq_oss_module, test/test_quantization.py::TestFusedObsFakeQuantModule::test_fused_mod_per_channel, test/test_quantization.py::TestBackendConfig::test_backend_config_set_backend_pattern_config, test/test_quantization.py::TestBackendConfig::test_backend_op_config_add_dtype_config, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_extra_inputs_getter, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_fused_module, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_reference_quantized_module, test/test_quantization.py::TestUtils::test_get_fqn_to_example_inputs_complex_args, test/test_quantization.py::TestUtils::test_quantize_weight_clamping_per_channel, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_activations, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_forward_hooks_preserved, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_mha_batch_first_attr_is_copied_in_prepare, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_quantized_embedding, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_resnet_base, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_embedding_bag_dynamic, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_nested1, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_nested3, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_quantized_rnn, test/test_quantization.py::TestQuantizeEagerOps::test_conv_1d, test/test_quantization.py::TestQuantizeEagerOps::test_functional_module, test/test_quantization.py::TestQuantizeEagerQAT::test_embedding_qat_qconfig_equal, test/test_quantization.py::TestQuantizeEagerQAT::test_forward_hooks_preserved, test/test_quantization.py::TestQuantizeEagerQAT::test_mul_scalar_uses_input_qparams, test/test_quantization.py::TestQuantizeEagerQAT::test_qat_embedding_bag_errors, test/test_quantization.py::TestQuantizeEagerQAT::test_train_save_load_eval, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_linear_bn_workflow, test/test_quantization.py::TestFuseEager::test_fuse_function_customization, test/test_quantization.py::TestFuseEager::test_fuse_module_train, test/test_quantization.py::TestFuseEager::test_fusion_sequential_model_train, test/test_quantization.py::TestModelNumericsEager::test_float_quant_compare_per_channel, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_functional_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_lstm_dynamic, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_conv_static, test/test_quantization.py::TestNumericSuiteEager::test_shadow_logger, test/test_quantization.py::TestEqualizeEager::test_converged, test/test_quantization.py::TestEqualizeEager::test_equalize_fused_linearrelu, test/test_quantization.py::TestFuseFx::test_fuse_conv_bn_add_relu_by_default, test/test_quantization.py::TestFuseFx::test_fuse_conv_bn_add_relu_lowering, test/test_quantization.py::TestFuseFx::test_fuse_custom_pattern, test/test_quantization.py::TestFuseFx::test_linear_bn_leaky_relu_not_fused_by_default, test/test_quantization.py::TestFuseFx::test_problematic_fuse_example, test/test_quantization.py::TestQuantizeFx::test__convert_to_reference_decomposed_fx, test/test_quantization.py::TestQuantizeFx::test__convert_to_reference_decomposed_fx_per_channel_quant, test/test_quantization.py::TestQuantizeFx::test_backend_config_quantization_range, test/test_quantization.py::TestQuantizeFx::test_backend_config_scale_min, test/test_quantization.py::TestQuantizeFx::test_conv_transpose_relu_not_reference, test/test_quantization.py::TestQuantizeFx::test_convert_custom_config_to_dict, test/test_quantization.py::TestQuantizeFx::test_convert_qconfig_mapping, test/test_quantization.py::TestQuantizeFx::test_copy_node_has_shared_actpp_instance, test/test_quantization.py::TestQuantizeFx::test_custom_module_class_input_has_duplicate_nodes, test/test_quantization.py::TestQuantizeFx::test_dequantize, test/test_quantization.py::TestQuantizeFx::test_dict_output, test/test_quantization.py::TestQuantizeFx::test_dynamic_quant_weight_observer, test/test_quantization.py::TestQuantizeFx::test_fold_quant_dequant, test/test_quantization.py::TestQuantizeFx::test_fp32_input_fp32_output, test/test_quantization.py::TestQuantizeFx::test_fuse_custom_config_from_dict, test/test_quantization.py::TestQuantizeFx::test_fused_module_qat_swap, test/test_quantization.py::TestQuantizeFx::test_fusion_pattern_unquantized, test/test_quantization.py::TestQuantizeFx::test_keep_original_weights, test/test_quantization.py::TestQuantizeFx::test_linear_bn, test/test_quantization.py::TestQuantizeFx::test_linear_qint8_activation, test/test_quantization.py::TestQuantizeFx::test_lowering_functional_conv_with_kwargs, test/test_quantization.py::TestQuantizeFx::test_mixed_dtypes, test/test_quantization.py::TestQuantizeFx::test_observer_fqn, test/test_quantization.py::TestQuantizeFx::test_packed_weight_fused_op, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_non_traceable_module_classes, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_standalone_module_class, test/test_quantization.py::TestQuantizeFx::test_preserve_qconfig, test/test_quantization.py::TestQuantizeFx::test_preserve_tuple, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_dict_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_dict_tuple_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_tuple_args, test/test_quantization.py::TestQuantizeFx::test_qconfig_for_call_method, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_from_dict, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_object_type, test/test_quantization.py::TestQuantizeFx::test_qconfig_module_type, test/test_quantization.py::TestQuantizeFx::test_qconfig_none, test/test_quantization.py::TestQuantizeFx::test_qconfig_precedence, test/test_quantization.py::TestQuantizeFx::test_quantized_input_quantized_output, test/test_quantization.py::TestQuantizeFx::test_quantized_model_type, test/test_quantization.py::TestQuantizeFx::test_remove_qconfig, test/test_quantization.py::TestQuantizeFx::test_return_none, test/test_quantization.py::TestQuantizeFx::test_reuse_input_qconfig, test/test_quantization.py::TestQuantizeFx::test_stack_trace_preserved_linear, test/test_quantization.py::TestQuantizeFx::test_symmetric_qnnpack_qat_qconfig_mapping, test/test_quantization.py::TestQuantizeFx::test_torch_unsqueeze_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_unsqueeze__nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFxOps::test_boolean_tensor, test/test_quantization.py::TestQuantizeFxOps::test_conv_module, test/test_quantization.py::TestQuantizeFxOps::test_embedding, test/test_quantization.py::TestQuantizeFxOps::test_hardswish, test/test_quantization.py::TestQuantizeFxOps::test_instance_norm, test/test_quantization.py::TestQuantizeFxOps::test_mish_reference, test/test_quantization.py::TestQuantizeFxOps::test_qbatch_norm, test/test_quantization.py::TestQuantizeFxOps::test_quantized_mul_qat, test/test_quantization.py::TestQuantizeFxOps::test_rnn, test/test_quantization.py::TestQuantizeFxOps::test_softmax_reference, test/test_quantization.py::TestQuantizeFxOps::test_sum, test/test_quantization.py::TestQuantizeFxModels::test_qat_functional_linear, test/test_quantization.py::TestQuantizeFxModels::test_resnet18_ddp, test/test_quantization.py::TestQuantizeFxModels::test_resnet_base, test/test_quantization.py::TestQuantizeFxModels::test_switch_device_prepare_convert, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_quantization.py::TestGraphUtils::test_conv_bn_conv_relu, test/test_quantization.py::TestDuplicateDQPass::test_avgpool_use_different_qconfig, test/test_quantization.py::TestDuplicateDQPass::test_no_add_quant_duplicate_dq, test/test_quantization.py::TestMetaDataPorting::test_metadata_porting_for_dq_no_static_q, test/test_quantization.py::TestMetaDataPorting::test_metadata_porting_with_no_quant_inbetween, test/test_quantization.py::TestMetaDataPorting::test_simple_metadata_porting, test/test_quantization.py::TestNumericDebugger::test_extract_results_from_loggers_list_output, test/test_quantization.py::TestQuantizePT2E::test_composable_quantizer_throw, test/test_quantization.py::TestQuantizePT2E::test_conv_transpose_bn_relu, test/test_quantization.py::TestQuantizePT2E::test_derived_qspec, test/test_quantization.py::TestQuantizePT2E::test_derived_qspec_per_channel, test/test_quantization.py::TestQuantizePT2E::test_embedding_conv_linear_quantization, test/test_quantization.py::TestQuantizePT2E::test_embedding_quantizer, test/test_quantization.py::TestQuantizePT2E::test_fixed_qparams_qspec_ptq, test/test_quantization.py::TestQuantizePT2E::test_fixed_qparams_qspec_qat, test/test_quantization.py::TestQuantizePT2E::test_observer_callback, test/test_quantization.py::TestQuantizePT2E::test_preserve_nn_module_stack, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_float32_float8_e4m3fn, test/test_quantization.py::TestQuantizePT2E::test_shared_qspec, test/test_quantization.py::TestQuantizePT2E::test_shared_qspec_transitivity, test/test_quantization.py::TestPT2ERepresentation::test_add, test/test_quantization.py::TestPT2ERepresentation::test_conv2d, test/test_quantization.py::TestXNNPACKQuantizer::test_conv1d, test/test_quantization.py::TestXNNPACKQuantizer::test_conv1d_with_conv2d, test/test_quantization.py::TestXNNPACKQuantizer::test_conv_linear_no_permute, test/test_quantization.py::TestXNNPACKQuantizer::test_dynamic_linear_int4_weight, test/test_quantization.py::TestXNNPACKQuantizer::test_linear, test/test_quantization.py::TestXNNPACKQuantizer::test_set_module_type, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_cat_recipe_same_inputs, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_conv2d_binary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_conv2d_binary2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_dynamic_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_unary_dynamic, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_conv2d_binary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_qconfig, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_qconfig_for_dynamic_quant, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_fold_bn_erases_add_node, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion_cuda, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_relu_fusion_no_conv_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_update_shared_qspec, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_fold_bn_erases_add_node, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_bias_derived_qspec, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_fusion_literal_args, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_per_channel_weight_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_no_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_update_shared_qspec, test/test_quantization.py::TestQuantizePT2EQATModels::test_qat_mobilenet_v2, test/test_quantization.py::TestFXGraphMatcher::test_dict_return_type, test/test_quantization.py::TestFXGraphMatcher::test_methods, test/test_quantization.py::TestFXGraphMatcher::test_nodes_before_cat, test/test_quantization.py::TestFXGraphMatcher::test_simple_mod, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_loggers_cuda, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extend_logger_results_with_comparison, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extract_weights_linear_fun_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_fp16_weights, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_loggers_preserve_qat_numerics, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_logging_inputs, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_fqn, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_unsupported_op_copy_skips_shadowing, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_user_module_scriptable, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_conv_bn_relu_fusion_fp32, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_linear_mod_quant_quant, test/test_quantization.py::TestFXNumericSuiteNShadows::test_linear_relu_mod, test/test_quantization.py::TestFXNumericSuiteNShadows::test_partial_qconfig_mapping, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_retroactive_padding, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_mobilenet_v2, test/test_quantization.py::TestFxModelReportDetector::test_multiple_q_config_options, test/test_quantization.py::TestFxModelReportDetector::test_sequential_model_format, test/test_quantization.py::TestFxModelReportObserver::test_random_epochs_and_batches, test/test_quantization.py::TestFxModelReportDetectDynamicStatic::test_nested_detection_case, test/test_quantization.py::TestFxDetectInputWeightEqualization::test_input_weight_equalization_determine_points, test/test_quantization.py::TestFxDetectOutliers::test_no_outlier_report_gen, test/test_quantization.py::TestFxModelReportVisualizer::test_generate_tables_match_with_report, test/test_quantization.py::TestFxModelReportVisualizer::test_generate_tables_single_feat_match, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_convert, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_equalization_scales, test/test_quantization.py::TestSerialization::test_conv2d_graph_v2, test/test_quantization.py::TestSerialization::test_conv2d_nobias_graph_v2, test/test_quantization.py::TestSerialization::test_conv3d_relu, test/test_quantization.py::TestSerialization::test_linear, test/test_quantization.py::TestQuantizeJit::test_nested, test/test_quantization.py::TestQuantizeJit::test_skip_quant, test/test_quantization.py::TestQuantizeJitPasses::test_finalize_debug, test/test_quantization.py::TestQuantizeJitPasses::test_foldbn_shared_classtype, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_if, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_interface_unshare_type, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_propagate_observed_for_function, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_shared_class_type, test/test_quantization.py::TestQuantizeJitPasses::test_insert_quant_dequant_shared_class_type, test/test_quantization.py::TestQuantizeJitPasses::test_interface_with_fork, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_dequantize, test/test_quantization.py::TestQuantizeJitOps::test_clamp, test/test_quantization.py::TestQuantizeJitOps::test_conv_with_benchmark_flag, test/test_quantization.py::TestQuantizeJitOps::test_elu, test/test_quantization.py::TestQuantizeJitOps::test_hardswish, test/test_quantization.py::TestQuantizeJitOps::test_layer_norm, test/test_quantization.py::TestQuantizeJitOps::test_qbatch_norm_relu_BNFuncRelu, test/test_quantization.py::TestQuantizeJitOps::test_quantized_add, test/test_quantization.py::TestQuantizeJitOps::test_quantized_add_relu_alpha, test/test_quantization.py::TestQuantizeJitOps::test_quantized_add_scalar_relu, test/test_quantization.py::TestQuantizeJitOps::test_quantized_mul_scalar_relu, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_multi_op, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_prepare_dynamic_child_qconfig, test/test_quantization.py::TestQuantizeDynamicJitOps::test_embedding_bag_padding_idx_error, test/test_quantization.py::TestFusionPasses::test_quantized_add_relu_fusion, test/test_quantization.py::TestDeprecatedJitQuantized::test_erase_class_tensor_shapes, test/test_quantization.py::TestDeprecatedJitQuantized::test_quantization_modules, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_fake_quantize, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quantization_mappings, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_qat_embedding_ops, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_qat_linear, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_quantizable_rnn, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_activation, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_linear, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_normalization, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_import_nn_intrinsic_quantized, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_pattern_utils, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_quantization_patterns, test/test_quantization.py::TestBitsCPU::test_subclass_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_extremes_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_soak_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_soak_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_finfo_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_type_promotion_fails_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_type_promotion_fails_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_type_promotion_fails_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPUOnlyCPU::test_mul_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPUOnlyCPU::test_pt2_traceable_aot_eager_cpu_float8_e4m3fn
2025-08-14T22:11:33.5259490Z 
2025-08-14T22:11:34.3031067Z Uploading artifacts took 0.80 seconds
2025-08-14T22:11:37.8937025Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:11:37.8939765Z   import pkg_resources
2025-08-14T22:11:38.0198959Z Running dynamo/cpython/3_13/test_defaultdict 1/1 ... [2025-08-14 22:11:38.019425]
2025-08-14T22:11:38.0200262Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:11:38.0203085Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/cpython/3_13/test_defaultdict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:11:38.019828]
2025-08-14T22:11:42.7352661Z 
2025-08-14T22:11:42.7354634Z dynamo/cpython/3_13/test_defaultdict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.cpython.3_13.test_defaultdict_1.1_52d4488d7479af75_.log
2025-08-14T22:11:42.7363987Z Running 11 items in this shard: test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_basic, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_callable_arg, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_copy, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_deep_copy, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_keyerror_without_factory, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_missing, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_pickling, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_recursive_repr, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_repr, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_shallow_copy, test/dynamo/cpython/3_13/test_defaultdict.py::TestDefaultDict::test_union
2025-08-14T22:11:42.7371868Z 
2025-08-14T22:11:47.0180865Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:11:47.0183943Z   import pkg_resources
2025-08-14T22:11:47.2096171Z Running test_transformers 2/3 ... [2025-08-14 22:11:47.209189]
2025-08-14T22:11:47.2097949Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:11:47.2103253Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'not serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:11:47.209653]
2025-08-14T22:12:00.4729726Z 
2025-08-14T22:12:00.4731114Z test_quantization 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_2.4_7b91ac77b43b86de_.log
2025-08-14T22:12:00.4954898Z Running 313 items in this shard: test/test_quantization.py::TestQuantizedOps::test_advanced_indexing, test/test_quantization.py::TestQuantizedOps::test_avg_pool2d, test/test_quantization.py::TestQuantizedOps::test_avg_pool3d_nhwc, test/test_quantization.py::TestQuantizedOps::test_batch_norm, test/test_quantization.py::TestQuantizedOps::test_cat, test/test_quantization.py::TestQuantizedOps::test_empty_batch, test/test_quantization.py::TestQuantizedOps::test_hardtanh, test/test_quantization.py::TestQuantizedOps::test_interpolate3d, test/test_quantization.py::TestQuantizedOps::test_leaky_relu, test/test_quantization.py::TestQuantizedOps::test_max_pool2d_nhwc, test/test_quantization.py::TestQuantizedOps::test_qadd_relu_cudnn, test/test_quantization.py::TestQuantizedOps::test_qadd_relu_cudnn_nhwc, test/test_quantization.py::TestQuantizedOps::test_qcelu, test/test_quantization.py::TestQuantizedOps::test_qelu, test/test_quantization.py::TestQuantizedOps::test_qgelu, test/test_quantization.py::TestQuantizedOps::test_qmul_broadcast, test/test_quantization.py::TestQuantizedOps::test_qrelu6, test/test_quantization.py::TestQuantizedOps::test_qtanh, test/test_quantization.py::TestQuantizedOps::test_std, test/test_quantization.py::TestQNNPackOps::test_mean, test/test_quantization.py::TestQNNPackOps::test_qnnpack_add, test/test_quantization.py::TestQNNPackOps::test_qnnpack_mul, test/test_quantization.py::TestQNNPackOps::test_qnnpack_relu, test/test_quantization.py::TestQNNPackOps::test_qnnpack_tanh, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_relu_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_gelu_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_qnnpack_free_memory_and_unpack, test/test_quantization.py::TestQuantizedLinear::test_qlinear_sum_relu_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv1d, test/test_quantization.py::TestQuantizedConv::test_qconv1d_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu_cudnn, test/test_quantization.py::TestQuantizedConv::test_qconv1d_unpack, test/test_quantization.py::TestQuantizedConv::test_qconv2d_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_hardtanh_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv2d_relu_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv3d, test/test_quantization.py::TestQuantizedConv::test_qconv3d_fp8, test/test_quantization.py::TestDynamicQuantizedOps::test_dynamic_convtranspose3d, test/test_quantization.py::TestDynamicQuantizedOps::test_qlinear, test/test_quantization.py::TestDynamicQuantizedOps::test_wrapped_fbgemm_linear_fp16, test/test_quantization.py::TestDynamicQuantizedOps::test_wrapped_fbgemm_pack_gemm_matrix_fp16_pt2_compliant, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_2d_indices, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_bag_2bit, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_bag_byte, test/test_quantization.py::TestQuantizedFunctionalOps::test_conv2d_api, test/test_quantization.py::TestQuantizedFunctionalOps::test_conv3d_api, test/test_quantization.py::TestQuantizedFunctionalOps::test_grid_sample, test/test_quantization.py::TestFakeQuantizeOps::test_backward_per_tensor, test/test_quantization.py::TestFakeQuantizeOps::test_backward_per_tensor_cachemask_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_fixed_qparams_fq_module, test/test_quantization.py::TestFakeQuantizeOps::test_forward_backward_per_tensor_with_amp, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_channel_cachemask_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_tensor_cachemask_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_backward_per_channel_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_forward_per_channel_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_numerical_consistency_per_tensor, test/test_quantization.py::TestFusedObsFakeQuant::test_fused_obs_fake_quant_moving_avg, test/test_quantization.py::TestQuantizedTensor::test_clone, test/test_quantization.py::TestQuantizedTensor::test_cuda_quantization_does_not_pin_memory, test/test_quantization.py::TestQuantizedTensor::test_decomposed_dequantize_per_tensor, test/test_quantization.py::TestQuantizedTensor::test_dequantize_fp16_cpu, test/test_quantization.py::TestQuantizedTensor::test_per_channel_to_device, test/test_quantization.py::TestQuantizedTensor::test_qscheme_pickle, test/test_quantization.py::TestQuantizedTensor::test_qtensor_cpu, test/test_quantization.py::TestQuantizedTensor::test_qtensor_dtypes, test/test_quantization.py::TestQuantizedTensor::test_qtensor_equal, test/test_quantization.py::TestQuantizedTensor::test_qtensor_fill_per_channel_nhwc, test/test_quantization.py::TestQuantizedTensor::test_qtensor_fill_per_tensor_nhwc, test/test_quantization.py::TestQuantizedTensor::test_qtensor_index_put_cuda, test/test_quantization.py::TestQuantizedTensor::test_qtensor_int_repr, test/test_quantization.py::TestQuantizedTensor::test_qtensor_resize, test/test_quantization.py::TestQuantizedTensor::test_qtensor_unsqueeze, test/test_quantization.py::TestQuantizedTensor::test_quantize_per_channel_sub_byte, test/test_quantization.py::TestFakeQuantize::test_fq_module_per_channel, test/test_quantization.py::TestObserver::test_dynamic_quant_observer, test/test_quantization.py::TestObserver::test_histogram_observer_save_load_state_dict, test/test_quantization.py::TestObserver::test_per_tensor_observers, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm3d, test/test_quantization.py::TestStaticQuantizedModule::test_linear_tanh, test/test_quantization.py::TestStaticQuantizedModule::test_sigmoid, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_conv3d, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_convtranspose1d, test/test_quantization.py::TestDynamicQuantizedModule::test_linear_api, test/test_quantization.py::TestDynamicQuantizedModule::test_lstm_api, test/test_quantization.py::TestRecordHistogramObserver::test_record_observer, test/test_quantization.py::TestHistogramObserver::test_histogram_observer, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_correct_numel, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_same_inputs, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_single_inputs, test/test_quantization.py::TestFusedObsFakeQuantModule::test_fused_obs_fq_module, test/test_quantization.py::TestBackendConfig::test_backend_config_from_dict, test/test_quantization.py::TestBackendConfig::test_backend_config_set_name, test/test_quantization.py::TestBackendConfig::test_backend_op_config_from_dict, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_root_module, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_root_node_getter, test/test_quantization.py::TestBackendConfig::test_backend_op_config_to_dict, test/test_quantization.py::TestUtils::test_get_fqn_to_example_inputs_default_kwargs, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_activations_in_non_leaf_module_list, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_dequant_stub, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_manual, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_nested3, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_linear_relu_fusion, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_nested2, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_quantized_rnn_cell, test/test_quantization.py::TestQuantizeEagerOps::test_conv_transpose_3d, test/test_quantization.py::TestQuantizeEagerOps::test_leaky_relu, test/test_quantization.py::TestQuantizeEagerQAT::test_add_scalar_uses_input_qparams, test/test_quantization.py::TestQuantizeEagerQAT::test_conv_linear, test/test_quantization.py::TestQuantizeEagerQAT::test_dropout, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_leaky_relu, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_relu, test/test_quantization.py::TestFuseEager::test_fusion_convtranspose_bn_eval, test/test_quantization.py::TestFuseEager::test_fusion_linear_bn_eval, test/test_quantization.py::TestModelNumericsEager::test_fake_quant_true_quant_compare, test/test_quantization.py::TestModelNumericsEager::test_weight_only_activation_only_fakequant, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_conv_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_functional_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_conv_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_submodule_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_linear_dynamic, test/test_quantization.py::TestNumericSuiteEager::test_mobilenet_v2, test/test_quantization.py::TestBiasCorrectionEager::test_linear_chain, test/test_quantization.py::TestFuseFx::test_fuse_convtranspose_bn_eval, test/test_quantization.py::TestFuseFx::test_fusion_pattern_with_multiple_inputs, test/test_quantization.py::TestQuantizeFx::test_attention, test/test_quantization.py::TestQuantizeFx::test_convert_custom_config_set_preserved_attributes, test/test_quantization.py::TestQuantizeFx::test_convtranspose_per_channel_fails_early, test/test_quantization.py::TestQuantizeFx::test_custom_module_class_input_has_multiple_users, test/test_quantization.py::TestQuantizeFx::test_dynamic_linear_input_multiple_use, test/test_quantization.py::TestQuantizeFx::test_get_default_qconfig_valid_backend, test/test_quantization.py::TestQuantizeFx::test_getattr_with_nontensor_result, test/test_quantization.py::TestQuantizeFx::test_linear_leaky_relu_lowering, test/test_quantization.py::TestQuantizeFx::test_lowering_functional_linear_with_kwargs, test/test_quantization.py::TestQuantizeFx::test_not_used, test/test_quantization.py::TestQuantizeFx::test_pattern_match_constant, test/test_quantization.py::TestQuantizeFx::test_permute_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_float_to_observed_mapping, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_to_dict, test/test_quantization.py::TestQuantizeFx::test_prepare_mode, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_list_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_split_list_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_split_tuple_args, test/test_quantization.py::TestQuantizeFx::test_qconfig_function, test/test_quantization.py::TestQuantizeFx::test_qconfig_module_name_object_type_order, test/test_quantization.py::TestQuantizeFx::test_qnnpack_backend_config, test/test_quantization.py::TestQuantizeFx::test_qparams_buffers, test/test_quantization.py::TestQuantizeFx::test_ref_linear_module, test/test_quantization.py::TestQuantizeFx::test_save_observer_state_dict, test/test_quantization.py::TestQuantizeFx::test_shape_followed_by_quantized_op, test/test_quantization.py::TestQuantizeFx::test_standalone_module_float_interface, test/test_quantization.py::TestQuantizeFx::test_standalone_module_quantized_interface, test/test_quantization.py::TestQuantizeFx::test_state_dict, test/test_quantization.py::TestQuantizeFx::test_static_lstm_consume_tuple, test/test_quantization.py::TestQuantizeFx::test_symmetric_qnnpack_qconfig_mapping, test/test_quantization.py::TestQuantizeFx::test_torch_transpose_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_view_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFxOps::test_add_relu, test/test_quantization.py::TestQuantizeFxOps::test_add_relu_multiple_uses_of_relu, test/test_quantization.py::TestQuantizeFxOps::test_ave_pool_with_custom_cfg, test/test_quantization.py::TestQuantizeFxOps::test_cat, test/test_quantization.py::TestQuantizeFxOps::test_chunk, test/test_quantization.py::TestQuantizeFxOps::test_conv_transpose_2d, test/test_quantization.py::TestQuantizeFxOps::test_copy_node_fp32_input, test/test_quantization.py::TestQuantizeFxOps::test_div, test/test_quantization.py::TestQuantizeFxOps::test_elu, test/test_quantization.py::TestQuantizeFxOps::test_fixed_qparams_ops, test/test_quantization.py::TestQuantizeFxOps::test_gelu_normal, test/test_quantization.py::TestQuantizeFxOps::test_int8_input_no_unnecessary_fq, test/test_quantization.py::TestQuantizeFxOps::test_layer_norm, test/test_quantization.py::TestQuantizeFxOps::test_leaky_relu, test/test_quantization.py::TestQuantizeFxOps::test_linear_dynamic_fp16, test/test_quantization.py::TestQuantizeFxOps::test_norm_weight_bias, test/test_quantization.py::TestQuantizeFxOps::test_quantized_add_qat, test/test_quantization.py::TestQuantizeFxOps::test_quantized_conv_relu, test/test_quantization.py::TestQuantizeFxOps::test_silu_reference, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_writer_replace_consecutive_submodules, test/test_quantization.py::TestGraphUtils::test_conv_bn_relu, test/test_quantization.py::TestDuplicateDQPass::test_simple_duplicate_dq, test/test_quantization.py::TestNumericDebugger::test_control_flow, test/test_quantization.py::TestNumericDebugger::test_prepare_for_propagation_comparison, test/test_quantization.py::TestQuantizePT2E::test_allow_exported_model_train_eval, test/test_quantization.py::TestQuantizePT2E::test_allow_exported_model_train_eval_idempotent, test/test_quantization.py::TestQuantizePT2E::test_conv_padding_bn_relu, test/test_quantization.py::TestQuantizePT2E::test_disallow_eval_train, test/test_quantization.py::TestQuantizePT2E::test_dont_fold_other_constant, test/test_quantization.py::TestQuantizePT2E::test_max_pool2d_quantizer, test/test_quantization.py::TestQuantizePT2E::test_prepare_obs_or_fq_callback, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_bfloat16_float8_e4m3fn, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_bfloat16_float8_e5m2, test/test_quantization.py::TestQuantizePT2E::test_reentrant, test/test_quantization.py::TestQuantizePT2E::test_simple_quantizer, test/test_quantization.py::TestQuantizePT2EAffineQuantization::test_channel_group_quantization, test/test_quantization.py::TestPT2ERepresentation::test_dynamic_linear, test/test_quantization.py::TestPT2ERepresentation::test_qdq_per_channel, test/test_quantization.py::TestPT2ERepresentation::test_static_linear, test/test_quantization.py::TestXNNPACKQuantizer::test_mul_and_inplace_mul, test/test_quantization.py::TestXNNPACKQuantizer::test_obs_sharing_ops, test/test_quantization.py::TestXNNPACKQuantizer::test_qat_dynamic_linear, test/test_quantization.py::TestXNNPACKQuantizerModels::test_resnet18, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_conv2d_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_dynamic_quant_linear, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_filter_conv2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_flatten_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_flatten_recipe2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_dynamic_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_serials, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_unary_dynamic_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_lowering_to_x86, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_maxpool2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_dynamic_quant_linear, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_and_module_type_case2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_and_module_type_with_mixed_configs, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_qconfig_with_underscores, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_with_mixed_configs, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion_literal_args, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_per_channel_weight_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_transpose_bn, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_inplace_add_relu, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_preserve_source_fn_stack, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_fusion, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_relu_fusion_cuda, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_preserve_source_fn_stack, test/test_quantization.py::TestFXGraphMatcher::test_simple_fun, test/test_quantization.py::TestFXGraphMatcher::test_simple_fusion, test/test_quantization.py::TestFXGraphMatcher::test_simple_tensor_ops, test/test_quantization.py::TestFXGraphMatcherModels::test_mobilenet_v2, test/test_quantization.py::TestFXGraphMatcherModels::test_mobilenet_v2_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_cuda, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_meth_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extract_weights_cuda, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_layer_names, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_fp16_activations, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_fun_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_mul_add_cat_stack_skips_shadowing, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_user_defined_function, test/test_quantization.py::TestFXNumericSuiteNShadows::test_conv_bn_relu_mod, test/test_quantization.py::TestFXNumericSuiteNShadows::test_functions, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_deduplication, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_insert_padding, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_ordering, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_activations_linear, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_activations_lstm_dynamic, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_shadow_activations_lstm_dynamic, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_weights_conv, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_weights_linear, test/test_quantization.py::TestFxModelReportDetector::test_multi_linear_model_without_per_channel, test/test_quantization.py::TestFxModelReportDetector::test_simple_conv, test/test_quantization.py::TestFxModelReportObserver::test_zero_tensor_errors, test/test_quantization.py::TestFxModelReportClass::test_equalization_mapping_generation, test/test_quantization.py::TestFxModelReportClass::test_generate_report, test/test_quantization.py::TestFxDetectInputWeightEqualization::test_input_weight_equalization_report_gen, test/test_quantization.py::TestFxDetectOutliers::test_all_outlier_report_gen, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_prepare, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_weights_bias, test/test_quantization.py::TestSerialization::test_conv2d_graph, test/test_quantization.py::TestSerialization::test_conv2d_graph_v3, test/test_quantization.py::TestSerialization::test_conv2d_nobias_graph, test/test_quantization.py::TestSerialization::test_conv2d_nobias_graph_v3, test/test_quantization.py::TestSerialization::test_conv2d_relu, test/test_quantization.py::TestSerialization::test_default_qat_qconfig, test/test_quantization.py::TestSerialization::test_linear_relu, test/test_quantization.py::TestQuantizeJitPasses::test_conv_trace, test/test_quantization.py::TestQuantizeJitPasses::test_dedup_module_uses, test/test_quantization.py::TestQuantizeJitPasses::test_finalize_for_linear, test/test_quantization.py::TestQuantizeJitPasses::test_foldbn_trivial_nobias, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_if_consistent_observation, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_dequantize_in_block, test/test_quantization.py::TestQuantizeJitOps::test_instance_norm, test/test_quantization.py::TestQuantizeJitOps::test_linear, test/test_quantization.py::TestQuantizeJitOps::test_quantized_cat, test/test_quantization.py::TestQuantizeJitOps::test_quantized_mul, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_quant_multi_uses, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_weight_observer, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_with_if, test/test_quantization.py::TestQuantizeDynamicJitOps::test_embedding_bag, test/test_quantization.py::TestDeprecatedJitQuantized::test_rnn_cell_quantized, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quantize, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_stubs, test/test_quantization.py::TestAOMigrationNNQuantized::test_functional_import, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_qat_dynamic_linear, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_dropout, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_qat_conv_fused, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_quantized_bn_relu, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_quantized_linear_relu, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_fuse, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_graph_module, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_match_utils, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_quantize_fx, test/test_quantization.py::TestBitsCPU::test_cat_cpu, test/test_quantization.py::TestBitsCPU::test_types_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_extremes_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_rte_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_rte_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_soak_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e4m3fnuz
2025-08-14T22:12:00.5150001Z 
2025-08-14T22:12:04.8206042Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:12:04.8210324Z   import pkg_resources
2025-08-14T22:12:04.9766920Z Running test_transformers 3/3 ... [2025-08-14 22:12:04.976143]
2025-08-14T22:12:04.9768127Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:12:04.9775690Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'not serial', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:12:04.976796]
2025-08-14T22:13:39.6085328Z 
2025-08-14T22:13:39.6086788Z test_quantization 3/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_3.4_8bcab25c00c9e9f8_.log
2025-08-14T22:13:39.6451659Z Running 359 items in this shard: test/test_quantization.py::TestQuantizedOps::test_avg_pool2d_nhwc, test/test_quantization.py::TestQuantizedOps::test_batch_norm_relu, test/test_quantization.py::TestQuantizedOps::test_cat_nhwc, test/test_quantization.py::TestQuantizedOps::test_channel_shuffle, test/test_quantization.py::TestQuantizedOps::test_equal, test/test_quantization.py::TestQuantizedOps::test_interpolate, test/test_quantization.py::TestQuantizedOps::test_max_pool2d_cudnn, test/test_quantization.py::TestQuantizedOps::test_max_pool3d, test/test_quantization.py::TestQuantizedOps::test_qhardsigmoid, test/test_quantization.py::TestQuantizedOps::test_qmul_relu_different_qparams, test/test_quantization.py::TestQuantizedOps::test_qrelu, test/test_quantization.py::TestQuantizedOps::test_qsoftmax_qnnpack, test/test_quantization.py::TestQuantizedOps::test_sigmoid_dequantize_rounding_error, test/test_quantization.py::TestQuantizedOps::test_sigmoid_non_observed, test/test_quantization.py::TestQNNPackOps::test_avg_pool2d, test/test_quantization.py::TestQNNPackOps::test_qnnpack_maxpool2d, test/test_quantization.py::TestQNNPackOps::test_qnnpack_sigmoid_sweep, test/test_quantization.py::TestQuantizedLinear::test_qlinear_cudnn, test/test_quantization.py::TestQuantizedLinear::test_qlinear_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_relu_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_sum_relu_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_unpack, test/test_quantization.py::TestQuantizedConv::test_benchmark, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv2d_add_relu, test/test_quantization.py::TestQuantizedConv::test_qconv2d_hardswish_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_relu, test/test_quantization.py::TestQuantizedConv::test_qconv2d_relu_cudnn, test/test_quantization.py::TestQuantizedConv::test_qconv2d_relu_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_sum_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv2d_sum_relu_float_output_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv3d_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv3d_relu, test/test_quantization.py::TestQuantizedConv::test_qconv_transpose1d, test/test_quantization.py::TestDynamicQuantizedOps::test_dynamic_convtranspose1d, test/test_quantization.py::TestDynamicQuantizedOps::test_qlinear_dynamic_fp16, test/test_quantization.py::TestDynamicQuantizedOps::test_unpacked_qlinear_dynamic_fp16, test/test_quantization.py::TestDynamicQuantizedOps::test_unpacked_qlinear_dynamic_fp16_opcheck, test/test_quantization.py::TestQuantizedFunctionalOps::test_conv1d_api, test/test_quantization.py::TestFakeQuantizeOps::test_backward_per_tensor_cachemask_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_fake_quant_control, test/test_quantization.py::TestFakeQuantizeOps::test_fake_quant_preserves_qparam_shapes_for_activations, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_channel_cachemask_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_tensor_half_precision_numerics, test/test_quantization.py::TestFakeQuantizeOps::test_fq_serializable_per_tensor, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_backward_per_tensor_cuda, test/test_quantization.py::TestFusedObsFakeQuant::test_fused_backward_op_fake_quant_off, test/test_quantization.py::TestFusedObsFakeQuant::test_fused_obs_fake_quant_backward_op, test/test_quantization.py::TestQuantizedTensor::test_bfp16_quantize, test/test_quantization.py::TestQuantizedTensor::test_choose_qparams, test/test_quantization.py::TestQuantizedTensor::test_decomposed_dequantize_per_channel, test/test_quantization.py::TestQuantizedTensor::test_decomposed_dynamic_quant_pattern, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_channel_bfloat16_input, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_channel_group, test/test_quantization.py::TestQuantizedTensor::test_decomposed_quantize_per_tensor, test/test_quantization.py::TestQuantizedTensor::test_fp16_saturate_op, test/test_quantization.py::TestQuantizedTensor::test_per_channel_qtensor_to_memory_format, test/test_quantization.py::TestQuantizedTensor::test_pickle_checkpoint_qtensor, test/test_quantization.py::TestQuantizedTensor::test_qtensor_index_put_cpu, test/test_quantization.py::TestQuantizedTensor::test_qtensor_legacy_new_failure, test/test_quantization.py::TestQuantizedTensor::test_qtensor_per_channel_permute, test/test_quantization.py::TestQuantizedTensor::test_quantize_per_channel_float_qparams, test/test_quantization.py::TestFakeQuantize::test_quant_min_max_override, test/test_quantization.py::TestObserver::test_dynamic_quant_observer_matching_choose_qparams, test/test_quantization.py::TestObserver::test_histogram_observer_ignore_infinity, test/test_quantization.py::TestObserver::test_observer_scriptable, test/test_quantization.py::TestObserver::test_per_channel_observers, test/test_quantization.py::TestObserver::test_state_dict_respects_device_affinity, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm2d_serialization, test/test_quantization.py::TestStaticQuantizedModule::test_conv2d_add_relu, test/test_quantization.py::TestStaticQuantizedModule::test_conv2d_api, test/test_quantization.py::TestStaticQuantizedModule::test_conv2d_relu_api, test/test_quantization.py::TestStaticQuantizedModule::test_conv3d_relu_api, test/test_quantization.py::TestStaticQuantizedModule::test_dropout_serialization, test/test_quantization.py::TestStaticQuantizedModule::test_elu, test/test_quantization.py::TestStaticQuantizedModule::test_group_norm, test/test_quantization.py::TestStaticQuantizedModule::test_hard_swish, test/test_quantization.py::TestStaticQuantizedModule::test_linear, test/test_quantization.py::TestStaticQuantizedModule::test_linear_leaky_relu, test/test_quantization.py::TestStaticQuantizedModule::test_quant_dequant_api, test/test_quantization.py::TestDynamicQuantizedModule::test_cell_api, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_convtranspose2d, test/test_quantization.py::TestReferenceQuantizedModule::test_sparse, test/test_quantization.py::TestRecordHistogramObserver::test_observer_scriptable, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_extreme_inputs, test/test_quantization.py::TestHistogramObserver::test_observer_scriptable, test/test_quantization.py::TestDistributed::test_syncbn_preserves_qconfig, test/test_quantization.py::TestFusedObsFakeQuantModule::test_default_fused_qat_config, test/test_quantization.py::TestFusedObsFakeQuantModule::test_embedding_bag_qat_config, test/test_quantization.py::TestBackendConfig::test_backend_config_to_dict, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_num_tensor_args_to_observation_type, test/test_quantization.py::TestBackendConfig::test_dtype_config_from_dict, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_convtranspose_per_channel_fails_early, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_nested1, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_nested2, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_normalization, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_save_load_state_dict, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_embedding_ops_dynamic, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_single_layer, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_two_layers, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_type_match_rule, test/test_quantization.py::TestQuantizeEagerOps::test_conv_2d, test/test_quantization.py::TestQuantizeEagerOps::test_conv_3d, test/test_quantization.py::TestQuantizeEagerOps::test_conv_transpose_1d, test/test_quantization.py::TestQuantizeEagerOps::test_int16_reference_module, test/test_quantization.py::TestQuantizeEagerOps::test_linear, test/test_quantization.py::TestQuantizeEagerOps::test_relu, test/test_quantization.py::TestQuantizeEagerQAT::test_conv_linear_symm, test/test_quantization.py::TestQuantizeEagerQAT::test_dynamic_qat_linear, test/test_quantization.py::TestQuantizeEagerQAT::test_eval_only_fake_quant, test/test_quantization.py::TestQuantizeEagerQAT::test_manual, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_conv_bn_folded_vs_unfolded, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_conv_bn_relu, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_fixed_qparam_ops, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_linear_precomputed_fake_quant, test/test_quantization.py::TestFuseEager::test_forward_hooks_preserved, test/test_quantization.py::TestFuseEager::test_fusion_sequential_model_eval, test/test_quantization.py::TestModelNumericsEager::test_float_quant_compare_per_tensor, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_linear_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_linear_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_partial, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_linear_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_lstm_dynamic, test/test_quantization.py::TestNumericSuiteEager::test_output_logger, test/test_quantization.py::TestFuseFx::test_fuse_addtional_fuser_method, test/test_quantization.py::TestFuseFx::test_fuse_conv_bn_add_relu_onednn, test/test_quantization.py::TestFuseFx::test_fuse_linear_bn_eval, test/test_quantization.py::TestFuseFx::test_fuse_linear_bn_leaky_relu_onednn, test/test_quantization.py::TestFuseFx::test_fuse_linear_tanh_for_onednn_backend, test/test_quantization.py::TestFuseFx::test_fuse_module_relu, test/test_quantization.py::TestFuseFx::test_fusion_pattern_with_matchallnode, test/test_quantization.py::TestFuseFx::test_linear_tanh_not_fused_by_default, test/test_quantization.py::TestFuseFx::test_qconfig_fused_module, test/test_quantization.py::TestQuantizeFx::test__convert_to_reference_decomposed_fx_dynamic_quant, test/test_quantization.py::TestQuantizeFx::test_assert_on_size_after_quant_layer, test/test_quantization.py::TestQuantizeFx::test_backend_config_check_for_weight_and_bias, test/test_quantization.py::TestQuantizeFx::test_change_backend_config_for_fixed_qparam_ops, test/test_quantization.py::TestQuantizeFx::test_channel_shuffle_lowering, test/test_quantization.py::TestQuantizeFx::test_conv_bn_relu, test/test_quantization.py::TestQuantizeFx::test_conv_linear_not_reference, test/test_quantization.py::TestQuantizeFx::test_conv_lowering, test/test_quantization.py::TestQuantizeFx::test_conv_transpose_relu_reference, test/test_quantization.py::TestQuantizeFx::test_convert_custom_config_from_dict, test/test_quantization.py::TestQuantizeFx::test_custom_module_class, test/test_quantization.py::TestQuantizeFx::test_default_quant_after_none_qconfig, test/test_quantization.py::TestQuantizeFx::test_dynamic_with_fusion, test/test_quantization.py::TestQuantizeFx::test_dynamic_with_fusion_multiple_uses, test/test_quantization.py::TestQuantizeFx::test_fp32_input_quantized_output, test/test_quantization.py::TestQuantizeFx::test_fp32_sum, test/test_quantization.py::TestQuantizeFx::test_fuse_custom_config_to_dict, test/test_quantization.py::TestQuantizeFx::test_linear_shape_view, test/test_quantization.py::TestQuantizeFx::test_linear_size_view, test/test_quantization.py::TestQuantizeFx::test_lowering_functional_conv_transpose_with_kwargs, test/test_quantization.py::TestQuantizeFx::test_masked_fill_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_match_pattern_with_multiple_args, test/test_quantization.py::TestQuantizeFx::test_output_lists_and_dicts, test/test_quantization.py::TestQuantizeFx::test_pattern_match, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_from_dict, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_input_quantized_indexes, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_non_traceable_module_names, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_standalone_module_name, test/test_quantization.py::TestQuantizeFx::test_qat_prepare_device_affinity, test/test_quantization.py::TestQuantizeFx::test_qconfig_dict_setup, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_global, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_module_name, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_module_name_object_type_order, test/test_quantization.py::TestQuantizeFx::test_qconfig_mapping_set_module_name_regex, test/test_quantization.py::TestQuantizeFx::test_qconfig_module_name_regex, test/test_quantization.py::TestQuantizeFx::test_qconfig_qat_module_type, test/test_quantization.py::TestQuantizeFx::test_quant_output_always_observed, test/test_quantization.py::TestQuantizeFx::test_ref_conv_module, test/test_quantization.py::TestQuantizeFx::test_register_patterns, test/test_quantization.py::TestQuantizeFx::test_repeat_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_reroute_tuple_getitem_patterns, test/test_quantization.py::TestQuantizeFx::test_size_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_sub_scalar, test/test_quantization.py::TestQuantizeFx::test_trace_quantize_per_tensor, test/test_quantization.py::TestQuantizeFx::test_transpose_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_unsqueeze_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFxOps::test_bmm, test/test_quantization.py::TestQuantizeFxOps::test_bmm_int_reference, test/test_quantization.py::TestQuantizeFxOps::test_clamp, test/test_quantization.py::TestQuantizeFxOps::test_conv_transpose_1d, test/test_quantization.py::TestQuantizeFxOps::test_embedding_bag, test/test_quantization.py::TestQuantizeFxOps::test_fixed_qparams_ops_fp16, test/test_quantization.py::TestQuantizeFxOps::test_fixed_qparams_ops_qint8, test/test_quantization.py::TestQuantizeFxOps::test_float_functional, test/test_quantization.py::TestQuantizeFxOps::test_functional_conv, test/test_quantization.py::TestQuantizeFxOps::test_functional_linear, test/test_quantization.py::TestQuantizeFxOps::test_getitem, test/test_quantization.py::TestQuantizeFxOps::test_multiple_qconfigs_for_single_value, test/test_quantization.py::TestQuantizeFxOps::test_pixel_shuffle, test/test_quantization.py::TestQuantizeFxOps::test_pixel_shuffle_module, test/test_quantization.py::TestQuantizeFxOps::test_pixel_unshuffle_module, test/test_quantization.py::TestQuantizeFxOps::test_qbatch_norm_relu, test/test_quantization.py::TestQuantizeFxOps::test_qmatmul, test/test_quantization.py::TestQuantizeFxOps::test_rnn_cell, test/test_quantization.py::TestQuantizeFxOps::test_sub, test/test_quantization.py::TestQuantizeFxModels::test_model_dropout, test/test_quantization.py::TestQuantizeFxModels::test_qat_embedding_linear, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_quantization.py::TestMetaDataPorting::test_no_metadata_porting, test/test_quantization.py::TestMetaDataPorting::test_no_metadata_porting_through_unknown_ops, test/test_quantization.py::TestNumericDebugger::test_run_decompositions_map_handle_to_new_nodes, test/test_quantization.py::TestNumericDebugger::test_run_decompositions_same_handle_id, test/test_quantization.py::TestNumericDebugger::test_simple, test/test_quantization.py::TestQuantizePT2E::test_constant_prop_preserve_metadata, test/test_quantization.py::TestQuantizePT2E::test_fixed_qparams_qspec_observer_dedup, test/test_quantization.py::TestQuantizePT2E::test_fold_quantize, test/test_quantization.py::TestQuantizePT2E::test_fold_quantize_per_channel, test/test_quantization.py::TestQuantizePT2E::test_groupwise_per_channel_quant, test/test_quantization.py::TestQuantizePT2E::test_input_edge_sanity_check, test/test_quantization.py::TestQuantizePT2E::test_model_is_exported, test/test_quantization.py::TestQuantizePT2E::test_move_exported_model_bn_device_cpu, test/test_quantization.py::TestQuantizePT2E::test_move_exported_model_dropout, test/test_quantization.py::TestQuantizePT2E::test_multi_users_without_output_observer, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_bfloat16_int16, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_float32_float8_e5m2, test/test_quantization.py::TestQuantizePT2E::test_transform_for_annotation, test/test_quantization.py::TestQuantizePT2E::test_wo_annotate_conv_output_quantizer, test/test_quantization.py::TestQuantizePT2EAffineQuantization::test_dynamic_affine_act_per_channel_weights, test/test_quantization.py::TestPT2ERepresentation::test_add_relu, test/test_quantization.py::TestPT2ERepresentation::test_maxpool2d, test/test_quantization.py::TestXNNPACKQuantizer::test_cat_same_node, test/test_quantization.py::TestXNNPACKQuantizer::test_dynamic_linear, test/test_quantization.py::TestXNNPACKQuantizer::test_dynamic_linear_with_conv, test/test_quantization.py::TestXNNPACKQuantizer::test_gru, test/test_quantization.py::TestXNNPACKQuantizer::test_linear_gru, test/test_quantization.py::TestXNNPACKQuantizer::test_linear_relu, test/test_quantization.py::TestXNNPACKQuantizer::test_linear_with_dynamic_shape, test/test_quantization.py::TestXNNPACKQuantizer::test_mul_float32_max, test/test_quantization.py::TestXNNPACKQuantizer::test_set_module_name_with_underscores, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_adaptive_avg_pool2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_attention_block, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_cat_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_cat_recipe_single_input, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_conv2d_serials_binary_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_filter_linear_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_filter_maxpool2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_conv2d_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_and_module_type_case1, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_bias_derived_qspec, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion_no_conv_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_relu_fusion, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_no_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_per_channel_weight_custom_dtype, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_relu_fusion_no_conv_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_inplace_add_relu, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_per_channel_weight_custom_dtype, test/test_quantization.py::TestQuantizePT2EQATModels::test_qat_resnet18, test/test_quantization.py::TestFXGraphMatcher::test_matching_failure_node_count, test/test_quantization.py::TestFXGraphMatcher::test_matching_failure_node_type, test/test_quantization.py::TestFXGraphMatcher::test_nodes_with_equal_types_get_matched, test/test_quantization.py::TestFXGraphMatcher::test_op_relationship_mapping, test/test_quantization.py::TestFXGraphMatcher::test_results_order, test/test_quantization.py::TestFXGraphMatcher::test_simple_mod_multi, test/test_quantization.py::TestFXGraphMatcher::test_user_defined_function, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_mul_inputs_activations, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_fun_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_fun_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_mod_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extract_weights_conv_fun_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extract_weights_fqn, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_int8_shadows_fp32_simple, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_int8_shadows_int8_mod, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_fp16_shadow_activations, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_fun_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_meth_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_op_with_only_kwargs_skips_shadowing, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_functions, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_linear_mod_fp32_fp32, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_linear_mod_quant_fp32, test/test_quantization.py::TestFXNumericSuiteNShadows::test_add_loggers_mobilenet_v2, test/test_quantization.py::TestFXNumericSuiteNShadows::test_extract_weights_linear, test/test_quantization.py::TestFXNumericSuiteNShadows::test_linear_mod, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_activations_conv, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_shadow_activations_conv, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_weights_lstm_dynamic, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_sparsenn_shadow, test/test_quantization.py::TestFxModelReportObserver::test_observer_after_relu, test/test_quantization.py::TestFxModelReportObserver::test_single_batch_of_ones, test/test_quantization.py::TestFxModelReportClass::test_constructor, test/test_quantization.py::TestFxModelReportClass::test_prepare_model_callibration, test/test_quantization.py::TestFxModelReportClass::test_qconfig_mapping_generation, test/test_quantization.py::TestFxDetectInputWeightEqualization::test_input_weight_equalization_report_gen_empty, test/test_quantization.py::TestFxModelReportVisualizer::test_generate_tables_no_match, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_graphs, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_results, test/test_quantization.py::TestSerialization::test_lstm, test/test_quantization.py::TestQuantizeJit::test_linear_dynamic_fp16, test/test_quantization.py::TestQuantizeJit::test_observer_with_ignored_function, test/test_quantization.py::TestQuantizeJit::test_single_linear, test/test_quantization.py::TestQuantizeJitPasses::test_foldbn_no_fusion, test/test_quantization.py::TestQuantizeJitPasses::test_foldbn_trivial, test/test_quantization.py::TestQuantizeJitPasses::test_inplace_option, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_child_qconfig, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_nested_if, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_reused_weight, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_propagate_observed, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_propagate_observed_in_submodule, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_skip_values, test/test_quantization.py::TestQuantizeJitPasses::test_insert_quant_dequant, test/test_quantization.py::TestQuantizeJitPasses::test_module_list, test/test_quantization.py::TestQuantizeJitPasses::test_quantize_fork_wait, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_dequant_same_value, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_quantize_for_if, test/test_quantization.py::TestQuantizeJitPasses::test_skip_dequant_constant_prop, test/test_quantization.py::TestQuantizeJitOps::test_dequantize_tuple, test/test_quantization.py::TestQuantizeJitOps::test_group_norm, test/test_quantization.py::TestQuantizeJitOps::test_qbatch_norm, test/test_quantization.py::TestQuantizeJitOps::test_qbatch_norm_relu_BNFuncInplaceRelu, test/test_quantization.py::TestQuantizeJitOps::test_quantized_add_relu, test/test_quantization.py::TestQuantizeJitOps::test_quantized_conv_relu, test/test_quantization.py::TestQuantizeJitOps::test_quantized_mul_relu, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_insert_quant_dequant_linear_dynamic, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_prepare_dynamic, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_quantize_dynamic_fp16, test/test_quantization.py::TestDeprecatedJitQuantized::test_rnn_quantized, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_fuser_method_mappings, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quant_type, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quantize_jit, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_qat_conv, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_quantized_dynamic_import, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_batchnorm, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_functional_modules, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_import, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_import_nn_intrinsic_qat, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_qat_linear_relu, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_quantized_conv_relu, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_nn_intrinsic_fused, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_convert, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_fusion_patterns, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_prepare, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_extremes_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_rte_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_finfo_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_finfo_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_finfo_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_float8_e8m0fnu_rne_rounding_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e4m3fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_type_promotion_fails_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPUOnlyCPU::test_pt2_traceable_aot_eager_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPUOnlyCPU::test_pt2_traceable_aot_eager_cpu_float8_e8m0fnu
2025-08-14T22:13:39.6720224Z 
2025-08-14T22:13:45.3249697Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:13:45.3253422Z   import pkg_resources
2025-08-14T22:13:45.5374583Z Running test_ao_sparsity 1/1 ... [2025-08-14 22:13:45.537003]
2025-08-14T22:13:45.5375416Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:13:45.5383387Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ao_sparsity.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:13:45.537936]
2025-08-14T22:14:11.8204386Z 
2025-08-14T22:14:11.8205849Z test_ao_sparsity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ao_sparsity_1.1_297f0496f0018656_.log
2025-08-14T22:14:11.8312595Z Running 88 items in this shard: test/test_ao_sparsity.py::TestQuantizedSparseKernels::test_sparse_qlinear, test/test_ao_sparsity.py::TestQuantizedSparseLayers::test_sparse_qlinear, test/test_ao_sparsity.py::TestQuantizedSparseLayers::test_sparse_qlinear_serdes, test/test_ao_sparsity.py::TestFakeSparsity::test_jit_trace, test/test_ao_sparsity.py::TestFakeSparsity::test_masking_logic, test/test_ao_sparsity.py::TestFakeSparsity::test_state_dict_preserved, test/test_ao_sparsity.py::TestFakeSparsity::test_weights_parametrized, test/test_ao_sparsity.py::TestCubicScheduler::test_constructor, test/test_ao_sparsity.py::TestCubicScheduler::test_step, test/test_ao_sparsity.py::TestScheduler::test_constructor, test/test_ao_sparsity.py::TestScheduler::test_lambda_scheduler, test/test_ao_sparsity.py::TestScheduler::test_order_of_steps, test/test_ao_sparsity.py::TestScheduler::test_step, test/test_ao_sparsity.py::TestBaseSparsifier::test_constructor, test/test_ao_sparsity.py::TestBaseSparsifier::test_convert, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params1, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params2, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params3, test/test_ao_sparsity.py::TestBaseSparsifier::test_prepare_config, test/test_ao_sparsity.py::TestBaseSparsifier::test_state_dict, test/test_ao_sparsity.py::TestBaseSparsifier::test_step, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_constructor, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_prepare, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_sparsity_levels, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_step, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_constructor, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_prepare, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_sparsity_levels, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_step, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_step_2_of_4, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_complex_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_constructor, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prepare_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prepare_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_activation_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_bias_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_padding_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_pool_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_activation_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_bias_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_layernorm_linear_multiple_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_layernorm_linear_single_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_linear_multiple_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_linear_single_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_step_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_step_linear, test/test_ao_sparsity.py::TestFPGMPruner::test_compute_distance, test/test_ao_sparsity.py::TestFPGMPruner::test_update_mask, test/test_ao_sparsity.py::TestSaliencyPruner::test_lstm_saliency_pruner_update_mask, test/test_ao_sparsity.py::TestSaliencyPruner::test_saliency_pruner_update_mask, test/test_ao_sparsity.py::TestComposability::test_convert_without_squash_mask, test/test_ao_sparsity.py::TestComposability::test_fusion_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_q_prep_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_qat_prep_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_fusion, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_q_prep, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_qat_prep, test/test_ao_sparsity.py::TestFxComposability::test_q_prep_fx_before_s_prep, test/test_ao_sparsity.py::TestFxComposability::test_q_prep_fx_s_prep_ref_conv, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_before_q_prep_fx, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_before_qat_prep_fx, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_q_prep_fx_ref, test/test_ao_sparsity.py::TestActivationSparsifier::test_activation_sparsifier, test/test_ao_sparsity.py::TestBaseDataScheduler::test_constructor, test/test_ao_sparsity.py::TestBaseDataScheduler::test_order_of_steps, test/test_ao_sparsity.py::TestBaseDataScheduler::test_state_dict, test/test_ao_sparsity.py::TestBaseDataScheduler::test_step, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_nn_embeddings, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_nn_parameters, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_tensors, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_nn_embeddings, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_nn_parameters, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_tensors, test/test_ao_sparsity.py::TestQuantizationUtils::test_ptq_quantize_first, test/test_ao_sparsity.py::TestQuantizationUtils::test_ptq_sparsify_first, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module_for_tensors, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_get_arg_info_from_tensor_fqn, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_get_arg_info_from_tensor_fqn_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn_root
2025-08-14T22:14:11.8371436Z 
2025-08-14T22:14:17.3538832Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:14:17.3541963Z   import pkg_resources
2025-08-14T22:14:17.5450131Z Running test_license 1/1 ... [2025-08-14 22:14:17.544603]
2025-08-14T22:14:17.5450906Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:14:17.5455455Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_license.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:14:17.545225]
2025-08-14T22:14:23.0209631Z 
2025-08-14T22:14:23.0211565Z test_license 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_license_1.1_3e1e69b707ef956b_.log
2025-08-14T22:14:23.0215106Z Running 2 items in this shard: test/test_license.py::TestLicense::test_distinfo_license, test/test_license.py::TestLicense::test_license_for_wheel
2025-08-14T22:14:23.0216799Z 
2025-08-14T22:14:28.7815274Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:14:28.7818469Z   import pkg_resources
2025-08-14T22:14:29.0148253Z Running torch_np/test_binary_ufuncs 1/1 ... [2025-08-14 22:14:29.014267]
2025-08-14T22:14:29.0149338Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:14:29.0154608Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_binary_ufuncs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:14:29.015041]
2025-08-14T22:14:34.9924169Z 
2025-08-14T22:14:34.9925975Z torch_np/test_binary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_binary_ufuncs_1.1_af2b894f0ff46f73_.log
2025-08-14T22:14:34.9952948Z Running 38 items in this shard: test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_add, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_arctan2, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_bitwise_and, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_bitwise_or, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_bitwise_xor, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_copysign, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_divide, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_equal, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_float_power, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_floor_divide, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_fmax, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_fmin, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_fmod, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_gcd, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_greater, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_greater_equal, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_heaviside, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_hypot, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_lcm, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_ldexp, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_left_shift, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_less, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_less_equal, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_logaddexp, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_logaddexp2, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_logical_and, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_logical_or, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_logical_xor, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_matmul, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_maximum, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_minimum, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_multiply, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_nextafter, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_not_equal, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_power, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_remainder, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_right_shift, test/torch_np/test_binary_ufuncs.py::TestBinaryUfuncBasic::test_subtract
2025-08-14T22:14:34.9974792Z 
2025-08-14T22:14:40.7762690Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:14:40.7765532Z   import pkg_resources
2025-08-14T22:14:41.0767479Z Running xpu/test_fusion 1/1 ... [2025-08-14 22:14:41.076195]
2025-08-14T22:14:41.0768732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:14:41.0775447Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_fusion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:14:41.077125]
2025-08-14T22:14:46.7874458Z 
2025-08-14T22:14:46.7875614Z xpu/test_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_fusion_1.1_fc2268645534b800_.log
2025-08-14T22:14:46.7876706Z Running 0 items in this shard:
2025-08-14T22:14:46.7877008Z 
2025-08-14T22:14:52.4016307Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:14:52.4020014Z   import pkg_resources
2025-08-14T22:14:52.6734327Z Running torch_np/test_unary_ufuncs 1/1 ... [2025-08-14 22:14:52.672825]
2025-08-14T22:14:52.6735823Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:14:52.6740035Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_unary_ufuncs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:14:52.673472]
2025-08-14T22:14:59.1690148Z 
2025-08-14T22:14:59.1691803Z torch_np/test_unary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_unary_ufuncs_1.1_f8069e123dcea7f8_.log
2025-08-14T22:14:59.1714757Z Running 42 items in this shard: test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_absolute, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arccos, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arccosh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arcsin, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arcsinh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arctan, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_arctanh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_cbrt, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_ceil, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_conjugate, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_cos, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_cosh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_deg2rad, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_degrees, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_exp, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_exp2, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_expm1, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_fabs, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_floor, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_isfinite, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_isinf, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_isnan, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_log, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_log10, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_log1p, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_log2, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_logical_not, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_negative, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_positive, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_rad2deg, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_radians, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_reciprocal, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_rint, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_sign, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_signbit, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_sin, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_sinh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_sqrt, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_square, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_tan, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_tanh, test/torch_np/test_unary_ufuncs.py::TestUnaryUfuncs::test_trunc
2025-08-14T22:14:59.1736043Z 
2025-08-14T22:15:04.5197413Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:15:04.5201217Z   import pkg_resources
2025-08-14T22:15:04.7356831Z Running test_foreach 1/1 ... [2025-08-14 22:15:04.735258]
2025-08-14T22:15:04.7357622Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:15:04.7363124Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_foreach.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:15:04.735953]
2025-08-14T22:18:43.5638814Z 
2025-08-14T22:18:43.5640380Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_07ac6dca3b655525_.log
2025-08-14T22:18:43.8687033Z Running 3577 items in this shard: test/test_foreach.py::TestForeachCPU::test_0dim_tensor_overload_cpu_ok_cpu, test/test_foreach.py::TestForeachCPU::test_0dim_tensor_overload_exception_cpu, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_bfloat16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_complex64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float32, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_float64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int16, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int32, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int64, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_int8, test/test_foreach.py::TestForeachCPU::test_add_scalar_with_empty_list_and_empty_tensor_cpu_uint8, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_abs_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_acos_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_add_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcdiv_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcmul_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_asin_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_atan_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_ceil_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_max_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_min_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_copy_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cos_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cosh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_div_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erf_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erfc_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_exp_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_expm1_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_floor_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_frac_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lerp_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lgamma_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log10_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log1p_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log2_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_max_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_maximum_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_minimum_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_mul_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_neg_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_norm_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_pow_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_reciprocal_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_round_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_rsqrt_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sigmoid_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sign_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sin_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sinh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sqrt_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sub_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tan_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tanh_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_trunc_cpu_float32, test/test_foreach.py::TestForeachCPU::test_all_zero_size_tensors_do_not_launch_kernel__foreach_zero_cpu_float32, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_abs_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_acos_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_add_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcdiv_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_addcmul_outplace_cpu_float64, 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test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_ceil_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_max_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_inplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_inplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_outplace_cpu_complex128, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_clamp_min_outplace_cpu_float64, test/test_foreach.py::TestForeachCPU::test_autodiff__foreach_copy_inplace_cpu_complex128, 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test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_float64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int16, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int32, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int64, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_int8, test/test_foreach.py::TestForeachCPU::test_unary_op_tensors_on_different_devices__foreach_zero_cpu_uint8
2025-08-14T22:18:44.1750789Z 
2025-08-14T22:18:49.6340852Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:18:49.6343795Z   import pkg_resources
2025-08-14T22:18:49.8302124Z Running test_expanded_weights 1/1 ... [2025-08-14 22:18:49.829742]
2025-08-14T22:18:49.8302900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:18:49.8308286Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_expanded_weights.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:18:49.830457]
2025-08-14T22:19:18.4513551Z 
2025-08-14T22:19:18.4515001Z test_expanded_weights 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_expanded_weights_1.1_23b08f7fad36f0c5_.log
2025-08-14T22:19:18.4727964Z Running 189 items in this shard: test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_forward_helper_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_forward_helper_failure_args_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_set_grad_sample_if_exists_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_set_grad_sample_if_exists_failure_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_sum_over_all_but_batch_and_last_n_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_failure_cpu, test/test_expanded_weights.py::TestExpandedWeightHelperFunctionCPU::test_unpack_expanded_weight_or_tensor_with_custom_function_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_cnn_model_mean_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_cnn_model_sum_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_embedding_model_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_error_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv1d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv2d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_conv3d_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_bfloat16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_complex128, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_complex64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int16, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int32, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_int8, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_forward_nn_functional_linear_cpu_uint8, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_mean_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weight_per_sample_grad_sum_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_expanded_weights_per_sample_grad_input_no_grad_nn_functional_linear_cpu_float64, 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test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_layer_norm_model_num_dim_3_cpu, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv1d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv2d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_conv3d_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_embedding_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_group_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_instance_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_layer_norm_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightFunctionalCPU::test_unsupported_expand_weights_nn_functional_linear_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1size1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad1size1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2size1_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_pad2size1_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_reflect_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_reflect_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_stride_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_stride_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv1d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_dilated_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_dilated_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_padding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_padding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_reflect_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_reflect_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_strided_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_strided_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv2d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_1x1x1_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_1x1x1_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_circular_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_circular_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_replicate_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_replicate_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_padding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_stride_padding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zero_batch_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zero_batch_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zeros_stride2_pad2_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Conv3d_zeros_stride2_pad2_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_discontiguous_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_discontiguous_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Embedding_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_LayerNorm_3d_no_affine_large_feature_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_LayerNorm_3d_no_affine_large_feature_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_batch_dim_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_batch_dim_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_bias_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_Linear_no_bias_multiple_inputs_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_GRU_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_LSTM_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_eval_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_eval_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_train_mode_cpu_float32, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_module_nn_RNN_train_mode_cpu_float64, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_compute_batch_size_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_compute_batch_size_not_pytreeable_cpu, test/test_expanded_weights.py::TestExpandedWeightModuleCPU::test_per_sample_api_failing_cpu
2025-08-14T22:19:18.4992218Z 
2025-08-14T22:19:24.3478538Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:19:24.3481612Z   import pkg_resources
2025-08-14T22:19:24.5543328Z Running typing/test_python_operators 1/1 ... [2025-08-14 22:19:24.553621]
2025-08-14T22:19:24.5544485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:19:24.5550755Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'typing/test_python_operators.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:19:24.554560]
2025-08-14T22:19:32.5358963Z 
2025-08-14T22:19:32.5362788Z typing/test_python_operators 1/1 was successful, full logs can be found in artifacts with path test/test-reports/typing.test_python_operators_1.1_5d61f9f466bcf7a3_.log
2025-08-14T22:19:32.5595443Z Running 318 items in this shard: test/typing/test_python_operators.py::TestPythonOperators::test_binary_a100_op_%_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a101_op_%_b101, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a102_op_%_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a103_op_%_b103, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a104_op_*_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a105_op_*_b105, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a106_op_*_b_3, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a107_op_*_b107, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a108_op_**_b_1_5, test/typing/test_python_operators.py::TestPythonOperators::test_binary_a109_op_**_b109, 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2025-08-14T22:19:32.5823908Z 
2025-08-14T22:19:37.9890013Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:19:37.9893099Z   import pkg_resources
2025-08-14T22:19:38.3895124Z Running test_fx_experimental 1/1 ... [2025-08-14 22:19:38.388953]
2025-08-14T22:19:38.3896952Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:19:38.3903035Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_experimental.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:19:38.389769]
2025-08-14T22:20:05.2589961Z 
2025-08-14T22:20:05.2591778Z test_transformers 3/3 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_3.3_0c65a9c848940477_.log
2025-08-14T22:20:05.4429604Z Running 1133 items in this shard: test/test_transformers.py::TestTransformersCPU::test_decoder_only_layer_cpu, test/test_transformers.py::TestTransformersCPU::test_decoder_padding_and_src_mask_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_encoder_is_causal_cpu, test/test_transformers.py::TestTransformersCPU::test_mask_check_fastpath_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_1_bias_True_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_8_bias_True_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim1_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim_2_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim1_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_no_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_no_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_no_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_script_encoder_subclass_cpu, test/test_transformers.py::TestTransformersCPU::test_script_mha_in_proj_weight_none_cpu, test/test_transformers.py::TestTransformersCPU::test_self_attn_TxT_attn_mask_cpu, test/test_transformers.py::TestTransformersCPU::test_train_with_pad_and_catch_error_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_False_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_True_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_False_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_False_training_True_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_True_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_subclass_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_atteention_large_bf16_nan_values_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_attention_fail_with_non_square_causal_attention_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_autocast_fp32_bfloat16_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_193_dropout_p_0_2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_attn_mask_present_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_head_dim_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_invalid_dtype_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel1_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_last_dim_stride_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_sdpa_kernel_grouped_query_attention_cuda_fused_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_sequence_lengths_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_nested_fails_on_padding_head_dim_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_unaligned_tensors_cpu, test/test_transformers.py::TestSDPACPU::test_scaled_dot_product_attention_math_with_negative_scale_kernel0_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_cpu_flash_attn_nan_propagation_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_cpu_flash_attn_nan_propagation_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_bfloat16_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_7_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_0_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_non_masked_rows_nan_props_float32_fill_val_inf_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads0_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads2_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads2_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads3_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads0_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads0_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads1_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads1_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads3_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads1_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads3_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_sdpa_backward_with_gradient_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape3_cpu
2025-08-14T22:20:05.5596050Z 
2025-08-14T22:20:08.8864875Z 
2025-08-14T22:20:08.8866180Z test_transformers 2/3 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_2.3_035f38df41743b3b_.log
2025-08-14T22:20:09.0520579Z Running 1063 items in this shard: test/test_transformers.py::TestTransformersCPU::test_bias_is_none_cpu, test/test_transformers.py::TestTransformersCPU::test_disable_fastpath_cpu, test/test_transformers.py::TestTransformersCPU::test_kpm_mask_trailing_column_with_nested_tensor_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_1_bias_False_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_8_bias_False_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim_2_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim_2_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_False_use_autocast_True_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_True_d_model_12_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_True_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_src_mask_nhead_4_cpu, test/test_transformers.py::TestTransformersCPU::test_with_nested_tensor_input_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_dispatch_fails_no_backend_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_autocast_fp32_float16_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_193_dropout_p_0_0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_256_dropout_p_0_0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_fail_fp32_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_broadcast_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_dim_3_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_datatypes_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_devices_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_devices_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mem_eff_attention_fail_with_batch_size_geq_65536_error_cpu, test/test_transformers.py::TestSDPACPU::test_sdp_math_gradcheck_contiguous_inputs_True_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_non_masked_rows_nan_props_float16_fill_val_inf_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_attention_math_with_negative_scale_kernel0_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads1_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads3_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads3_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads0_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads1_train_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads0_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads1_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_sdpa_with_inf_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape3_cpu
2025-08-14T22:20:09.1559887Z 
2025-08-14T22:20:09.1561527Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:09.1563050Z   import pkg_resources
2025-08-14T22:20:09.1563378Z Running test_file_check 1/1 ... [2025-08-14 22:20:09.046114]
2025-08-14T22:20:09.1563792Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:09.1564876Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_file_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:09.046484]
2025-08-14T22:20:12.1444733Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:12.1446269Z   import pkg_resources
2025-08-14T22:20:12.3024860Z Running torch_np/test_dtype 1/1 ... [2025-08-14 22:20:12.302023]
2025-08-14T22:20:12.3025633Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:12.3031904Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_dtype.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:12.302726]
2025-08-14T22:20:14.3202639Z 
2025-08-14T22:20:14.3203837Z test_file_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_file_check_1.1_08f4b83d47d6ff58_.log
2025-08-14T22:20:14.3205869Z Running 2 items in this shard: test/test_file_check.py::TestFileCheck::test_all_python_api, test/test_file_check.py::TestFileCheck::test_not_run
2025-08-14T22:20:14.3207004Z 
2025-08-14T22:20:16.2399420Z 
2025-08-14T22:20:16.2400613Z torch_np/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_dtype_1.1_37d662194102b699_.log
2025-08-14T22:20:16.2417328Z Running 44 items in this shard: test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'bool_', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'complex128', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'complex64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_bool, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'bool_', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'complex128', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'complex64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.bool_, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.complex128, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.complex64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.dtype('bool'), test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int8, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint8
2025-08-14T22:20:16.2432805Z 
2025-08-14T22:20:17.5287630Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:17.5289222Z   import pkg_resources
2025-08-14T22:20:17.7164814Z Running higher_order_ops/test_with_effects 1/1 ... [2025-08-14 22:20:17.716068]
2025-08-14T22:20:17.7165799Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:17.7168973Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:17.716487]
2025-08-14T22:20:19.8750772Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:19.8753620Z   import pkg_resources
2025-08-14T22:20:20.0012087Z Running test_native_functions 1/1 ... [2025-08-14 22:20:20.000789]
2025-08-14T22:20:20.0012952Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:20.0015316Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_functions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:20.001193]
2025-08-14T22:20:23.5713235Z 
2025-08-14T22:20:23.5715013Z test_native_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_functions_1.1_bcb88edde450ece8_.log
2025-08-14T22:20:23.5724257Z Running 11 items in this shard: test/test_native_functions.py::TestNativeFunctions::test_intlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_optional_filled_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_string_defaults, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload_but_is_unique, test/test_native_functions.py::TestNativeFunctions::test_vararg_symintlist_error
2025-08-14T22:20:23.5732587Z 
2025-08-14T22:20:27.6556682Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:27.6559799Z   import pkg_resources
2025-08-14T22:20:27.7813346Z Running functorch/test_minifier 1/1 ... [2025-08-14 22:20:27.780941]
2025-08-14T22:20:27.7814125Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:27.7816732Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_minifier.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:27.781349]
2025-08-14T22:20:32.3033274Z 
2025-08-14T22:20:32.3035442Z functorch/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_minifier_1.1_247b538eb638a78a_.log
2025-08-14T22:20:32.3039457Z Running 5 items in this shard: test/functorch/test_minifier.py::TestMinifier::test_has_add_mul, test/functorch/test_minifier.py::TestMinifier::test_has_mul_minifier, test/functorch/test_minifier.py::TestMinifier::test_input_returned, test/functorch/test_minifier.py::TestMinifier::test_module, test/functorch/test_minifier.py::TestMinifier::test_tup_use
2025-08-14T22:20:32.3042481Z 
2025-08-14T22:20:35.8296230Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:35.8299106Z   import pkg_resources
2025-08-14T22:20:35.9620822Z Running test_flop_counter 1/1 ... [2025-08-14 22:20:35.961652]
2025-08-14T22:20:35.9622015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:35.9625590Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_flop_counter.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:35.962109]
2025-08-14T22:20:41.4865867Z 
2025-08-14T22:20:41.4869295Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_70ce6a11f71cbaa5_.log
2025-08-14T22:20:41.4885894Z Running 18 items in this shard: test/higher_order_ops/test_with_effects.py::TestWithEffects::test_alias_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager_requires_grad, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor_external_op_return_none, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_custom_op_with_subclasses, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_op_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_aliased_outputs, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_is_output, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_return, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_output_view_simple, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_buffer_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_input_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_register_effectful_custom_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_in_forward_and_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_only_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_torchbind_custom_op
2025-08-14T22:20:41.4901152Z 
2025-08-14T22:20:41.8874657Z 
2025-08-14T22:20:41.8876452Z test_flop_counter 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_flop_counter_1.1_04987189fc3d054e_.log
2025-08-14T22:20:41.8884632Z Running 22 items in this shard: test/test_flop_counter.py::TestFlopCounter::test_addmm_out, test/test_flop_counter.py::TestFlopCounter::test_autograd_op, test/test_flop_counter.py::TestFlopCounter::test_backward, test/test_flop_counter.py::TestFlopCounter::test_backward_reset, test/test_flop_counter.py::TestFlopCounter::test_conv_backwards_as_decomposition, test/test_flop_counter.py::TestFlopCounter::test_conv_transpose_loop, test/test_flop_counter.py::TestFlopCounter::test_convs, test/test_flop_counter.py::TestFlopCounter::test_custom, test/test_flop_counter.py::TestFlopCounter::test_custom_op, test/test_flop_counter.py::TestFlopCounter::test_flop_counter_variety, test/test_flop_counter.py::TestFlopCounter::test_hook_registration, test/test_flop_counter.py::TestFlopCounter::test_inference_mode, test/test_flop_counter.py::TestFlopCounter::test_module, test/test_flop_counter.py::TestFlopCounter::test_nested_attention_fake_tensors, test/test_flop_counter.py::TestFlopCounter::test_noop, test/test_flop_counter.py::TestFlopCounter::test_op, test/test_flop_counter.py::TestFlopCounter::test_pytrees, test/test_flop_counter.py::TestFlopCounter::test_scaled_mm, test/test_flop_counter.py::TestFlopCounter::test_sdpa, test/test_flop_counter.py::TestFlopCounter::test_sdpa_nested_tensor, test/test_flop_counter.py::TestFlopCounter::test_torchscript, test/test_flop_counter.py::TestFlopCounter::test_warning
2025-08-14T22:20:41.8891185Z 
2025-08-14T22:20:45.4425018Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:45.4428173Z   import pkg_resources
2025-08-14T22:20:45.5694355Z Running torch_np/test_nep50_examples 1/1 ... [2025-08-14 22:20:45.568684]
2025-08-14T22:20:45.5695275Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:45.5697797Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_nep50_examples.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:45.569141]
2025-08-14T22:20:46.1876513Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:46.1880100Z   import pkg_resources
2025-08-14T22:20:46.3726478Z Running higher_order_ops/test_invoke_quant 1/1 ... [2025-08-14 22:20:46.371351]
2025-08-14T22:20:46.3727426Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:46.3729593Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_quant.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:46.371887]
2025-08-14T22:20:52.3971237Z 
2025-08-14T22:20:52.3972806Z torch_np/test_nep50_examples 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_nep50_examples_1.1_31513bd57cf960c9_.log
2025-08-14T22:20:52.5140189Z Running 1573 items in this shard: test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_3j + array(3, complex64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_True + uint8(2), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array(1_0, float32) + 1e-14 == 1_0, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([0_1], float32) == float64(0_1), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([100], uint8) + 200, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 1, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 200, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + 300, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + array(1, int64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1], uint8) + int64(1), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_0], float32) + 1e-14 == 1_0, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + 3, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + array(1_, float64), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + float64(1_), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_array([1_], float32) + int64(3), test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_bool_(True) + 1, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(1) + 1j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(1) + 3e100, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_float32(5) + 5j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int16(2) + 2, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int16(4) + 4j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_int32(1) + 5j, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(1) + 2, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(1) + 300, test/torch_np/test_nep50_examples.py::TestNEP50Table::test_nep50_exceptions_example_uint8(100) + 200, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_add_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_arctan2_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_bitwise_and_scalar_1_array16, 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test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_right_shift_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_subtract_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar27_array27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar28_array28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar29_array29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar30_array30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar31_array31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar32_array32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar33_array33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar34_array34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar35_array35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_1_array9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_2_0_array26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_compare_ufuncs_name_true_divide_scalar_True_array8, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar27_array27_dtype27, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar28_array28_dtype28, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar29_array29_dtype29, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar30_array30_dtype30, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar31_array31_dtype31, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar32_array32_dtype32, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar33_array33_dtype33, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar34_array34_dtype34, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar35_array35_dtype35, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array10_dtype10, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array11_dtype11, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array12_dtype12, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array13_dtype13, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array14_dtype14, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array15_dtype15, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array16_dtype16, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array17_dtype17, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_1_array9_dtype9, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array18_dtype18, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array19_dtype19, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array20_dtype20, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array21_dtype21, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array22_dtype22, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array23_dtype23, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array24_dtype24, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array25_dtype25, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_2_0_array26_dtype26, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array0_dtype0, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array1_dtype1, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array2_dtype2, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array3_dtype3, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array4_dtype4, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array5_dtype5, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array6_dtype6, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array7_dtype7, test/torch_np/test_nep50_examples.py::TestCompareToNumpy::test_direct_compare_scalar_True_array8_dtype8
2025-08-14T22:20:52.6087562Z 
2025-08-14T22:20:55.8427753Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:20:55.8430440Z   import pkg_resources
2025-08-14T22:20:55.9707059Z Running test_per_overload_api 1/1 ... [2025-08-14 22:20:55.970249]
2025-08-14T22:20:55.9707825Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:20:55.9710377Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_per_overload_api.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:20:55.970691]
2025-08-14T22:20:59.0583761Z 
2025-08-14T22:20:59.0585246Z higher_order_ops/test_invoke_quant 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_quant_1.1_aa3c145db7aa3e00_.log
2025-08-14T22:20:59.0591925Z Running 14 items in this shard: test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantEager::test_simple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantAotEager::test_simple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_construct_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_inline, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_multiple, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_pattern_matching, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_prologue, test/higher_order_ops/test_invoke_quant.py::TestInvokeQuantInductor::test_simple
2025-08-14T22:20:59.0597901Z 
2025-08-14T22:20:59.6917197Z 
2025-08-14T22:20:59.6918493Z test_per_overload_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_per_overload_api_1.1_b1a76edab62a39a6_.log
2025-08-14T22:20:59.6920645Z Running 3 items in this shard: test/test_per_overload_api.py::TestPerOverloadAPI::test_basics_opoverload, test/test_per_overload_api.py::TestPerOverloadAPI::test_basics_opoverloadpacket, test/test_per_overload_api.py::TestPerOverloadAPI::test_decompose
2025-08-14T22:20:59.6921895Z 
2025-08-14T22:21:02.6315363Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:02.6316916Z   import pkg_resources
2025-08-14T22:21:02.7597664Z Running test_tensorexpr_pybind 1/1 ... [2025-08-14 22:21:02.759393]
2025-08-14T22:21:02.7598763Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:02.7600954Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr_pybind.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:02.759768]
2025-08-14T22:21:03.0777131Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:03.0779739Z   import pkg_resources
2025-08-14T22:21:03.2220793Z Running test_pytree 1/1 ... [2025-08-14 22:21:03.221677]
2025-08-14T22:21:03.2221564Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:03.2224095Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pytree.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:03.222074]
2025-08-14T22:21:06.3300516Z 
2025-08-14T22:21:06.3302053Z test_tensorexpr_pybind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_pybind_1.1_6296e8abf65fe1e7_.log
2025-08-14T22:21:06.3313925Z Running 17 items in this shard: test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_alloc_in_loop, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_call_raw, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dtype_error, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dynamic_shape, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_dynamic_shape_2d, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_external_calls, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_shape_prop, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_shape_prop_module, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_custom_lowering, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_expand, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_permute, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_scalar_inputs, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_t, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_tensor_inputs, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_kernel_with_transpose, test/test_tensorexpr_pybind.py::TestTensorExprPyBind::test_simple_sum, test/test_tensorexpr_pybind.py::TestExprHandlePyBind::test_unary_ops
2025-08-14T22:21:06.3324877Z 
2025-08-14T22:21:08.5838609Z 
2025-08-14T22:21:08.5839881Z test_fx_experimental 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_experimental_1.1_5abe6842d9a2cfe2_.log
2025-08-14T22:21:08.6488298Z Running 723 items in this shard: test/test_fx_experimental.py::TestFXExperimental::test_annotate_getitem_node, test/test_fx_experimental.py::TestFXExperimental::test_annotate_returns_with_schema, test/test_fx_experimental.py::TestFXExperimental::test_aot_based_partition, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_no_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_empty_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_msg, test/test_fx_experimental.py::TestFXExperimental::test_call_to_assert_with_multiline_message, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion_mixed_dtype, test/test_fx_experimental.py::TestFXExperimental::test_conv_bn_fusion_not_running_state, test/test_fx_experimental.py::TestFXExperimental::test_cost_aware_partition, test/test_fx_experimental.py::TestFXExperimental::test_fetch, test/test_fx_experimental.py::TestFXExperimental::test_find_single_partition, test/test_fx_experimental.py::TestFXExperimental::test_lack_of_devices, test/test_fx_experimental.py::TestFXExperimental::test_large_node_error, test/test_fx_experimental.py::TestFXExperimental::test_merge_matmuls, test/test_fx_experimental.py::TestFXExperimental::test_meta_tracer, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args_perserve_type, test/test_fx_experimental.py::TestFXExperimental::test_normalize_args_preserve_meta, test/test_fx_experimental.py::TestFXExperimental::test_normalize_binary_operators, test/test_fx_experimental.py::TestFXExperimental::test_normalize_modules_exhaustive, test/test_fx_experimental.py::TestFXExperimental::test_optimize_for_inference_cpu, 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2025-08-14T22:21:08.7173998Z 
2025-08-14T22:21:08.8959127Z 
2025-08-14T22:21:08.8960486Z test_pytree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pytree_1.1_9b18b36cff072693_.log
2025-08-14T22:21:08.9016827Z Running 98 items in this shard: test/test_pytree.py::TestGenericPytree::test_aligned_public_apis, test/test_pytree.py::TestGenericPytree::test_broadcast_to_and_flatten_cxx, test/test_pytree.py::TestGenericPytree::test_broadcast_to_and_flatten_py, test/test_pytree.py::TestGenericPytree::test_enum_treespec_roundtrip_cxx, test/test_pytree.py::TestGenericPytree::test_enum_treespec_roundtrip_py, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_defaultdict_cxx, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_defaultdict_py, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_deque_cxx, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_deque_py, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_dict_cxx, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_dict_py, test/test_pytree.py::TestGenericPytree::test_flatten_unflatten_leaf_cxx, 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test/test_pytree.py::TestGenericPytree::test_tree_all_any_py, test/test_pytree.py::TestGenericPytree::test_tree_map_cxx, test/test_pytree.py::TestGenericPytree::test_tree_map_multi_inputs_cxx, test/test_pytree.py::TestGenericPytree::test_tree_map_multi_inputs_py, test/test_pytree.py::TestGenericPytree::test_tree_map_only_cxx, test/test_pytree.py::TestGenericPytree::test_tree_map_only_predicate_fn_cxx, test/test_pytree.py::TestGenericPytree::test_tree_map_only_predicate_fn_py, test/test_pytree.py::TestGenericPytree::test_tree_map_only_py, test/test_pytree.py::TestGenericPytree::test_tree_map_py, test/test_pytree.py::TestPythonPytree::test_constant, test/test_pytree.py::TestPythonPytree::test_constant_default_eq_error, test/test_pytree.py::TestPythonPytree::test_constant_default_hash_error, test/test_pytree.py::TestPythonPytree::test_dataclass, test/test_pytree.py::TestPythonPytree::test_deprecated_register_pytree_node, test/test_pytree.py::TestPythonPytree::test_flatten_flatten_with_key_consistency, test/test_pytree.py::TestPythonPytree::test_import_pytree_doesnt_import_optree, test/test_pytree.py::TestPythonPytree::test_key_access, test/test_pytree.py::TestPythonPytree::test_key_str, test/test_pytree.py::TestPythonPytree::test_pytree_context_serialize_bad, test/test_pytree.py::TestPythonPytree::test_pytree_custom_type_serialize, test/test_pytree.py::TestPythonPytree::test_pytree_custom_type_serialize_bad, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_bad_protocol, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_defaultdict_enum, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_enum, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_namedtuple, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_namedtuple_bad, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_register_bad, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec0, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec1, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec2, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec3, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec4, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec5, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec6, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec7, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec8, test/test_pytree.py::TestPythonPytree::test_pytree_serialize_spec9, test/test_pytree.py::TestPythonPytree::test_register_dataclass_class, test/test_pytree.py::TestPythonPytree::test_saved_serialized, test/test_pytree.py::TestPythonPytree::test_tree_flatten_with_path_is_leaf, test/test_pytree.py::TestPythonPytree::test_tree_flatten_with_path_roundtrip, test/test_pytree.py::TestPythonPytree::test_tree_leaves_with_path, test/test_pytree.py::TestPythonPytree::test_tree_map_with_path, test/test_pytree.py::TestPythonPytree::test_tree_map_with_path_multiple_trees, test/test_pytree.py::TestPythonPytree::test_treespec_equality, test/test_pytree.py::TestPythonPytree::test_treespec_repr, test/test_pytree.py::TestCxxPytree::test_pytree_custom_type_serialize, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_namedtuple, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec0, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec1, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec2, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec3, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec4, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec5, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec6, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec7, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec8, test/test_pytree.py::TestCxxPytree::test_pytree_serialize_spec9, test/test_pytree.py::TestCxxPytree::test_treespec_equality, test/test_pytree.py::TestCxxPytree::test_treespec_repr
2025-08-14T22:21:08.9071828Z 
2025-08-14T22:21:09.8465115Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:09.8467917Z   import pkg_resources
2025-08-14T22:21:09.9728560Z Running test_fx_passes 1/1 ... [2025-08-14 22:21:09.972392]
2025-08-14T22:21:09.9729316Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:09.9731349Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_passes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:09.972747]
2025-08-14T22:21:11.9515722Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:11.9518538Z   import pkg_resources
2025-08-14T22:21:12.0761597Z Running test_module_tracker 1/1 ... [2025-08-14 22:21:12.075734]
2025-08-14T22:21:12.0762343Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:12.0764003Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_module_tracker.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:12.076117]
2025-08-14T22:21:12.1903262Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:12.1904829Z   import pkg_resources
2025-08-14T22:21:12.3158097Z Running test_typing 1/1 ... [2025-08-14 22:21:12.315388]
2025-08-14T22:21:12.3158701Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:12.3160012Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_typing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:12.315758]
2025-08-14T22:21:13.9435010Z 
2025-08-14T22:21:13.9436679Z test_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_passes_1.1_1d76cf238a6bde83_.log
2025-08-14T22:21:13.9457498Z Running 53 items in this shard: test/test_fx_passes.py::TestFXGraphPasses::test_fuser_pass_deep_model, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition10, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition11, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition4, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition5, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition6, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition7, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition8, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition9, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn0_expected_partition0_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn10_expected_partition10_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn11_expected_partition11_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn12_expected_partition12_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn13_expected_partition13_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn14_expected_partition14_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn15_expected_partition15_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn16_expected_partition16_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn17_expected_partition17_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn18_expected_partition18_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn1_expected_partition1_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn2_expected_partition2_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn3_expected_partition3_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn4_expected_partition4_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn5_expected_partition5_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn6_expected_partition6_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn7_expected_partition7_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn8_expected_partition8_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn9_expected_partition9_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_independent_output_fn0_expected_partition0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model1, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model10, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model11, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model12, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model13, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model14, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model15, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model2, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model3, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model4, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model5, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model6, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model7, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model8, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model9
2025-08-14T22:21:13.9477830Z 
2025-08-14T22:21:15.5464550Z 
2025-08-14T22:21:15.5465894Z test_module_tracker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_module_tracker_1.1_a6d6e2269bc6d0aa_.log
2025-08-14T22:21:15.5467484Z Running 3 items in this shard: test/test_module_tracker.py::TestModuleTracker::test_bw_detection, test/test_module_tracker.py::TestModuleTracker::test_confused_hierarchy, test/test_module_tracker.py::TestModuleTracker::test_module_hierarchy
2025-08-14T22:21:15.5468584Z 
2025-08-14T22:21:17.3994486Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:17.3997281Z   import pkg_resources
2025-08-14T22:21:17.5257674Z Running test_openmp 1/1 ... [2025-08-14 22:21:17.525337]
2025-08-14T22:21:17.5258410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:17.5261017Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_openmp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:17.525769]
2025-08-14T22:21:18.8264091Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:18.8267082Z   import pkg_resources
2025-08-14T22:21:18.9526785Z Running torch_np/numpy_tests/core/test_scalarinherit 1/1 ... [2025-08-14 22:21:18.952248]
2025-08-14T22:21:18.9528073Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:18.9530212Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarinherit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:18.952636]
2025-08-14T22:21:23.0732040Z 
2025-08-14T22:21:23.0733931Z torch_np/numpy_tests/core/test_scalarinherit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarinherit_1.1_12474f2a70e3313b_.log
2025-08-14T22:21:23.0737869Z Running 3 items in this shard: test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_gh_15395, test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_init, test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_init2
2025-08-14T22:21:23.0740247Z 
2025-08-14T22:21:26.3884064Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:26.3885631Z   import pkg_resources
2025-08-14T22:21:26.5144301Z Running functorch/test_ac_knapsack 1/1 ... [2025-08-14 22:21:26.514052]
2025-08-14T22:21:26.5144818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:26.5147483Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_knapsack.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:26.514474]
2025-08-14T22:21:26.9104448Z 
2025-08-14T22:21:26.9105947Z test_openmp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openmp_1.1_9dabd5387fc0053a_.log
2025-08-14T22:21:26.9108215Z Running 2 items in this shard: test/test_openmp.py::TestOpenMP_ParallelFor::test_n_threads, test/test_openmp.py::TestOpenMP_ParallelFor::test_one_thread
2025-08-14T22:21:26.9109659Z 
2025-08-14T22:21:30.2352823Z 
2025-08-14T22:21:30.2354380Z functorch/test_ac_knapsack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_knapsack_1.1_c6e60457a3201124_.log
2025-08-14T22:21:30.2366978Z Running 15 items in this shard: test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_full_joint_nx_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_knapsack_memory_input, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_knapsack_runtime_input, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_non_ac_peak_memory, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_get_theoretical_max_runtime, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_inialize_from_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_recomputable_node_only_graph, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_recomputable_node_only_graph_with_larger_graph_context, test/functorch/test_ac_knapsack.py::TestGraphInfoProvider::test_simplified_fx_joint_graph, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_distribution_of_results_for_knapsack_algo, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_accounting_for_backward_pass, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_not_accounting_for_backward_pass, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_evaluate_knapsack_output_with_wrong_sized_values, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_get_backward_memory_from_topologically_sorted_graph, test/functorch/test_ac_knapsack.py::TestKnapsackEvaluator::test_get_knee_point_memory_budget
2025-08-14T22:21:30.2380175Z 
2025-08-14T22:21:30.2496131Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:30.2497762Z   import pkg_resources
2025-08-14T22:21:30.3778033Z Running backends/xeon/test_launch 1/1 ... [2025-08-14 22:21:30.377409]
2025-08-14T22:21:30.3778533Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:30.3781321Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'backends/xeon/test_launch.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:30.377823]
2025-08-14T22:21:33.5515917Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:33.5518281Z   import pkg_resources
2025-08-14T22:21:33.6791145Z Running test_nestedtensor 1/4 ... [2025-08-14 22:21:33.678679]
2025-08-14T22:21:33.6792095Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:33.6794140Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nestedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:33.679056]
2025-08-14T22:21:35.7506621Z 
2025-08-14T22:21:35.7508395Z backends/xeon/test_launch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/backends.xeon.test_launch_1.1_9139ab1563e745e9_.log
2025-08-14T22:21:35.7510902Z Running 2 items in this shard: test/backends/xeon/test_launch.py::TestTorchrun::test_cpu_info, test/backends/xeon/test_launch.py::TestTorchrun::test_multi_threads
2025-08-14T22:21:35.7512216Z 
2025-08-14T22:21:39.0057595Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:39.0063038Z   import pkg_resources
2025-08-14T22:21:39.1868225Z Running test_namedtensor 1/1 ... [2025-08-14 22:21:39.186406]
2025-08-14T22:21:39.1869008Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:39.1871349Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_namedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:39.186814]
2025-08-14T22:21:43.5091800Z 
2025-08-14T22:21:43.5093298Z test_namedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtensor_1.1_be431222e6346942_.log
2025-08-14T22:21:43.5140366Z Running 88 items in this shard: test/test_namedtensor.py::TestNamedTensor::test_aaa_must_run_first_check_experimental_warning, test/test_namedtensor.py::TestNamedTensor::test_addcmul_addcdiv, test/test_namedtensor.py::TestNamedTensor::test_addmm, test/test_namedtensor.py::TestNamedTensor::test_addmv, test/test_namedtensor.py::TestNamedTensor::test_align_as, test/test_namedtensor.py::TestNamedTensor::test_align_tensors, test/test_namedtensor.py::TestNamedTensor::test_align_tensors_two_inputs, test/test_namedtensor.py::TestNamedTensor::test_align_to, test/test_namedtensor.py::TestNamedTensor::test_align_to_ellipsis, test/test_namedtensor.py::TestNamedTensor::test_any_all, test/test_namedtensor.py::TestNamedTensor::test_as_strided, test/test_namedtensor.py::TestNamedTensor::test_as_strided_cuda, test/test_namedtensor.py::TestNamedTensor::test_autograd_ignores_names, test/test_namedtensor.py::TestNamedTensor::test_autograd_smoke, test/test_namedtensor.py::TestNamedTensor::test_autograd_warns_named_grad, test/test_namedtensor.py::TestNamedTensor::test_bernoulli, test/test_namedtensor.py::TestNamedTensor::test_big_tensor_repr_has_names, test/test_namedtensor.py::TestNamedTensor::test_binary_ops, test/test_namedtensor.py::TestNamedTensor::test_bitwise_not, test/test_namedtensor.py::TestNamedTensor::test_bmm, test/test_namedtensor.py::TestNamedTensor::test_cat, test/test_namedtensor.py::TestNamedTensor::test_cdist, test/test_namedtensor.py::TestNamedTensor::test_comparison_ops, test/test_namedtensor.py::TestNamedTensor::test_copy_transpose, test/test_namedtensor.py::TestNamedTensor::test_cummax_cummin, test/test_namedtensor.py::TestNamedTensor::test_detach, test/test_namedtensor.py::TestNamedTensor::test_diagonal, test/test_namedtensor.py::TestNamedTensor::test_dot, test/test_namedtensor.py::TestNamedTensor::test_equal, test/test_namedtensor.py::TestNamedTensor::test_expand, test/test_namedtensor.py::TestNamedTensor::test_factory_coverage, test/test_namedtensor.py::TestNamedTensor::test_factory_edge_cases, test/test_namedtensor.py::TestNamedTensor::test_flatten, test/test_namedtensor.py::TestNamedTensor::test_flatten_index_error, test/test_namedtensor.py::TestNamedTensor::test_flatten_nodims, test/test_namedtensor.py::TestNamedTensor::test_has_names, test/test_namedtensor.py::TestNamedTensor::test_index_fill, test/test_namedtensor.py::TestNamedTensor::test_info_smoke, test/test_namedtensor.py::TestNamedTensor::test_logcumsumexp, test/test_namedtensor.py::TestNamedTensor::test_logical_not, test/test_namedtensor.py::TestNamedTensor::test_logical_ops, test/test_namedtensor.py::TestNamedTensor::test_masked_fill, test/test_namedtensor.py::TestNamedTensor::test_masked_select, test/test_namedtensor.py::TestNamedTensor::test_matmul, test/test_namedtensor.py::TestNamedTensor::test_max_pooling, test/test_namedtensor.py::TestNamedTensor::test_max_pooling_without_names_does_not_warn, test/test_namedtensor.py::TestNamedTensor::test_mm, test/test_namedtensor.py::TestNamedTensor::test_mv, test/test_namedtensor.py::TestNamedTensor::test_no_jit_script_support, test/test_namedtensor.py::TestNamedTensor::test_no_jit_tracer_support, test/test_namedtensor.py::TestNamedTensor::test_no_multiprocessing_support, test/test_namedtensor.py::TestNamedTensor::test_no_pickle_support, test/test_namedtensor.py::TestNamedTensor::test_no_save_support, test/test_namedtensor.py::TestNamedTensor::test_noncontig_contiguous, test/test_namedtensor.py::TestNamedTensor::test_none_names_refcount, test/test_namedtensor.py::TestNamedTensor::test_nyi_dimname_overload_msg, test/test_namedtensor.py::TestNamedTensor::test_out_fn_semantics, test/test_namedtensor.py::TestNamedTensor::test_pow_special, test/test_namedtensor.py::TestNamedTensor::test_py3_ellipsis, test/test_namedtensor.py::TestNamedTensor::test_reduction_fns, test/test_namedtensor.py::TestNamedTensor::test_refine_names, test/test_namedtensor.py::TestNamedTensor::test_rename, test/test_namedtensor.py::TestNamedTensor::test_rename_, test/test_namedtensor.py::TestNamedTensor::test_rename_globber, test/test_namedtensor.py::TestNamedTensor::test_rename_rename_map, test/test_namedtensor.py::TestNamedTensor::test_repr, test/test_namedtensor.py::TestNamedTensor::test_resize, test/test_namedtensor.py::TestNamedTensor::test_select, test/test_namedtensor.py::TestNamedTensor::test_select_cuda, test/test_namedtensor.py::TestNamedTensor::test_set_names_property, test/test_namedtensor.py::TestNamedTensor::test_size, test/test_namedtensor.py::TestNamedTensor::test_split_fns_propagates_names, test/test_namedtensor.py::TestNamedTensor::test_squeeze, test/test_namedtensor.py::TestNamedTensor::test_stride, test/test_namedtensor.py::TestNamedTensor::test_support_device_named_grad, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_lists, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_named_tensor, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_numpy, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_tensor, test/test_namedtensor.py::TestNamedTensor::test_tensor_grad_is_unnamed, test/test_namedtensor.py::TestNamedTensor::test_transpose_variants, test/test_namedtensor.py::TestNamedTensor::test_trivial, test/test_namedtensor.py::TestNamedTensor::test_unary_propagate_names_fns, test/test_namedtensor.py::TestNamedTensor::test_unflatten, test/test_namedtensor.py::TestNamedTensor::test_unsupported_op_error_msg, test/test_namedtensor.py::TestNamedTensor::test_using_seen_interned_string_doesnt_bump_refcount, test/test_namedtensor.py::TestNamedTensor::test_using_unseen_interned_string_bumps_refcount_permanently, test/test_namedtensor.py::TestNamedTensor::test_using_unseen_uninterned_string_refcounts
2025-08-14T22:21:43.5183646Z 
2025-08-14T22:21:46.9041131Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:46.9043954Z   import pkg_resources
2025-08-14T22:21:47.0275427Z Running torch_np/test_ufuncs_basic 1/1 ... [2025-08-14 22:21:47.027116]
2025-08-14T22:21:47.0276346Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:47.0278988Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ufuncs_basic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:47.027558]
2025-08-14T22:21:51.7998153Z 
2025-08-14T22:21:51.7999349Z torch_np/test_ufuncs_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ufuncs_basic_1.1_0ec2bd4ea52a2741_.log
2025-08-14T22:21:51.8172438Z Running 371 items in this shard: test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_scalar_ufunc0, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_ufunc0, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_broadcast_ufunc0, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_equiv_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_equiv_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_equiv_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_no_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_no_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_no_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_safe_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_safe_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_safe_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_same_kind_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_same_kind_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_same_kind_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_unsafe_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_unsafe_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_out_casting_casting_unsafe_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc0, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc1, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc10, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc11, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc12, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc13, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc14, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc15, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc16, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc2, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc3, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc4, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc5, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc6, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc7, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc8, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_scalar_ufunc9, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc0, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc1, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc10, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc11, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc12, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc13, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc14, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc15, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc16, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc2, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc3, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc4, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc5, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc6, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc7, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc8, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_vector_vs_scalar_ufunc9, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc0, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc1, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc10, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc11, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc12, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc13, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc14, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc15, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc16, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc2, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc3, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc4, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc5, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc6, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc7, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc8, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_broadcast_ufunc9, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc10_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc10_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc10_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc11_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc11_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc11_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc12_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc12_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc12_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc13_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc14_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc14_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc14_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc15_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc15_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc15_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc16_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc16_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc16_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc1_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc1_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc1_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc2_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc2_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc2_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc3_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc3_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc3_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc4_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc4_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc4_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_equiv_ufunc5_out_dtype_complex128, 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test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc2_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc2_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc2_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc3_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc3_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc3_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc4_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc4_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc4_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc0_op0_iop0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc1_op1_iop1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc2_op2_iop2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc0_op0_iop0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc1_op1_iop1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc2_op2_iop2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestUfuncDtypeKwd::test_binary_ufunc_dtype, test/torch_np/test_ufuncs_basic.py::TestUfuncDtypeKwd::test_binary_ufunc_dtype_and_out
2025-08-14T22:21:51.8339307Z 
2025-08-14T22:21:55.0729174Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:21:55.0730696Z   import pkg_resources
2025-08-14T22:21:55.1975893Z Running test_meta 1/1 ... [2025-08-14 22:21:55.197156]
2025-08-14T22:21:55.1976796Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:21:55.1978027Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_meta.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:21:55.197502]
2025-08-14T22:22:46.7964227Z 
2025-08-14T22:22:46.7966037Z test_typing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_typing_1.1_23d041bd153b66d7_.log
2025-08-14T22:22:46.7975122Z Running 18 items in this shard: test/test_typing.py::TestTyping::test_fail_arithmetic_ops.py, test/test_typing.py::TestTyping::test_fail_creation_ops.py, test/test_typing.py::TestTyping::test_fail_random.py, test/test_typing.py::TestTyping::test_fail_torch_size.py, test/test_typing.py::TestTyping::test_reveal_module_list.py, test/test_typing.py::TestTyping::test_reveal_namedtuple.py, test/test_typing.py::TestTyping::test_reveal_opt_size.py, test/test_typing.py::TestTyping::test_reveal_size.py, test/test_typing.py::TestTyping::test_reveal_tensor_constructors.py, test/test_typing.py::TestTyping::test_reveal_tensor_copy.py, test/test_typing.py::TestTyping::test_reveal_tensor_sampling.py, test/test_typing.py::TestTyping::test_reveal_torch_optim.py, test/test_typing.py::TestTyping::test_success_arithmetic_ops.py, test/test_typing.py::TestTyping::test_success_creation_ops.py, test/test_typing.py::TestTyping::test_success_cuda_steam.py, test/test_typing.py::TestTyping::test_success_distributions.py, test/test_typing.py::TestTyping::test_success_math_ops.py, test/test_typing.py::TestTyping::test_success_torch_size.py
2025-08-14T22:22:46.7980378Z 
2025-08-14T22:22:50.2732064Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:22:50.2734842Z   import pkg_resources
2025-08-14T22:22:50.4034252Z Running test_utils_filelock 1/1 ... [2025-08-14 22:22:50.402985]
2025-08-14T22:22:50.4034880Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:22:50.4038177Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_filelock.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:22:50.403430]
2025-08-14T22:22:54.0235871Z 
2025-08-14T22:22:54.0237226Z test_utils_filelock 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_filelock_1.1_8dcdbda15dd05a09_.log
2025-08-14T22:22:54.0239314Z Running 2 items in this shard: test/test_utils_filelock.py::TestFileLock::test_no_crash, test/test_utils_filelock.py::TestFileLock::test_sequencing
2025-08-14T22:22:54.0240361Z 
2025-08-14T22:22:57.2664235Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:22:57.2667283Z   import pkg_resources
2025-08-14T22:22:57.3948084Z Running torch_np/test_random 1/1 ... [2025-08-14 22:22:57.394347]
2025-08-14T22:22:57.3948896Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:22:57.3951118Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_random.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:22:57.394759]
2025-08-14T22:23:01.0146322Z 
2025-08-14T22:23:01.0147647Z torch_np/test_random 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_random_1.1_330a1355969fc83c_.log
2025-08-14T22:23:01.0163425Z Running 41 items in this shard: test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_random_sample, test/torch_np/test_random.py::TestShuffle::test_1d_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_1d_use_numpy_True, test/torch_np/test_random.py::TestShuffle::test_2d_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_2d_use_numpy_True, test/torch_np/test_random.py::TestShuffle::test_shuffle_list_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_shuffle_list_use_numpy_True, test/torch_np/test_random.py::TestChoice::test_choice_use_numpy_False, test/torch_np/test_random.py::TestChoice::test_choice_use_numpy_True, test/torch_np/test_random.py::TestNumpyGlobal::test_numpy_global
2025-08-14T22:23:01.0177659Z 
2025-08-14T22:23:04.4008872Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:23:04.4012144Z   import pkg_resources
2025-08-14T22:23:04.5342724Z Running profiler/test_kineto 1/1 ... [2025-08-14 22:23:04.533883]
2025-08-14T22:23:04.5343197Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:23:04.5345817Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:23:04.534305]
2025-08-14T22:23:08.2554014Z 
2025-08-14T22:23:08.2555576Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_97a68862ed7f4233_.log
2025-08-14T22:23:08.2557859Z Running 1 items in this shard: test/profiler/test_kineto.py::SimpleKinetoInitializationTest::test_kineto_profiler_with_environment_variable
2025-08-14T22:23:08.2558995Z 
2025-08-14T22:23:11.7481928Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:23:11.7484795Z   import pkg_resources
2025-08-14T22:23:11.8792533Z Running test_compile_benchmark_util 1/1 ... [2025-08-14 22:23:11.878770]
2025-08-14T22:23:11.8793334Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:23:11.8796132Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_compile_benchmark_util.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:23:11.879254]
2025-08-14T22:23:17.0028562Z 
2025-08-14T22:23:17.0030502Z test_compile_benchmark_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_compile_benchmark_util_1.1_b7ab99f2976d0caa_.log
2025-08-14T22:23:17.0032896Z Running 1 items in this shard: test/test_compile_benchmark_util.py::TestCompileBenchmarkUtil::test_training_and_inference
2025-08-14T22:23:17.0034013Z 
2025-08-14T22:23:20.6541950Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:23:20.6544975Z   import pkg_resources
2025-08-14T22:23:20.7847695Z Running test_jiterator 1/1 ... [2025-08-14 22:23:20.784294]
2025-08-14T22:23:20.7848252Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:23:20.7850025Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jiterator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:23:20.784666]
2025-08-14T22:23:24.4388762Z 
2025-08-14T22:23:24.4390117Z test_jiterator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jiterator_1.1_9f8892057b76ce9a_.log
2025-08-14T22:23:24.4391300Z Running 0 items in this shard:
2025-08-14T22:23:27.8512641Z 
2025-08-14T22:23:27.8515476Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:23:27.8518322Z   import pkg_resources
2025-08-14T22:23:27.9822681Z Running test_optim 1/1 ... [2025-08-14 22:23:27.981813]
2025-08-14T22:23:27.9823416Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:23:27.9825876Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_optim.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:23:27.982289]
2025-08-14T22:25:00.0113892Z 
2025-08-14T22:25:00.0115147Z test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_1.1_2b6f5cb41656611c_.log
2025-08-14T22:25:00.0510019Z Running 966 items in this shard: test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_T_cur_reset, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_1, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_4, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr3, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr_state_dict, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_list, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_scalar, test/test_optim.py::TestLRScheduler::test_add_param_group_errors_reduce_lr_on_plateau, test/test_optim.py::TestLRScheduler::test_chained_lr1, test/test_optim.py::TestLRScheduler::test_chained_lr2, test/test_optim.py::TestLRScheduler::test_chained_lr2_get_last_lr_before_step, test/test_optim.py::TestLRScheduler::test_chained_lr3, test/test_optim.py::TestLRScheduler::test_chained_lr4, test/test_optim.py::TestLRScheduler::test_chained_lr5, test/test_optim.py::TestLRScheduler::test_closed_form_constantlr, test/test_optim.py::TestLRScheduler::test_closed_form_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_closed_form_exp_lr, test/test_optim.py::TestLRScheduler::test_closed_form_linearlr, test/test_optim.py::TestLRScheduler::test_closed_form_multi_step_lr, test/test_optim.py::TestLRScheduler::test_closed_form_poly_lr, test/test_optim.py::TestLRScheduler::test_closed_form_step_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_linearlr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_step_lr, test/test_optim.py::TestLRScheduler::test_compound_exp_and_linearlr, test/test_optim.py::TestLRScheduler::test_compound_exp_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_linearlr_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau1, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau5, test/test_optim.py::TestLRScheduler::test_compound_step_and_constantlr, test/test_optim.py::TestLRScheduler::test_compound_step_and_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_step_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass0, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass1, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass2, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass3, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass4, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass5, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass6, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass7, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass8, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass9, test/test_optim.py::TestLRScheduler::test_constant_initial_params_cyclelr, test/test_optim.py::TestLRScheduler::test_constant_initial_params_onecyclelr, test/test_optim.py::TestLRScheduler::test_constant_initial_params_swalr, test/test_optim.py::TestLRScheduler::test_constantlr, test/test_optim.py::TestLRScheduler::test_constantlr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_constantlr_with_epoch, test/test_optim.py::TestLRScheduler::test_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_cos_anneal_lr_continue, test/test_optim.py::TestLRScheduler::test_cosine_lr_state_dict, test/test_optim.py::TestLRScheduler::test_cosine_then_cyclic, test/test_optim.py::TestLRScheduler::test_cycle_lr_cycle_momentum_fail_with_momentumless_optimizer, test/test_optim.py::TestLRScheduler::test_cycle_lr_cycle_momentum_with_beta1_optimizer, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_invalid_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_removed_after_out_of_scope, test/test_optim.py::TestLRScheduler::test_cycle_lr_scale_fn_restored_from_state_dict, test/test_optim.py::TestLRScheduler::test_cycle_lr_state_dict_picklable, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr_no_momentum, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_with_adam, test/test_optim.py::TestLRScheduler::test_cycle_lr_with_momentumless_optimizer, test/test_optim.py::TestLRScheduler::test_error_when_getlr_has_epoch, test/test_optim.py::TestLRScheduler::test_exp_lr, test/test_optim.py::TestLRScheduler::test_exp_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_exponential_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_get_last_lr_constantlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_linearlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_multi_step_lr, test/test_optim.py::TestLRScheduler::test_get_last_lr_sequentiallr, test/test_optim.py::TestLRScheduler::test_get_last_lr_step_lr, test/test_optim.py::TestLRScheduler::test_lambda_lr, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_fn, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_obj, test/test_optim.py::TestLRScheduler::test_linear_linearlr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_linearlr, test/test_optim.py::TestLRScheduler::test_linearlr_start_factor_limits1, test/test_optim.py::TestLRScheduler::test_linearlr_start_factor_limits2, test/test_optim.py::TestLRScheduler::test_linearlr_with_epoch, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass0, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass1, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass10, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass11, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass12, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass2, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass3, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass4, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass5, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass6, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass7, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass8, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass9, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_on_plateau, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass11_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass11_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass1_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass1_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass2_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass2_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass4_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass4_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass5_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass5_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass7_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass7_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass8_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass8_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_True, test/test_optim.py::TestLRScheduler::test_multi_step_lr, test/test_optim.py::TestLRScheduler::test_multi_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_multi_step_lr_with_epoch, test/test_optim.py::TestLRScheduler::test_multiplicative_lr, test/test_optim.py::TestLRScheduler::test_multiplicative_lr_with_lr_lambda, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_arg, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_no_cyclic_references, test/test_optim.py::TestLRScheduler::test_no_cyclic_references_in_step, test/test_optim.py::TestLRScheduler::test_old_pattern_warning, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming_with_arg, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_arg, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_onecycle_lr_cannot_calculate_total_steps, test/test_optim.py::TestLRScheduler::test_onecycle_lr_cosine_annealing, test/test_optim.py::TestLRScheduler::test_onecycle_lr_invalid_anneal_strategy, test/test_optim.py::TestLRScheduler::test_onecycle_lr_invalid_pct_start, test/test_optim.py::TestLRScheduler::test_onecycle_lr_legacy_state_dict, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing_three_phases, test/test_optim.py::TestLRScheduler::test_poly_lr, test/test_optim.py::TestLRScheduler::test_polynomial_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau1, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau5, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau6, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau7, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau8, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau_get_last_lr_before_step, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau_state_dict, test/test_optim.py::TestLRScheduler::test_sequentiallr1, test/test_optim.py::TestLRScheduler::test_sequentiallr2, test/test_optim.py::TestLRScheduler::test_sequentiallr3, test/test_optim.py::TestLRScheduler::test_sequentiallr4, test/test_optim.py::TestLRScheduler::test_sequentiallr5, test/test_optim.py::TestLRScheduler::test_step_lr, test/test_optim.py::TestLRScheduler::test_step_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_swa_lr_state_dict, test/test_optim.py::TestLRScheduler::test_swalr_cosine_anneal_after_multiplicative, test/test_optim.py::TestLRScheduler::test_swalr_hypers, test/test_optim.py::TestLRScheduler::test_swalr_linear_anneal_after_multiplicative, test/test_optim.py::TestLRScheduler::test_swalr_no_anneal, test/test_optim.py::TestDifferentiableOptimizer::test_adadelta, test/test_optim.py::TestDifferentiableOptimizer::test_adagrad, test/test_optim.py::TestDifferentiableOptimizer::test_adam, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_betas, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_adamax, test/test_optim.py::TestDifferentiableOptimizer::test_adamw, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_betas, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_asgd, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_weight_decay_and_lr, test/test_optim.py::TestDifferentiableOptimizer::test_nadam, test/test_optim.py::TestDifferentiableOptimizer::test_radam, test/test_optim.py::TestDifferentiableOptimizer::test_rmsprop, test/test_optim.py::TestDifferentiableOptimizer::test_rprop, test/test_optim.py::TestDifferentiableOptimizer::test_sgd, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_False, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_True, test/test_optim.py::TestSWAUtils::test_averaged_model_default_avg_fn_picklable, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_True, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_True, test/test_optim.py::TestSWAUtils::test_averaged_model_mixed_device_ema_False, test/test_optim.py::TestSWAUtils::test_averaged_model_mixed_device_ema_True, test/test_optim.py::TestSWAUtils::test_averaged_model_state_dict, test/test_optim.py::TestSWAUtils::test_bn_update_eval_momentum, test/test_optim.py::TestSWAUtils::test_update_bn_cnn, test/test_optim.py::TestSWAUtils::test_update_bn_dnn, test/test_optim.py::TestOptimRenewedCPU::test_adamw_serialization_cpu, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_older_state_dict_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_ASGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adadelta_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adagrad_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_AdamW_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Adamax_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_LBFGS_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_NAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_RAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_RMSprop_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_Rprop_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_2d_SGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_ASGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adadelta_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adagrad_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_AdamW_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Adamax_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_LBFGS_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_NAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_RAdam_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_RMSprop_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_Rprop_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_complex_SGD_cpu_complex64, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_capturable_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_cpu_load_state_dict_impl_fused_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_deepcopy_copies_all_public_attrs_AdamW_cpu_float32, 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test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adafactor_cpu_float32, 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test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_SparseAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_SparseAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_second_order_optims_return_consistent_types_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_ASGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adadelta_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adafactor_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_AdamW_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adamax_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_NAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_RAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_RMSprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Rprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_pre_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_with_cuda_params_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_all_hooks_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_for_zero_grads_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_is_noop_when_params_have_no_grad_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_post_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_step_pre_hook_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_0_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_1_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_tensor_lr_num_dim_2_SparseAdam_cpu_float32
2025-08-14T22:25:00.0888930Z 
2025-08-14T22:25:03.4841205Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:25:03.4842942Z   import pkg_resources
2025-08-14T22:25:03.6113660Z Running test_decomp 1/1 ... [2025-08-14 22:25:03.610982]
2025-08-14T22:25:03.6114094Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:25:03.6117325Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:25:03.611423]
2025-08-14T22:25:39.5780876Z 
2025-08-14T22:25:39.5783862Z test_meta 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_meta_1.1_f5ea73142b39d809_.log
2025-08-14T22:25:41.0847978Z Running 40877 items in this shard: test/test_meta.py::TestMetaConverter::test_channels_last, test/test_meta.py::TestMetaConverter::test_channels_last_leaf, test/test_meta.py::TestMetaConverter::test_channels_last_non_leaf, test/test_meta.py::TestMetaConverter::test_complex_noncontiguous_bug, test/test_meta.py::TestMetaConverter::test_empty_strided_non_dense_leaf, test/test_meta.py::TestMetaConverter::test_imag, test/test_meta.py::TestMetaConverter::test_inplace_set_storage, test/test_meta.py::TestMetaConverter::test_leaf, test/test_meta.py::TestMetaConverter::test_non_leaf, test/test_meta.py::TestMetaConverter::test_non_leaf_torture, test/test_meta.py::TestMetaConverter::test_requires_grad_false, test/test_meta.py::TestMetaConverter::test_tensor_outlives_converter, test/test_meta.py::TestMetaConverter::test_view_as_complex, test/test_meta.py::TestMetaConverter::test_view_as_real, test/test_meta.py::TestMetaConverter::test_view_dtype, test/test_meta.py::TestMetaConverter::test_view_mutate, test/test_meta.py::TestMetaConverter::test_view_of_leaf, test/test_meta.py::TestMetaConverter::test_view_of_non_leaf, test/test_meta.py::TestMetaConverter::test_view_of_view_of_leaf, test/test_meta.py::TestMetaConverter::test_weakref, test/test_meta.py::TestMetaCPU::test_batch_norm_backward_output_mask0_cpu, test/test_meta.py::TestMetaCPU::test_batch_norm_backward_output_mask1_cpu, test/test_meta.py::TestMetaCPU::test_batch_norm_backward_output_mask2_cpu, test/test_meta.py::TestMetaCPU::test_batch_norm_backward_output_mask3_cpu, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___radd___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___rdiv___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___rmod___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___rmul___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___rpow___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype___rsub___cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs__conversions_complex_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs__conversions_polar_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_add_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_atan2_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_clamp_max_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_clamp_min_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_copysign_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_div_floor_rounding_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_div_no_rounding_mode_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_div_trunc_rounding_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_eq_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_float_power_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_floor_divide_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_fmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_fmin_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_fmod_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_ge_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_gt_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_heaviside_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_hypot_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_igamma_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_igammac_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_isclose_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_le_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_logaddexp_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_logical_and_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_logical_or_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_logical_xor_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_lt_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_maximum_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_minimum_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_mul_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_ne_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_nextafter_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_pow_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_remainder_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_rsub_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_special_xlog1py_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_special_zeta_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_sub_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_true_divide_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype__refs_xlogy_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_add_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_atan2_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_clamp_max_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_clamp_min_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_complex_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_copysign_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_div_floor_rounding_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_div_no_rounding_mode_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_div_trunc_rounding_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_eq_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_float_power_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_floor_divide_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_fmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_fmin_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_fmod_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_ge_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_gt_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_heaviside_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_hypot_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_igamma_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_igammac_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_isclose_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_jiterator_binary_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_jiterator_binary_return_by_ref_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_ldexp_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_le_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_logaddexp_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_logical_and_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_logical_or_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_logical_xor_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_lt_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_max_binary_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_maximum_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_min_binary_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_minimum_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_mul_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_ne_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_nextafter_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_polar_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_pow_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_remainder_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_rsub_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_t_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_u_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_v_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_w_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_hermite_polynomial_h_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_hermite_polynomial_he_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_laguerre_polynomial_l_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_legendre_polynomial_p_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_xlog1py_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_special_zeta_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_sub_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_true_divide_cpu_float32, test/test_meta.py::TestMetaCPU::test_binary_ufuncs_mixed_dtype_xlogy_cpu_float32, test/test_meta.py::TestMetaCPU::test_cdist_forward_cpu, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_H_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_H_cpu_bool, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_H_cpu_complex128, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_H_cpu_complex32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_H_cpu_complex64, 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test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_complex32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_complex64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_int16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_int32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_int64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_int8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_block_diag_cpu_uint8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bmm_cpu_complex128, 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test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_int16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_int32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_int64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_int8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_bucketize_cpu_uint8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_bool, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_complex128, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_complex64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_int16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_int32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_int64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_int8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_byte_cpu_uint8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_bool, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_complex128, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_complex64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_int16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_int32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_int64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_int8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cartesian_prod_cpu_uint8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_bool, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_complex128, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_complex32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_complex64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_int16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_int32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_int64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_int8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cat_cpu_uint8, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cauchy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cauchy_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cauchy_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cauchy_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdist_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdist_cpu_float64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_bool, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_complex128, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_complex32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_complex64, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_float16, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_float32, test/test_meta.py::TestMetaCPU::test_dispatch_meta_inplace_cdouble_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_trunc_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace__foreach_zero_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace__native_batch_norm_legit_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__native_batch_norm_legit_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__native_batch_norm_legit_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__native_batch_norm_legit_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_lengths_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_lengths_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_lengths_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_lengths_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_offsets_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_offsets_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_offsets_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__segment_reduce_offsets_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__softmax_backward_data_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__softmax_backward_data_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__softmax_backward_data_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__softmax_backward_data_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace__upsample_bilinear2d_aa_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace__upsample_bilinear2d_aa_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace__upsample_bilinear2d_aa_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_abs_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_acos_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_acosh_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_add_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addbmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcdiv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addcmul_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmm_decomposed_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addmv_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_addr_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_alias_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_all_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_allclose_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_amax_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_amin_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_aminmax_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_angle_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_any_cpu_bfloat16, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_bincount_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_and_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_left_shift_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_left_shift_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_left_shift_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_left_shift_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_left_shift_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_not_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_or_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_right_shift_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_right_shift_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_right_shift_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_right_shift_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_right_shift_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bitwise_xor_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_block_diag_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bool_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_shapes_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_tensors_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_broadcast_to_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_bucketize_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_byte_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cartesian_prod_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cat_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cauchy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cauchy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cauchy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cauchy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdist_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdist_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cdouble_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_ceil_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cfloat_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_chalf_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_char_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_inverse_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_inverse_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_inverse_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_inverse_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_solve_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_solve_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_solve_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_cholesky_solve_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_chunk_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_clamp_cpu_int8, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfc_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_erfinv_cpu_int64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_exp_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_as_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_expand_copy_cpu_complex128, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_expm1_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_exponential_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_exponential_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_exponential_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_exponential_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float8_e4m3fn, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float8_e4m3fnuz, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float8_e5m2, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_float8_e5m2fnuz, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_eye_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fft_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_fftn_cpu_uint8, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfft_cpu_complex64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfftn_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfftn_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfftn_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_hfftn_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifft_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftn_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftshift_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftshift_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftshift_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftshift_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ifftshift_cpu_complex64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfft_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfftn_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_ihfftn_cpu_float32, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fft_irfft_cpu_uint8, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fill_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_flatten_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_flip_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_flip_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_flip_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_fliplr_cpu_int8, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_uint16, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_uint32, test/test_meta.py::TestMetaCPU::test_meta_inplace_full_like_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_gather_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_gather_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_gather_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_gather_cpu_complex64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_log1p_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log2_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_log_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_normal_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_normal_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_normal_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_normal_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_log_softmax_with_dtype_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_logaddexp2_cpu_bfloat16, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_lt_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_solve_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_solve_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_solve_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_solve_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_unpack_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_unpack_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_unpack_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_lu_unpack_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mH_cpu_bfloat16, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_maximum_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_maximum_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_maximum_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mean_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_median_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_list_of_tensors_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_meshgrid_variadic_tensors_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_binary_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_no_dim_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_min_reduction_with_dim_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_minimum_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mode_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_movedim_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_msort_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mul_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_multinomial_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_multinomial_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_multinomial_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_multinomial_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mv_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nan_to_num_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmean_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmean_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmean_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmean_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanmedian_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanquantile_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nanquantile_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nansum_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_narrow_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_batch_norm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_batch_norm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_batch_norm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_batch_norm_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_native_layer_norm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_layer_norm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_native_layer_norm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ne_cpu_int8, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_channel_shuffle_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv1d_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv1d_cpu_complex128, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose1d_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose1d_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose1d_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose1d_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_nn_functional_conv_transpose2d_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_1_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_3_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_polygamma_polygamma_n_4_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_positive_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_pow_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_prod_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_prod_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_prod_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_prod_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_prod_cpu_float16, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_put_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_put_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_put_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_put_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_put_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_qr_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_qr_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_qr_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_qr_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_quantile_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_quantile_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_rad2deg_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_rand_like_cpu_float32, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_randn_like_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_ravel_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_real_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_reciprocal_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_remainder_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_renorm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_repeat_interleave_cpu_float64, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_as_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_as_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_as_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_as_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_as_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_reshape_cpu_int16, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_split_with_sizes_cpu_bool, 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test/test_meta.py::TestMetaCPU::test_meta_inplace_tanh_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensor_split_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tensordot_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tile_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_to_sparse_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_topk_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch__scaled_mm_cpu_float8_e4m3fn, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch__scaled_mm_cpu_float8_e4m3fnuz, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch__scaled_mm_cpu_float8_e5m2, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch__scaled_mm_cpu_float8_e5m2fnuz, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_torch_ops_aten__safe_softmax_default_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trace_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_transpose_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapezoid_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trapz_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_triangular_solve_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_triangular_solve_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_triangular_solve_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_triangular_solve_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_indices_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_tril_indices_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_indices_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_triu_indices_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_true_divide_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_trunc_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unbind_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unflatten_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_inplace_unfold_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_inplace_unfold_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_inplace_unfold_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_inplace_unfold_copy_cpu_complex32, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_acosh_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_add_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addbmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcdiv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addcmul_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmm_decomposed_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addmv_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_addr_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_alias_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_all_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_allclose_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_amax_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_amin_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_aminmax_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_angle_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_any_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_arange_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmax_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argmin_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argsort_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_argwhere_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_partial_views_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_as_strided_scatter_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_asin_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_asinh_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan2_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atan_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atanh_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_1d_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_2d_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_atleast_3d_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_baddbmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bernoulli_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bernoulli_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bernoulli_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bernoulli_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bfloat16_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bincount_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bincount_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bincount_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bincount_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bincount_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_and_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_left_shift_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_left_shift_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_left_shift_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_left_shift_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_left_shift_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_not_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_or_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_right_shift_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_right_shift_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_right_shift_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_right_shift_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_right_shift_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bitwise_xor_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_block_diag_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bmm_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_bool_cpu_int8, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfft_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfftn_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfftn_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfftn_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfftn_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_fft_ihfftn_cpu_int32, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_ravel_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_real_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_real_cpu_bool, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_interleave_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_interleave_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_repeat_interleave_cpu_complex128, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_indices_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_triu_indices_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_true_divide_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_true_divide_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_true_divide_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_true_divide_cpu_complex64, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_trunc_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_trunc_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_trunc_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_trunc_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unbind_copy_cpu_int16, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_uint16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_uint32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_uint64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unique_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unravel_index_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unravel_index_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unravel_index_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unravel_index_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unravel_index_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_chunk_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsafe_split_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_unsqueeze_copy_cpu_uint8, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_var_mean_unbiased_cpu_bfloat16, 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test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_vdot_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_complex_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_complex_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_complex_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_real_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_as_real_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_copy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_view_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_vsplit_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_vstack_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_where_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_xlogy_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zero__cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_cpu_uint8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_bfloat16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_bool, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_complex128, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_complex32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_complex64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_float16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_float32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_float64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_int16, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_int32, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_int64, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_int8, test/test_meta.py::TestMetaCPU::test_meta_outplace_zeros_like_cpu_uint8, test/test_meta.py::TestMetaCPU::test_nan_to_num_cpu, test/test_meta.py::TestMetaCPU::test_nonzero_cpu, test/test_meta.py::TestMetaCPU::test_quantized_embedding_bag_cpu, test/test_meta.py::TestMetaCPU::test_segment_reduce_backward_cpu, test/test_meta.py::TestMetaCPU::test_stride_for_index_Tensor_cpu, test/test_meta.py::TestMetaCPU::test_triangular_solve_out_cpu
2025-08-14T22:25:42.4883620Z 
2025-08-14T22:25:43.0052280Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:25:43.0055362Z   import pkg_resources
2025-08-14T22:25:43.1298740Z Running torch_np/test_basic 1/1 ... [2025-08-14 22:25:43.129489]
2025-08-14T22:25:43.1299588Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:25:43.1301696Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_basic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:25:43.129859]
2025-08-14T22:25:48.1018836Z 
2025-08-14T22:25:48.1020253Z torch_np/test_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_basic_1.1_1005c9e119c5a087_.log
2025-08-14T22:25:48.1158700Z Running 453 items in this shard: test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func0, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func1, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func10, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func11, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func12, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func13, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func14, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func15, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func16, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func17, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func18, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func19, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func2, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func20, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func21, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func22, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func23, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func24, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func25, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func26, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func27, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func28, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func29, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func3, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func30, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func31, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func32, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func33, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func34, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func35, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func36, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func37, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func38, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func39, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func4, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func40, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func41, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func42, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func43, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func44, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func45, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func46, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func47, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func48, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func49, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func5, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func50, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func51, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func52, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func53, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func54, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func55, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func56, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func57, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func58, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func59, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func6, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func60, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func61, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func62, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func63, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func64, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func65, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func66, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func67, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func68, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func69, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func7, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func70, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func71, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func72, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func73, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func74, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func8, test/torch_np/test_basic.py::TestOneArr::test_asarray_array_func9, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func0, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func1, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func10, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func11, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func12, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func13, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func14, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func15, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func16, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func17, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func18, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func19, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func2, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func20, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func21, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func22, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func23, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func24, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func25, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func26, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func27, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func28, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func29, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func3, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func30, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func31, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func32, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func33, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func34, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func35, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func36, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func37, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func38, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func39, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func4, test/torch_np/test_basic.py::TestOneArr::test_asarray_list_func40, 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test/torch_np/test_basic.py::TestOneArrAndAxis::test_andaxis_tensor_func9_axis_0, test/torch_np/test_basic.py::TestOneArrAndAxis::test_andaxis_tensor_func9_axis_1, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_array_func0_axes0, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_array_func0_axes1, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_array_func0_axes2, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_list_func0_axes0, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_list_func0_axes1, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_list_func0_axes2, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_tensor_func0_axes0, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_tensor_func0_axes1, test/torch_np/test_basic.py::TestOneArrAndAxesTuple::test_andtuple_tensor_func0_axes2, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_array_func0, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_array_func1, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_array_func2, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_array_func3, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_array_func4, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_list_func0, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_list_func1, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_list_func2, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_list_func3, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_list_func4, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_tensor_func0, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_tensor_func1, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_tensor_func2, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_tensor_func3, test/torch_np/test_basic.py::TestOneArrAndShape::test_andshape_tensor_func4, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_array_func0_np_func0, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_array_func1_np_func1, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_array_func2_np_func2, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_list_func0_np_func0, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_list_func1_np_func1, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_list_func2_np_func2, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_tensor_func0_np_func0, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_tensor_func1_np_func1, test/torch_np/test_basic.py::TestOneArrToScalar::test_toscalar_tensor_func2_np_func2, test/torch_np/test_basic.py::TestShapeLikeToArray::test_shape_func0, test/torch_np/test_basic.py::TestShapeLikeToArray::test_shape_func1, test/torch_np/test_basic.py::TestShapeLikeToArray::test_shape_func2, test/torch_np/test_basic.py::TestShapeLikeToArray::test_shape_func3, test/torch_np/test_basic.py::TestSequenceOfArrays::test_several_func0, test/torch_np/test_basic.py::TestSequenceOfArrays::test_several_func1, test/torch_np/test_basic.py::TestSequenceOfArrays::test_several_func2, test/torch_np/test_basic.py::TestSequenceOfArrays::test_several_func3, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_array_func0, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_array_func1, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_array_func2, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_array_func3, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_list_func0, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_list_func1, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_list_func2, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_list_func3, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_tensor_func0, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_tensor_func1, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_tensor_func2, test/torch_np/test_basic.py::TestSequenceOfArrays::test_single_tensor_func3, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func0, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func1, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func2, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func3, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func4, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func5, test/torch_np/test_basic.py::TestSequenceOfArraysToSingle::test_several_func6, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_array_func0, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_array_func1, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_list_func0, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_list_func1, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_tensor_func0, test/torch_np/test_basic.py::TestArrayToSequence::test_asarray_tensor_func1, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func0_args0, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func1_args1, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func2_args2, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func3_args3, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func4_args4, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func5_args5, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func6_args6, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func7_args7, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func8_args8, test/torch_np/test_basic.py::TestPythonArgsToArray::test_argstoarray_simple_func9_args9, test/torch_np/test_basic.py::TestNormalizations::test_too_few_args_positional, test/torch_np/test_basic.py::TestNormalizations::test_unknown_args, test/torch_np/test_basic.py::TestNormalizations::test_unknown_args_with_defaults, test/torch_np/test_basic.py::TestCopyTo::test_copyto_basic, test/torch_np/test_basic.py::TestCopyTo::test_copyto_typecast, test/torch_np/test_basic.py::TestCopyTo::test_copytobcast, test/torch_np/test_basic.py::TestDivmod::test_divmod_no_out, test/torch_np/test_basic.py::TestDivmod::test_divmod_out, test/torch_np/test_basic.py::TestDivmod::test_divmod_out_both_pos_and_kw, test/torch_np/test_basic.py::TestDivmod::test_divmod_out_list, test/torch_np/test_basic.py::TestDivmod::test_divmod_pos_only, test/torch_np/test_basic.py::TestSmokeNotImpl::test_nimpl_basic, test/torch_np/test_basic.py::TestDefaultDtype::test_defaultdtype_defaults, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_dt_float32, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_dt_pytorch, test/torch_np/test_basic.py::TestDefaultDtype::test_set_default_float_float32, test/torch_np/test_basic.py::TestExport::test_exported_objects, test/torch_np/test_basic.py::TestCtorNested::test_arrays_in_lists, test/torch_np/test_basic.py::TestMisc::test_f16_on_cuda, test/torch_np/test_basic.py::TestMisc::test_ndarrays_to_tensors
2025-08-14T22:25:48.1292834Z 
2025-08-14T22:25:51.3897951Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:25:51.3900871Z   import pkg_resources
2025-08-14T22:25:51.5163268Z Running lazy/test_bindings 1/1 ... [2025-08-14 22:25:51.515906]
2025-08-14T22:25:51.5164063Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:25:51.5166314Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_bindings.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:25:51.516317]
2025-08-14T22:25:54.9874207Z 
2025-08-14T22:25:54.9875587Z lazy/test_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_bindings_1.1_f6860d9e664654cf_.log
2025-08-14T22:25:54.9877961Z Running 1 items in this shard: test/lazy/test_bindings.py::test_metrics
2025-08-14T22:25:54.9878549Z 
2025-08-14T22:25:58.3934283Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:25:58.3935864Z   import pkg_resources
2025-08-14T22:25:58.5246314Z Running test_legacy_vmap 1/1 ... [2025-08-14 22:25:58.524128]
2025-08-14T22:25:58.5247010Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:25:58.5249039Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_legacy_vmap.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:25:58.524548]
2025-08-14T22:26:04.9517616Z 
2025-08-14T22:26:04.9519728Z test_legacy_vmap 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_legacy_vmap_1.1_c8749488397439c6_.log
2025-08-14T22:26:04.9559631Z Running 124 items in this shard: test/test_legacy_vmap.py::TestVmapAPILegacy::test_accepts_nested_inputs, test/test_legacy_vmap.py::TestVmapAPILegacy::test_backward_unsupported_interaction, test/test_legacy_vmap.py::TestVmapAPILegacy::test_batched_gradient_basic, test/test_legacy_vmap.py::TestVmapAPILegacy::test_constant_function, test/test_legacy_vmap.py::TestVmapAPILegacy::test_different_map_dim_size_raises, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_atan2, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_does_not_warn_by_default, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_masked_fill, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_multiple_returns, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_warns_when_warnings_are_enabled, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_with_undefined_grad, test/test_legacy_vmap.py::TestVmapAPILegacy::test_fallback_zero_dim, test/test_legacy_vmap.py::TestVmapAPILegacy::test_func_with_no_inputs, test/test_legacy_vmap.py::TestVmapAPILegacy::test_functools_partial, test/test_legacy_vmap.py::TestVmapAPILegacy::test_grad_unsupported_interaction, test/test_legacy_vmap.py::TestVmapAPILegacy::test_in_dim_not_in_tensor_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_in_dims_wrong_type_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_inplace_fallback_nary_different_levels, test/test_legacy_vmap.py::TestVmapAPILegacy::test_inplace_fallback_nary_same_levels, test/test_legacy_vmap.py::TestVmapAPILegacy::test_inplace_fallback_unary, test/test_legacy_vmap.py::TestVmapAPILegacy::test_integer_in_dim_but_not_tensor_input_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_multiple_inputs, test/test_legacy_vmap.py::TestVmapAPILegacy::test_multiple_out_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_multiple_outputs, test/test_legacy_vmap.py::TestVmapAPILegacy::test_multiple_outputs_error_cases, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nested_non_default_in_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nested_out_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nested_with_different_map_dim, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nested_with_same_map_dim, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nn_module, test/test_legacy_vmap.py::TestVmapAPILegacy::test_non_default_in_dims_out_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_non_tensor_output_raises, test/test_legacy_vmap.py::TestVmapAPILegacy::test_non_zero_in_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_none_in_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_nonzero_out_dims, test/test_legacy_vmap.py::TestVmapAPILegacy::test_noop_in_inner_vmap, test/test_legacy_vmap.py::TestVmapAPILegacy::test_not_enough_in_dims_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_out_dim_out_of_bounds_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_out_dims_and_num_outputs_mismatch_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_out_dims_edge_case, test/test_legacy_vmap.py::TestVmapAPILegacy::test_out_dims_must_be_int_or_tuple_of_int_err_msg, test/test_legacy_vmap.py::TestVmapAPILegacy::test_single_input, test/test_legacy_vmap.py::TestVmapAPILegacy::test_unsupported_op_err_msg, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_T_numpy, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_as_strided, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_binary_pointwise_ops, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_bmm, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_cat, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_chunk, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_clamp, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_clone, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_comparison_ops, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_conj, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_contiguous, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_diagonal, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_dot, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_expand_as, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_fill_and_zero_inplace, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_imag, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_is_complex, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_is_contiguous, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_is_floating_point, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_mm, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_movedim, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_mv, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_narrow, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_new_empty, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_new_empty_strided, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_new_zeros, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_no_random_op_support, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_real, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_reshape, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_reshape_as, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_result_type, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_select, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_slice, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_split, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_squeeze, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_stack, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_stride, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_sum_dim, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_t, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_tensor_split, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_to, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_trace, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_transpose, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_unary_pointwise_ops, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_unbind, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_unfold, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_view, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_view_as, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_view_as_complex, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_view_as_real, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_vmap_fallback_check, test/test_legacy_vmap.py::TestVmapOperatorsLegacy::test_vmap_fallback_check_ok, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_add_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_binary_cross_entropy_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_diagonal_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_div_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_expand_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_index_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_inplace_manyview_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_inplace_on_view_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_lgamma_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_log1p_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_log_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_logsumexp_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_max_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_median_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_min_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_mul_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_permute_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_reshape_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_select_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_sigmoid_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_slice_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_stack_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_sub_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_threshold_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_trace_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_unrelated_output_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_unrelated_output_multiple_grad_cpu, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_vmap_fallback_check, test/test_legacy_vmap.py::TestVmapBatchedGradientLegacyCPU::test_vmap_fallback_check_ok
2025-08-14T22:26:04.9597801Z 
2025-08-14T22:26:08.2690042Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:26:08.2692893Z   import pkg_resources
2025-08-14T22:26:08.3939708Z Running test_modules 1/2 ... [2025-08-14 22:26:08.393530]
2025-08-14T22:26:08.3940508Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:26:08.3943054Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:26:08.393971]
2025-08-14T22:28:26.3408379Z 
2025-08-14T22:28:26.3409933Z test_nestedtensor 1/4 was successful, full logs can be found in artifacts with path test/test-reports/test_nestedtensor_1.4_af4d2267ec649acb_.log
2025-08-14T22:28:26.3609880Z Running 378 items in this shard: test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_2d_nested_tensor_batch_size_2_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_2_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_batch_size_4_max_seq_len_5_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_3_vocab_size_10, test/test_nestedtensor.py::TestNestedTensor::test_3d_nested_tensor_float_batch_size_2_max_seq_len_3_vocab_size_20, test/test_nestedtensor.py::TestNestedTensor::test_cat, test/test_nestedtensor.py::TestNestedTensor::test_copy_, test/test_nestedtensor.py::TestNestedTensor::test_like_functions_randn_like, test/test_nestedtensor.py::TestNestedTensor::test_nested_tensor, test/test_nestedtensor.py::TestNestedTensor::test_size_dim, test/test_nestedtensor.py::TestNestedTensor::test_unbind_4, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_binary_ops_with_scalar_ge_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_cuda_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_bmm_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_detach_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_detach_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_device_checks_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_jagged_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_dropout_jagged_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_embedding_jagged_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_noncontiguous_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_linear_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_masked_fill_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_nt_with_broadcasted_t_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_matmul_with_bmm_path_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_128_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_128_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_384_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_dense_elementwise_embedding_dim_8_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_indexing_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_nested_tensor_mul_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_scaled_dot_product_attention_input_dim_3_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_serialization_requires_grad_False_weights_only_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_softmax_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim3_cpu_float16, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_dim4_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_to_padded_tensor_noncontiguous_cpu_float64, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_cos_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_silu_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_sin_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_sqrt_cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_unary_funcs_tanh__cpu, test/test_nestedtensor.py::TestNestedTensorDeviceTypeCPU::test_view_inference_mode_interaction_cpu_float32, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_add_strided_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_backward_for_add_op_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_dropout_backward_jagged_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_gelu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_5d_size_128_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_edge_case_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_128_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_4_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_layer_norm_backward_size_512_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_generates_leaf_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_linear_plus_transpose_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_reshape_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_reshape_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_softmax_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_nested_tensor_squeeze_gradcheck_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_relu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_selu_backward_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_to_buffer_series_ops_grad_with_broadcast_cpu, test/test_nestedtensor.py::TestNestedTensorAutogradCPU::test_values_grad_with_broadcast_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_0_layout_strided_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_1_layout_strided_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_jagged_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_True_contiguous_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_True_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_2_layout_strided_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_jagged_requires_grad_False_contiguous_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_jagged_requires_grad_False_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_jagged_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_jagged_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_strided_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_strided_requires_grad_True_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_strided_requires_grad_True_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_3_layout_strided_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_4_layout_jagged_requires_grad_False_contiguous_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_4_layout_jagged_requires_grad_True_contiguous_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_4_layout_strided_requires_grad_False_contiguous_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_4_layout_strided_requires_grad_False_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_as_nested_tensor_from_tensor_dim_4_layout_strided_requires_grad_True_contiguous_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_binary_pointwise_broadcasting_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_binary_pointwise_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_binary_pointwise_with_nested_int_second_arg_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_compile_padded_dense_conversion_preserves_metadata_cache_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_compile_preserves_metadata_cache_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_composite_op_with_custom_mode_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_construction_from_list_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_device_dtype_transfer_updates_offsets_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_flatten_decomp_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_flex_attention_noncontig_with_holes_False_cross_attention_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_flex_attention_noncontig_with_holes_True_cross_attention_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_flex_attention_noncontig_with_holes_True_cross_attention_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_is_contiguous_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_layout_construction_as_nested_tensor_components_require_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_layout_construction_as_nested_tensor_components_require_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_layout_construction_nested_tensor_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_layout_construction_nested_tensor_requires_grad_False_components_require_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_op_different_output_shape_dim_sum_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_op_different_output_shape_dim_sum_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_jagged_view_from_values_offsets_requires_grad_True_values_is_view_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_operate_on_batch_dim_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layer_norm_with_lengths_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_layout_under_torch_dispatch_mode_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_linear_nt_dim_3_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_linear_nt_dim_4_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_linear_nt_dim_5_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_mean_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_batch_only_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_1_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_mean_transpose_offset_1_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_mean_transpose_offset_2_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_mean_transpose_offset_2_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_mean_transpose_offset_2_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_mean_transpose_offset_2_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_sum_transpose_offset_2_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_reduce_ragged_idx_greater_than_1_different_output_shape_sum_transpose_offset_2_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_transpose_non_ragged_dim_different_output_shape_mean_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_transpose_non_ragged_dim_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_transpose_non_ragged_dim_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_mean_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_mean_keepdim_True_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_mean_keepdim_True_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_mean_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_False_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_op_dim_with_lengths_different_output_shape_sum_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_backwards_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_flop_counter_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_constant_sequence_length_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_constant_sequence_length_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sdpa_with_packed_in_proj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_1_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_reduce_ragged_idx_greater_than_1_same_output_shape_transpose_offset_2_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_requires_grad_True_components_require_grad_False_softmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_False_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_dim_with_lengths_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_True_components_require_grad_False_softmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_softmax_reduce_batch_dim_requires_grad_True_components_require_grad_True_softmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_specialize_dynamic_shape_recompile_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_squeeze_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_batch_and_non_batch_keepdim_False_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_False_requires_grad_False_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_sum_dim_reduce_ragged_and_non_batch_keepdim_True_requires_grad_True_components_require_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_False_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_2_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_3_requires_grad_False_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_compile_nt_dim_4_requires_grad_True_cpu_float32, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_False_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_float16, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_2_requires_grad_True_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_to_padded_tensor_nt_dim_3_requires_grad_True_cpu_bool, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_backward_cpu_float64, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_unbind_transpose_ragged_idx_3_cpu, test/test_nestedtensor.py::TestNestedTensorSubclassCPU::test_view_ragged_idx_not_one_cpu, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward___rmod___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_add_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_amin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_angle_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_asin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_atan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_ceil_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_chalf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_clamp_max_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_conj_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_erf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_exp2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_linalg_vector_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_logaddexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_masked_var_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_max_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_narrow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_celu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_hardtanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_logsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_softplus_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_softshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_polygamma_polygamma_n_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_positive_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_rad2deg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_real_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_reciprocal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_remainder_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sgn_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_i1e_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_special_ndtri_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_squeeze_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_backward_where_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward___rmod___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward___rpow___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward___rsub___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_abs_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_acos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_add_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_complex_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_ldexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_logsumexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_masked_sum_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_max_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_min_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_min_reduction_with_dim_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_mul_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_neg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_embedding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_nn_functional_rrelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_prod_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_reciprocal_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_special_xlog1py_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_split_with_sizes_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_sqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_std_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_true_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_backward_xlogy_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward___rpow___cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_abs_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_angle_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_argmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_atan2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_cfloat_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_char_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_deg2rad_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_div_floor_rounding_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erfc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_float_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_floor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_floor_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_frac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ge_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_half_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isclose_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_isneginf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_jiterator_binary_return_by_ref_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_not_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_logical_or_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_masked_amax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_ne_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_linear_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_logsigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_relu6_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_polar_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_polygamma_polygamma_n_1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_rad2deg_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_round_decimals_neg_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_rsub_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_short_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_sigmoid_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_sinc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_sinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_special_bessel_y0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_special_hermite_polynomial_he_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_special_spherical_bessel_j0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_special_zeta_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_split_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_tan_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_tanh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_true_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_compile_forward_trunc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_acos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_acosh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_add_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_asinh_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_cfloat_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_chunk_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_cos_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_count_nonzero_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_digamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_eq_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_erfc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_erfinv_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_exp2_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_float_power_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_floor_divide_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_fmin_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_frexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_igamma_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_igammac_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_isposinf_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_ldexp_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_log1p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_logical_xor_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_lt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_masked_argmax_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_masked_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_mean_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_min_binary_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_elu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_hardshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_prelu_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_rms_norm_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_softsign_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_tanhshrink_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_nn_functional_threshold_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_polygamma_polygamma_n_4_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_pow_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_decimals_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_round_decimals_neg_3_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_airy_ai_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_bessel_j0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_chebyshev_polynomial_v_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_erfcx_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_hermite_polynomial_he_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_legendre_polynomial_p_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_i0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_modified_bessel_i1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_scaled_modified_bessel_k0_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_special_scaled_modified_bessel_k1_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_split_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_sqrt_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_to_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_trunc_cpu_float32, test/test_nestedtensor.py::TestNestedTensorOpInfoCPU::test_forward_xlogy_cpu_float32
2025-08-14T22:28:26.3793944Z 
2025-08-14T22:28:30.2178665Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:28:30.2181898Z   import pkg_resources
2025-08-14T22:28:30.4077505Z Running test_modules 2/2 ... [2025-08-14 22:28:30.406838]
2025-08-14T22:28:30.4078553Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:28:30.4084189Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_modules.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:28:30.407311]
2025-08-14T22:28:33.0081712Z 
2025-08-14T22:28:33.0082532Z test_modules 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.2_28f319ba256aa9d6_.log
2025-08-14T22:28:33.0747527Z Running 1800 items in this shard: test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cpu_float32, 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test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNN_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNN_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCELoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCEWithLogitsLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Bilinear_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Bilinear_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CTCLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CosineEmbeddingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CrossEntropyLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Embedding_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRUCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRUCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardswish_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardtanh_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HuberLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HuberLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_KLDivLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_L1Loss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTMCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LayerNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LeakyReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LeakyReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Linear_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Linear_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LocalResponseNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LocalResponseNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSigmoid_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MSELoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Mish_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Mish_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_NLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_NLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNNCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU6_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Sigmoid_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SmoothL1Loss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SoftMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SoftMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmin_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softplus_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softplus_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softsign_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanh_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanhshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Threshold_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerDecoderLayer_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Transformer_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Transformer_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_True_set_grad_True_cpu_float32
2025-08-14T22:28:33.1390625Z 
2025-08-14T22:28:36.2536933Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:28:36.2540064Z   import pkg_resources
2025-08-14T22:28:36.3767987Z Running xpu/test_conv 1/1 ... [2025-08-14 22:28:36.376372]
2025-08-14T22:28:36.3769217Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:28:36.3771354Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:28:36.376719]
2025-08-14T22:28:40.2812014Z 
2025-08-14T22:28:40.2813269Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_e79888d419f9230f_.log
2025-08-14T22:28:40.2814456Z Running 0 items in this shard:
2025-08-14T22:28:40.2814858Z 
2025-08-14T22:28:43.4617675Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:28:43.4619225Z   import pkg_resources
2025-08-14T22:28:43.5878929Z Running test_ops_jit 2/2 ... [2025-08-14 22:28:43.587485]
2025-08-14T22:28:43.5879384Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:28:43.5882363Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:28:43.587902]
2025-08-14T22:29:56.3970230Z 
2025-08-14T22:29:56.3976591Z test_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.1_89062df4d577bfa2_.log
2025-08-14T22:29:56.9145126Z Running 9016 items in this shard: test/test_decomp.py::TestDecompCPU::test_arange_graph_cpu, test/test_decomp.py::TestDecompCPU::test_batch_norm_unflatten_weight_bias_cpu, test/test_decomp.py::TestDecompCPU::test_bernoulli_default_cpu, test/test_decomp.py::TestDecompCPU::test_broadcasting_index_copy_cpu, test/test_decomp.py::TestDecompCPU::test_cat_single_input_cpu, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvals_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvals_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_median_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_median_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_median_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_median_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_normalize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_normalize_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_softmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_std_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_masked_fill_cpu, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_igamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_igamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_igamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_igamma_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_uniform_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_amp_batch_norm_backward_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_contiguous_log_softmax_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_contiguous_softmax_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_elu_backward_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_exponential_non_inf_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_native_layer_norm_cpu_decomp_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_rms_norm_decomp_cuda_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_bfloat16, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float16, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_decomp.py::DecompOneOffTestsCPU::test_threshold_backward_dtype_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_weight_norm_interface_cpu, test/test_decomp.py::HasDecompTest::test_aten_core_operators, test/test_decomp.py::HasDecompTest::test_has_decomposition
2025-08-14T22:29:57.4121321Z 
2025-08-14T22:30:01.4260806Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:01.4263813Z   import pkg_resources
2025-08-14T22:30:01.6521570Z Running test_fx_reinplace_pass 1/1 ... [2025-08-14 22:30:01.650950]
2025-08-14T22:30:01.6522426Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:01.6524623Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_reinplace_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:01.651551]
2025-08-14T22:30:05.9276472Z 
2025-08-14T22:30:05.9277991Z test_fx_reinplace_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_reinplace_pass_1.1_5b467939ace940fb_.log
2025-08-14T22:30:05.9291650Z Running 12 items in this shard: test/test_fx_reinplace_pass.py::TestReinplacePass::test_out_node_updated, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_basic, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_different_metadata, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_index_mutation, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_overlapping_memory, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_op, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid2, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_valid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_sym_input, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_with_view
2025-08-14T22:30:05.9303558Z 
2025-08-14T22:30:09.8598487Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:09.8602220Z   import pkg_resources
2025-08-14T22:30:09.9876072Z Running nn/test_multihead_attention 1/1 ... [2025-08-14 22:30:09.987177]
2025-08-14T22:30:09.9876883Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:09.9880958Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:09.987716]
2025-08-14T22:30:22.5463708Z 
2025-08-14T22:30:22.5470754Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_721728df699ba9e4_.log
2025-08-14T22:30:22.5498300Z Running 19 items in this shard: test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_False, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_True, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_3d_attn_mask, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_fast_path_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_nested_tensor_outside_fast_path, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_no_bias, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_query_and_bias_have_different_dtypes_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_small_test_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_bias_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_weight_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_cpu, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_mock_cpu
2025-08-14T22:30:22.5522387Z 
2025-08-14T22:30:26.9460258Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:26.9463350Z   import pkg_resources
2025-08-14T22:30:27.0782112Z Running functorch/test_aot_joint_with_descriptors 1/1 ... [2025-08-14 22:30:27.077754]
2025-08-14T22:30:27.0782957Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:27.0784686Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aot_joint_with_descriptors.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:27.078133]
2025-08-14T22:30:38.0605718Z 
2025-08-14T22:30:38.0607567Z functorch/test_aot_joint_with_descriptors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aot_joint_with_descriptors_1.1_91e7ecf722e9a213_.log
2025-08-14T22:30:38.0617289Z Running 10 items in this shard: test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_conv_bn_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_export_and_compile, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_conv_bn_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_multiple_outputs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_node_consistency, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_simple_linear, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_in_out_specs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_module_with_kwargs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_multiple_outputs_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_simple_linear_module
2025-08-14T22:30:38.0626409Z 
2025-08-14T22:30:41.6319920Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:41.6321458Z   import pkg_resources
2025-08-14T22:30:41.7593142Z Running test_pruning_op 1/1 ... [2025-08-14 22:30:41.758904]
2025-08-14T22:30:41.7593620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:41.7596072Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_pruning_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:41.759272]
2025-08-14T22:30:45.6299698Z 
2025-08-14T22:30:45.6300875Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_837d1b261647ae1b_.log
2025-08-14T22:30:45.6302980Z Running 2 items in this shard: test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_32bit_indices, test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_64bit_indices
2025-08-14T22:30:45.6304325Z 
2025-08-14T22:30:48.9785206Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:48.9788466Z   import pkg_resources
2025-08-14T22:30:49.1663996Z Running lazy/test_functionalization 1/1 ... [2025-08-14 22:30:49.165847]
2025-08-14T22:30:49.1665692Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:49.1668031Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_functionalization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:49.166248]
2025-08-14T22:30:52.6860544Z 
2025-08-14T22:30:52.6861882Z lazy/test_functionalization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_functionalization_1.1_e1bc4e32b0213da2_.log
2025-08-14T22:30:52.6863720Z Running 2 items in this shard: test/lazy/test_functionalization.py::LazyFuncionalizationTest::test_data_assign, test/lazy/test_functionalization.py::LazyFuncionalizationTest::test_lazy_init_with_view
2025-08-14T22:30:52.6864643Z 
2025-08-14T22:30:56.0928900Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:30:56.0932112Z   import pkg_resources
2025-08-14T22:30:56.2241249Z Running functorch/test_ac 1/1 ... [2025-08-14 22:30:56.223692]
2025-08-14T22:30:56.2242029Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:30:56.2244148Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:30:56.224098]
2025-08-14T22:31:03.4705359Z 
2025-08-14T22:31:03.4706908Z functorch/test_ac 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_1.1_83fea658387b27d2_.log
2025-08-14T22:31:03.4708406Z 
2025-08-14T22:31:06.8849368Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:31:06.8850941Z   import pkg_resources
2025-08-14T22:31:07.0098504Z Running test_ops_fwd_gradients 1/2 ... [2025-08-14 22:31:07.009417]
2025-08-14T22:31:07.0099155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:31:07.0100973Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:31:07.009774]
2025-08-14T22:35:50.9749473Z 
2025-08-14T22:35:50.9750882Z test_modules 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_2.2_19ed825eacc55501_.log
2025-08-14T22:35:51.1127070Z Running 1805 items in this shard: test/test_modules.py::TestModuleCPU::test_check_inplace_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTM_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTM_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCELoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCEWithLogitsLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CTCLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CosineEmbeddingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CrossEntropyLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Embedding_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GaussianNLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GaussianNLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GroupNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GroupNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardswish_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardtanh_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HingeEmbeddingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HingeEmbeddingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_KLDivLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_L1Loss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTMCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LayerNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSigmoid_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSoftmax_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSoftmax_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MSELoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MarginRankingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MarginRankingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PoissonNLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PoissonNLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RMSNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RMSNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNNCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU6_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SiLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SiLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Sigmoid_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SmoothL1Loss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmin_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softsign_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanh_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanhshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Threshold_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerDecoderLayer_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_True_set_grad_False_cpu_float32
2025-08-14T22:35:51.2323086Z 
2025-08-14T22:35:52.3751031Z Uploading artifacts took 1.40 seconds
2025-08-14T22:35:54.5782571Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:35:54.5785743Z   import pkg_resources
2025-08-14T22:35:54.7590448Z Running test_ops_fwd_gradients 2/2 ... [2025-08-14 22:35:54.758509]
2025-08-14T22:35:54.7591291Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:35:54.7594676Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:35:54.758922]
2025-08-14T22:37:22.9590427Z 
2025-08-14T22:37:22.9591777Z test_ops_jit 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_2.2_db24bdb13dbc9158_.log
2025-08-14T22:37:22.9972539Z Running 540 items in this shard: test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_abs_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_acosh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_asinh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atan_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atanh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_cat_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_digamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_floor_rounding_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_no_rounding_mode_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erf_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erfc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_gt_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_le_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_householder_product_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_inv_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_matrix_power_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log1p_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log_softmax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_log_softmax_with_dtype_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_logit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_logsumexp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mH_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_max_binary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mul_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_ne_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_nn_functional_conv_transpose3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_round_decimals_neg_3_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_softmax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_transpose_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_trunc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_vstack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_T_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___getitem___cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___getitem___cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___rdiv___cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___rmatmul___cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___rmul___cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit___rmul___cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit__batch_norm_with_update_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit__chunk_cat_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit__native_batch_norm_legit_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_histogram_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_hsplit_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_hsplit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_igammac_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_fill_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_fill_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_put_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_put_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_reduce_amax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_reduce_amin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_reduce_prod_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_index_select_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_inner_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_int_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isclose_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isfinite_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isfinite_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isinf_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isinf_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_isnan_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_item_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_item_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_jiterator_2inputs_2outputs_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_jiterator_binary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_kron_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_kthvalue_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lerp_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lerp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_lgamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cholesky_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cholesky_ex_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cholesky_ex_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cond_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_cond_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_diagonal_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_diagonal_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eig_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_eigvalsh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_householder_product_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_householder_product_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_inv_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_matrix_rank_hermitian_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_multi_dot_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_norm_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_pinv_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_pinv_hermitian_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_pinv_hermitian_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_linalg_pinv_singular_cpu_complex64, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softmin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_softsign_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_threshold_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nonzero_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nonzero_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nonzero_static_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_fro_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_nuc_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_nuc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_normal_in_place_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_normal_number_mean_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ones_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ones_like_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ones_like_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ormqr_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_outer_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_2_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_3_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_4_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_positive_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_positive_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pow_cpu_complex64, 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2025-08-14T22:37:23.0273334Z 
2025-08-14T22:37:26.0727918Z 
2025-08-14T22:37:26.0729188Z test_ops_fwd_gradients 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_1.2_7eb8cc4cda8b4dfe_.log
2025-08-14T22:37:26.1971121Z Running 1603 items in this shard: test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_H_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_T_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___getitem___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___radd___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___radd___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rdiv___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rdiv___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmatmul___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmul___cpu_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_argmin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_cumprod_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_cumprod_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_cumsum_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_cumsum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_fill_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_log_softmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_logsumexp_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_logsumexp_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_normalize_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_prod_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_prod_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_select_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_select_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_softmin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_std_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_var_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_matmul_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_matmul_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_matrix_exp_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_max_binary_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_max_pool2d_with_indices_backward_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_max_reduction_no_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_max_reduction_with_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_meshgrid_list_of_tensors_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_meshgrid_list_of_tensors_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_meshgrid_variadic_tensors_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_msort_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mul_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mul_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_multinomial_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mv_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mv_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanmean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nansum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_batch_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_dropout_backward_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_native_layer_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ne_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_strided_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_strided_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_full_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_ones_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nextafter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_celu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv1d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv2d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cosine_similarity_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cross_entropy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_elu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_embedding_bag_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_glu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardtanh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_huber_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_instance_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_trilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_kl_div_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_l1_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_l1_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_layer_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_leaky_relu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_linear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_local_response_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_mish_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_mse_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multi_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_normalize_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_normalize_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_circular_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_relu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rms_norm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rms_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_silu_complex_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_silu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_smooth_l1_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_soft_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softplus_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softsign_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_upsample_nearest_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_static_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_fro_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_normal_in_place_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ones_like_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ones_like_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ormqr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_outer_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pca_lowrank_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pca_lowrank_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_permute_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pinverse_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pinverse_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polar_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polygamma_polygamma_n_2_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polygamma_polygamma_n_3_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pow_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_pow_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_qr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_quantile_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rand_like_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randint_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randint_like_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randn_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randn_like_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ravel_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_real_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reciprocal_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reciprocal_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_remainder_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_repeat_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_repeat_interleave_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_repeat_interleave_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reshape_as_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reshape_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resize__cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resize__cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resize_as__cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resolve_conj_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resolve_neg_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_roll_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rot90_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rot90_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_round_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_round_decimals_0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_round_decimals_3_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rsqrt_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rsub_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scalar_tensor_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scalar_tensor_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_add_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_reduce_amin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_searchsorted_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_select_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_select_scatter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sgn_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sigmoid_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sign_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_blackman_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_general_hamming_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_hamming_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_hann_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_nuttall_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sin_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sinc_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sinc_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sinh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sinh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_softmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_softmax_with_dtype_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_softmax_with_dtype_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sort_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sparse_sampled_addmm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_airy_ai_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_bessel_j1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_bessel_y0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_bessel_y1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_chebyshev_polynomial_w_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_erfcx_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_hermite_polynomial_he_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_i1e_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_laguerre_polynomial_l_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_legendre_polynomial_p_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_i1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_k1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_ndtr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_ndtri_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_w_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_xlog1py_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_list_args_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_multiple_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sub_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sub_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_to_size_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_lowrank_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_t_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_along_dim_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_along_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tan_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tanh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensordot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tile_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_sparse_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trace_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapezoid_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapezoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapz_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triangular_solve_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triangular_solve_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trunc_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unflatten_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_uniform_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unique_consecutive_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vdot_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_real_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vsplit_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vstack_cpu_complex128
2025-08-14T22:37:26.3324009Z 
2025-08-14T22:37:26.4654617Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:26.4657449Z   import pkg_resources
2025-08-14T22:37:26.5908777Z Running test_hub 1/1 ... [2025-08-14 22:37:26.590492]
2025-08-14T22:37:26.5909633Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:26.5912860Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_hub.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:26.590932]
2025-08-14T22:37:29.3164529Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:29.3167620Z   import pkg_resources
2025-08-14T22:37:29.4488729Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-08-14 22:37:29.448455]
2025-08-14T22:37:29.4489730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:29.4492355Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:29.448881]
2025-08-14T22:37:33.1194677Z 
2025-08-14T22:37:33.1196258Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_ae1690b59c23b98b_.log
2025-08-14T22:37:33.1199423Z Running 2 items in this shard: test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_exception, test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_no_exception
2025-08-14T22:37:33.1200587Z 
2025-08-14T22:37:36.4255954Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:36.4258767Z   import pkg_resources
2025-08-14T22:37:36.5525480Z Running test_stateless 1/1 ... [2025-08-14 22:37:36.552148]
2025-08-14T22:37:36.5526210Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:36.5529483Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_stateless.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:36.552570]
2025-08-14T22:37:38.6844523Z 
2025-08-14T22:37:38.6845501Z test_hub 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_hub_1.1_bf80a67e316dc8a0_.log
2025-08-14T22:37:38.6850811Z Running 20 items in this shard: test/test_hub.py::TestHub::test_download_url_to_file, test/test_hub.py::TestHub::test_get_set_dir, test/test_hub.py::TestHub::test_hub_parse_repo_info, test/test_hub.py::TestHub::test_list_entrypoints, test/test_hub.py::TestHub::test_load_commit_from_forked_repo, test/test_hub.py::TestHub::test_load_from_branch, test/test_hub.py::TestHub::test_load_from_github, test/test_hub.py::TestHub::test_load_from_local_dir, test/test_hub.py::TestHub::test_load_legacy_zip_checkpoint, test/test_hub.py::TestHub::test_load_state_dict_from_url, test/test_hub.py::TestHub::test_load_zip_1_6_checkpoint, test/test_hub.py::TestHub::test_trust_repo_builtin_trusted_owners, test/test_hub.py::TestHub::test_trust_repo_check_no, test/test_hub.py::TestHub::test_trust_repo_check_yes, test/test_hub.py::TestHub::test_trust_repo_false_emptystring, test/test_hub.py::TestHub::test_trust_repo_false_no, test/test_hub.py::TestHub::test_trust_repo_legacy, test/test_hub.py::TestHub::test_trust_repo_none, test/test_hub.py::TestHub::test_trust_repo_true, test/test_hub.py::TestHub::test_trusted_repo_false_yes
2025-08-14T22:37:38.6855216Z 
2025-08-14T22:37:42.1355041Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:42.1358397Z   import pkg_resources
2025-08-14T22:37:42.3254090Z Running distributions/test_constraints 1/1 ... [2025-08-14 22:37:42.324360]
2025-08-14T22:37:42.3255157Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:42.3257352Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_constraints.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:42.324801]
2025-08-14T22:37:46.7340390Z 
2025-08-14T22:37:46.7341860Z test_stateless 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_stateless_1.1_fbdfc6c73b65fa69_.log
2025-08-14T22:37:46.7367724Z Running 50 items in this shard: test/test_stateless.py::TestStatelessFunctionalAPI::test_circular_references_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_circular_references_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_batch_norm_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_batch_norm_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_member_reference_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_member_reference_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_multiple_dicts_error, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_tuple_dicts, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_error_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_error_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_data_parallel_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_gradient_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_gradient_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_jit_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_jit_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_kwargs_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_functional_call_with_kwargs_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_in_place_operator_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_in_place_operator_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_module_fail_reset_to_original_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_module_fail_reset_to_original_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_some_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_some_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_special_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_special_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_some_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_some_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrize_tie_weights_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrized_module_change_parametrization_original_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_reparametrized_module_change_parametrization_original_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_strict_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_strict_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_setattr_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_errors_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_errors_torch_func, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_no_error_without_flag, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_warns_stateless, test/test_stateless.py::TestStatelessFunctionalAPI::test_tied_weights_warns_torch_func, test/test_stateless.py::TestStatelessDeprecation::test_private_stateless_warns, test/test_stateless.py::TestStatelessDeprecation::test_stateless_functional_call_warns, test/test_stateless.py::TestPythonOptimizeMode::test_runs_with_optimize_flag
2025-08-14T22:37:46.7390320Z 
2025-08-14T22:37:46.9125106Z 
2025-08-14T22:37:46.9126744Z distributions/test_constraints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_constraints_1.1_3fc24a18715ac624_.log
2025-08-14T22:37:46.9236907Z Running 136 items in this shard: test/distributions/test_constraints.py::test_constraint[False-constraint_fn0-False-value0], test/distributions/test_constraints.py::test_constraint[False-constraint_fn1-False-value1], test/distributions/test_constraints.py::test_constraint[False-constraint_fn2-False-value2], test/distributions/test_constraints.py::test_constraint[False-constraint_fn3-True-value3], test/distributions/test_constraints.py::test_constraint[False-constraint_fn4-False-value4], test/distributions/test_constraints.py::test_constraint[False-constraint_fn5-False-value5], test/distributions/test_constraints.py::test_constraint[False-constraint_fn6-True-value6], test/distributions/test_constraints.py::test_constraint[False-constraint_fn7-True-value7], test/distributions/test_constraints.py::test_constraint[False-constraint_fn8-False-value8], test/distributions/test_constraints.py::test_constraint[False-constraint_fn9-True-value9], test/distributions/test_constraints.py::test_constraint[False-constraint_fn10-False-value10], test/distributions/test_constraints.py::test_constraint[False-constraint_fn11-False-value11], test/distributions/test_constraints.py::test_constraint[False-constraint_fn12-True-value12], test/distributions/test_constraints.py::test_constraint[False-constraint_fn13-True-value13], test/distributions/test_constraints.py::test_constraint[False-constraint_fn14-False-value14], test/distributions/test_constraints.py::test_constraint[False-constraint_fn15-True-value15], test/distributions/test_constraints.py::test_constraint[False-constraint_fn16-True-value16], test/distributions/test_constraints.py::test_constraint[False-constraint_fn17-True-value17], test/distributions/test_constraints.py::test_constraint[True-constraint_fn0-False-value0], test/distributions/test_constraints.py::test_constraint[True-constraint_fn1-False-value1], test/distributions/test_constraints.py::test_constraint[True-constraint_fn2-False-value2], test/distributions/test_constraints.py::test_constraint[True-constraint_fn3-True-value3], test/distributions/test_constraints.py::test_constraint[True-constraint_fn4-False-value4], test/distributions/test_constraints.py::test_constraint[True-constraint_fn5-False-value5], test/distributions/test_constraints.py::test_constraint[True-constraint_fn6-True-value6], test/distributions/test_constraints.py::test_constraint[True-constraint_fn7-True-value7], test/distributions/test_constraints.py::test_constraint[True-constraint_fn8-False-value8], test/distributions/test_constraints.py::test_constraint[True-constraint_fn9-True-value9], test/distributions/test_constraints.py::test_constraint[True-constraint_fn10-False-value10], test/distributions/test_constraints.py::test_constraint[True-constraint_fn11-False-value11], test/distributions/test_constraints.py::test_constraint[True-constraint_fn12-True-value12], test/distributions/test_constraints.py::test_constraint[True-constraint_fn13-True-value13], test/distributions/test_constraints.py::test_constraint[True-constraint_fn14-False-value14], test/distributions/test_constraints.py::test_constraint[True-constraint_fn15-True-value15], test/distributions/test_constraints.py::test_constraint[True-constraint_fn16-True-value16], test/distributions/test_constraints.py::test_constraint[True-constraint_fn17-True-value17], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn0-args0], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn1-args1], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn2-args2], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args3], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args4], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args5], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThan-args6], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_biject_to[False-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args10], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args11], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args12], test/distributions/test_constraints.py::test_biject_to[False-_LessThan-args13], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn14-args14], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args15], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args16], test/distributions/test_constraints.py::test_biject_to[False-_Interval-args17], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_biject_to[False-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn21-args21], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn22-args22], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn23-args23], test/distributions/test_constraints.py::test_biject_to[False-constraint_fn24-args24], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn0-args0], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn1-args1], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn2-args2], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args3], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args4], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args5], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThan-args6], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_biject_to[True-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args10], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args11], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args12], test/distributions/test_constraints.py::test_biject_to[True-_LessThan-args13], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn14-args14], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args15], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args16], test/distributions/test_constraints.py::test_biject_to[True-_Interval-args17], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_biject_to[True-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn21-args21], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn22-args22], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn23-args23], test/distributions/test_constraints.py::test_biject_to[True-constraint_fn24-args24], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn0-args0], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn1-args1], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn2-args2], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args3], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args4], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args5], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThan-args6], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_transform_to[False-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args10], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args11], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args12], test/distributions/test_constraints.py::test_transform_to[False-_LessThan-args13], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn14-args14], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args15], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args16], test/distributions/test_constraints.py::test_transform_to[False-_Interval-args17], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_transform_to[False-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn21-args21], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn22-args22], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn23-args23], test/distributions/test_constraints.py::test_transform_to[False-constraint_fn24-args24], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn0-args0], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn1-args1], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn2-args2], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args3], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args4], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args5], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThan-args6], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args7], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args8], test/distributions/test_constraints.py::test_transform_to[True-_GreaterThanEq-args9], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args10], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args11], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args12], test/distributions/test_constraints.py::test_transform_to[True-_LessThan-args13], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn14-args14], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args15], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args16], test/distributions/test_constraints.py::test_transform_to[True-_Interval-args17], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args18], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args19], test/distributions/test_constraints.py::test_transform_to[True-_HalfOpenInterval-args20], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn21-args21], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn22-args22], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn23-args23], test/distributions/test_constraints.py::test_transform_to[True-constraint_fn24-args24]
2025-08-14T22:37:46.9331849Z 
2025-08-14T22:37:50.6469956Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:50.6473818Z   import pkg_resources
2025-08-14T22:37:50.7726903Z Running profiler/test_record_function 1/1 ... [2025-08-14 22:37:50.772189]
2025-08-14T22:37:50.7727764Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:50.7730437Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_record_function.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:50.772630]
2025-08-14T22:37:50.9773849Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:50.9776659Z   import pkg_resources
2025-08-14T22:37:51.1210535Z Running nn/test_lazy_modules 1/1 ... [2025-08-14 22:37:51.120587]
2025-08-14T22:37:51.1211367Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:51.1216477Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:51.121274]
2025-08-14T22:37:54.2945178Z 
2025-08-14T22:37:54.2947139Z profiler/test_record_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_record_function_1.1_9b4c800c9ae10983_.log
2025-08-14T22:37:54.2950141Z Running 4 items in this shard: test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_delegation_with_profiler, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function_fork, test/profiler/test_record_function.py::TestRecordFunction::test_record_function
2025-08-14T22:37:54.2952155Z 
2025-08-14T22:37:55.3622510Z 
2025-08-14T22:37:55.3623949Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_d96c3b203bed5642_.log
2025-08-14T22:37:55.3643646Z Running 59 items in this shard: test/nn/test_lazy_modules.py::TestLazyModules::test_chained_initialization, test/nn/test_lazy_modules.py::TestLazyModules::test_invalid_functions, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm_with_dict_input, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transposed1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_forward_hook, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_linear_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_linear_state_and_forward, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_jit_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_jit_param, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_parameter, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_pre_forward_hook, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_share_memory_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_share_memory_param, test/nn/test_lazy_modules.py::TestLazyModules::test_linear, test/nn/test_lazy_modules.py::TestLazyModules::test_linear_state, test/nn/test_lazy_modules.py::TestLazyModules::test_materialize_device, test/nn/test_lazy_modules.py::TestLazyModules::test_materialize_dtype, test/nn/test_lazy_modules.py::TestLazyModules::test_optimizer_pass, test/nn/test_lazy_modules.py::TestLazyModules::test_spectral_norm, test/nn/test_lazy_modules.py::TestLazyModules::test_weight_norm
2025-08-14T22:37:55.3661929Z 
2025-08-14T22:37:57.8600730Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:57.8603593Z   import pkg_resources
2025-08-14T22:37:57.9847939Z Running test_jit_fuser_te 1/1 ... [2025-08-14 22:37:57.984225]
2025-08-14T22:37:57.9849115Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:57.9852268Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_fuser_te.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:57.984577]
2025-08-14T22:37:59.0106716Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:37:59.0110060Z   import pkg_resources
2025-08-14T22:37:59.1361349Z Running test_segment_reductions 1/1 ... [2025-08-14 22:37:59.135514]
2025-08-14T22:37:59.1362521Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:37:59.1368390Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:37:59.135965]
2025-08-14T22:38:04.6604895Z 
2025-08-14T22:38:04.6608227Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_984dc0bde68fac7f_.log
2025-08-14T22:38:04.6644622Z Running 74 items in this shard: test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int64
2025-08-14T22:38:04.6678942Z 
2025-08-14T22:38:07.8427342Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:38:07.8429008Z   import pkg_resources
2025-08-14T22:38:07.9652263Z Running test_import_stats 1/1 ... [2025-08-14 22:38:07.964829]
2025-08-14T22:38:07.9652724Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:38:07.9655215Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:38:07.965231]
2025-08-14T22:38:14.5915698Z 
2025-08-14T22:38:14.5917256Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_b63b953b5ee8590a_.log
2025-08-14T22:38:14.5918597Z Running 2 items in this shard: test/test_import_stats.py::TestImportTime::test_time_cuda_device_count, test/test_import_stats.py::TestImportTime::test_time_import_torch
2025-08-14T22:38:14.5919328Z 
2025-08-14T22:38:17.8303195Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:38:17.8304746Z   import pkg_resources
2025-08-14T22:38:17.9528432Z Running test_masked 1/1 ... [2025-08-14 22:38:17.952450]
2025-08-14T22:38:17.9529103Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:38:17.9530628Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_masked.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:38:17.952817]
2025-08-14T22:38:52.0673230Z 
2025-08-14T22:38:52.0674529Z test_masked 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_masked_1.1_2b3070c29378a936_.log
2025-08-14T22:38:52.0788169Z Running 194 items in this shard: test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_where_coo_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_coo_fill_value_123_cpu, test/test_masked.py::TestMaskedCPU::test_where_csr_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_csr_fill_value_123_cpu, test/test_masked.py::TestMaskedCPU::test_where_hybrid_coo_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_hybrid_coo_fill_value_123_cpu
2025-08-14T22:38:52.0931116Z 
2025-08-14T22:38:55.5893143Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:38:55.5896537Z   import pkg_resources
2025-08-14T22:38:55.7259672Z Running test_cuda_sanitizer 1/1 ... [2025-08-14 22:38:55.725547]
2025-08-14T22:38:55.7260533Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:38:55.7263509Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_sanitizer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:38:55.726003]
2025-08-14T22:38:59.5904103Z 
2025-08-14T22:38:59.5905542Z test_cuda_sanitizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_sanitizer_1.1_43615a7d4e55935e_.log
2025-08-14T22:38:59.5907023Z Running 0 items in this shard:
2025-08-14T22:38:59.5907402Z 
2025-08-14T22:39:03.4811183Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:39:03.4814205Z   import pkg_resources
2025-08-14T22:39:03.6169273Z Running test_monitor 1/1 ... [2025-08-14 22:39:03.616479]
2025-08-14T22:39:03.6170045Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:39:03.6173074Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:39:03.616945]
2025-08-14T22:39:07.4881063Z 
2025-08-14T22:39:07.4881997Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_8cd9f4fa8f73044e_.log
2025-08-14T22:39:07.4884076Z Running 6 items in this shard: test/test_monitor.py::TestMonitor::test_event_handler, test/test_monitor.py::TestMonitor::test_fixed_count_stat, test/test_monitor.py::TestMonitor::test_interval_stat, test/test_monitor.py::TestMonitor::test_log_event, test/test_monitor.py::TestMonitor::test_wait_counter, test/test_monitor.py::TestMonitorTensorboard::test_event_handler
2025-08-14T22:39:07.4885618Z 
2025-08-14T22:39:11.4928330Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:39:11.4931406Z   import pkg_resources
2025-08-14T22:39:11.6286006Z Running profiler/test_cpp_thread 1/1 ... [2025-08-14 22:39:11.628156]
2025-08-14T22:39:11.6286899Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:39:11.6289370Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:39:11.628543]
2025-08-14T22:39:15.7502965Z 
2025-08-14T22:39:15.7504394Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_81eaac614adba81e_.log
2025-08-14T22:39:15.7510314Z Running 6 items in this shard: test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_profile_memory_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_with_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_without_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_profile_memory_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_with_enable_profiler_in_child_thread_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_without_enable_profiler_in_child_thread_xpu
2025-08-14T22:39:15.7515103Z 
2025-08-14T22:39:19.4433705Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:39:19.4437720Z   import pkg_resources
2025-08-14T22:39:19.5815193Z Running test_subclass 1/1 ... [2025-08-14 22:39:19.580711]
2025-08-14T22:39:19.5817385Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:39:19.5820151Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_subclass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:39:19.581225]
2025-08-14T22:39:25.4556883Z 
2025-08-14T22:39:25.4558298Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_40a936d8f6c00389_.log
2025-08-14T22:39:25.4636902Z Running 100 items in this shard: test/test_subclass.py::TestSubclass::test_deepcopy_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_lazy_module_base_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_diag_tensor_below, test/test_subclass.py::TestSubclass::test_lazy_module_logging_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_non_wrapper_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_sparse_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_wrapper_with_custom_sizes, test/test_subclass.py::TestSubclass::test_lazy_module_wrapper_with_custom_strides, test/test_subclass.py::TestSubclass::test_module_optimization_base_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_diag_tensor_below, test/test_subclass.py::TestSubclass::test_module_optimization_logging_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_non_wrapper_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_sparse_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_wrapper_with_custom_sizes, test/test_subclass.py::TestSubclass::test_module_optimization_wrapper_with_custom_strides, test/test_subclass.py::TestSubclass::test_non_rewrapping_torch_dispatch_subclass_as_parameter_throws_for_detach, test/test_subclass.py::TestSubclass::test_param_invariants_base_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_base_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_diag_tensor_below_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_diag_tensor_below_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_logging_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_logging_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_non_wrapper_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_non_wrapper_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_sparse_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_sparse_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_sizes_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_sizes_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_strides_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_strides_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_parametrization_base_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_base_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_diag_tensor_below_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_diag_tensor_below_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_logging_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_logging_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_non_wrapper_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_non_wrapper_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_sparse_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_sparse_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_sizes_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_sizes_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_strides_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_strides_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_repr_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_repr_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_repr_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_tensor_subclass_storage_data_accesses_throw, test/test_subclass.py::TestSubclass::test_type_propagation_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_strides_as_param_True
2025-08-14T22:39:25.4715322Z 
2025-08-14T22:39:30.6290138Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:39:30.6293120Z   import pkg_resources
2025-08-14T22:39:30.8655923Z Running profiler/test_profiler 1/1 ... [2025-08-14 22:39:30.865022]
2025-08-14T22:39:30.8656793Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:39:30.8663580Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:39:30.865631]
2025-08-14T22:39:54.5209332Z 
2025-08-14T22:39:54.5215656Z profiler/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_1.1_990f929709597c4d_.log
2025-08-14T22:39:54.5265963Z Running 70 items in this shard: test/profiler/test_profiler.py::TestProfilerCUDA::test_cudagraph_profiling_workaround, test/profiler/test_profiler.py::TestProfilerCUDA::test_custom_module_input_op_ids, test/profiler/test_profiler.py::TestProfilerCUDA::test_mem_leak, test/profiler/test_profiler.py::TestProfilerITT::test_custom_module_input_op_ids, test/profiler/test_profiler.py::TestProfiler::test_basic_chrome_trace, test/profiler/test_profiler.py::TestProfiler::test_basic_profile, test/profiler/test_profiler.py::TestProfiler::test_concrete_inputs_profiling, test/profiler/test_profiler.py::TestProfiler::test_concrete_inputs_profiling_toggling, test/profiler/test_profiler.py::TestProfiler::test_cpu_annotation_overlap, test/profiler/test_profiler.py::TestProfiler::test_disable_external_correlation, test/profiler/test_profiler.py::TestProfiler::test_dynamic_toggle, test/profiler/test_profiler.py::TestProfiler::test_event_list, test/profiler/test_profiler.py::TestProfiler::test_export_stacks, test/profiler/test_profiler.py::TestProfiler::test_flops, test/profiler/test_profiler.py::TestProfiler::test_forked_process, test/profiler/test_profiler.py::TestProfiler::test_guarded_record_function_fast, test/profiler/test_profiler.py::TestProfiler::test_high_level_trace, test/profiler/test_profiler.py::TestProfiler::test_is_profiler_enabled, test/profiler/test_profiler.py::TestProfiler::test_kineto, test/profiler/test_profiler.py::TestProfiler::test_kineto_multigpu, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_api, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_multiple_steppers, test/profiler/test_profiler.py::TestProfiler::test_kineto_profiler_with_environment_variable, test/profiler/test_profiler.py::TestProfiler::test_lazy_build_tree, test/profiler/test_profiler.py::TestProfiler::test_memory_profiler, test/profiler/test_profiler.py::TestProfiler::test_module_hierarchy, test/profiler/test_profiler.py::TestProfiler::test_nested_tensor_with_shapes, test/profiler/test_profiler.py::TestProfiler::test_oom_tracing, test/profiler/test_profiler.py::TestProfiler::test_override_time_units, test/profiler/test_profiler.py::TestProfiler::test_profile_all_threads, test/profiler/test_profiler.py::TestProfiler::test_profiler_correlation_id, test/profiler/test_profiler.py::TestProfiler::test_profiler_cuda_sync_events, test/profiler/test_profiler.py::TestProfiler::test_profiler_disable_fwd_bwd_link, test/profiler/test_profiler.py::TestProfiler::test_profiler_fwd_bwd_link, test/profiler/test_profiler.py::TestProfiler::test_profiler_metadata, test/profiler/test_profiler.py::TestProfiler::test_profiler_op_event_args, test/profiler/test_profiler.py::TestProfiler::test_profiler_op_event_kwargs, test/profiler/test_profiler.py::TestProfiler::test_profiler_strides, test/profiler/test_profiler.py::TestProfiler::test_profiler_time_scale, test/profiler/test_profiler.py::TestProfiler::test_profiler_tracing, test/profiler/test_profiler.py::TestProfiler::test_profiler_type, test/profiler/test_profiler.py::TestProfiler::test_record_function_fast, test/profiler/test_profiler.py::TestProfiler::test_schedule_function_count, test/profiler/test_profiler.py::TestProfiler::test_skip_first_wait, test/profiler/test_profiler.py::TestProfiler::test_source, test/profiler/test_profiler.py::TestProfiler::test_tensorboard_trace_handler, test/profiler/test_profiler.py::TestProfiler::test_user_annotation, test/profiler/test_profiler.py::TestExperimentalUtils::test_bfs, test/profiler/test_profiler.py::TestExperimentalUtils::test_dfs, test/profiler/test_profiler.py::TestExperimentalUtils::test_fuzz_symbolize, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_conv2d_bias_followed_by_batchnorm2d_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_debug_autotuner, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_extra_cuda_copy_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_extra_cuda_copy_pattern_benchmark, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_for_loop_indexing_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_fp32_matmul_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_grad_not_set_to_none_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_matmul_dim_fp16_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_name_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_optimizer_single_tensor_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_overload_names, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_pattern_match_helper, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_pattern_matcher_json_report, test/profiler/test_profiler.py::TestExperimentalUtils::test_profiler_synchronized_dataloader_pattern, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_idle_time, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_queue_depth, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_queue_depth_when_no_cuda_events, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_compute_self_time, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_get_optimizable_events, test/profiler/test_profiler.py::TestExperimentalUtils::test_utils_intervals_overlap
2025-08-14T22:39:54.5315497Z 
2025-08-14T22:39:59.1335646Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:39:59.1338672Z   import pkg_resources
2025-08-14T22:39:59.3293331Z Running functorch/test_vmap_registrations 1/1 ... [2025-08-14 22:39:59.328788]
2025-08-14T22:39:59.3294317Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:39:59.3299825Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:39:59.329235]
2025-08-14T22:40:08.8212843Z 
2025-08-14T22:40:08.8214230Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_30499c34a6755df6_.log
2025-08-14T22:40:08.9951285Z Running 1719 items in this shard: test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::cat], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::get_first], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::leaky_relu], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__and__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__and__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__iand__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__iand__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ior__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ior__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ixor__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__ixor__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__or__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__or__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__xor__.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__xor__.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_add_batch_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_autocast_to_full_precision], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::_autocast_to_reduced_precision], 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test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_gammaincc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_gammaln], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_i0], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_log1p], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_log_softmax], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_logit], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_logsumexp], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_multigammaln], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_ndtr], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_polygamma], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_psi], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_round], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_sinc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_softmax], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy.other_scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy.self_scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::split.sizes], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::square], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::square_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sspaddmm], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stft.center], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stft], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stride.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract_.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract_.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sum_to_size], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::svd.U], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::svd], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapaxes], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapaxes_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapdims], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapdims_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_numel], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_size.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_storage_offset], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_stride.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::take_along_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.indices], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.sections], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.tensor_indices_or_sections], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensordot], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::thnn_conv2d], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tile], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.device], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.dtype], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.dtype_layout], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.other], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_dense], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_dense_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_mkldnn_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trace_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapezoid.dx], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapezoid.x], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapz.dx], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapz.x], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::triplet_margin_loss], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide_.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide_.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::type_as], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten_dense_tensors], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unsafe_chunk], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bicubic2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bilinear2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_linear1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_trilinear3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::value_selecting_reduction_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vander], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::view_as], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.array], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vstack], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarOther], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarSelf], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where]
2025-08-14T22:40:09.1058715Z 
2025-08-14T22:40:12.7917340Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:40:12.7920411Z   import pkg_resources
2025-08-14T22:40:12.9193798Z Running nn/test_pruning 1/1 ... [2025-08-14 22:40:12.918945]
2025-08-14T22:40:12.9194599Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:40:12.9197148Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_pruning.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:40:12.919369]
2025-08-14T22:40:16.9411287Z 
2025-08-14T22:40:16.9412524Z nn/test_pruning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pruning_1.1_14ed2bac31bcb80f_.log
2025-08-14T22:40:16.9424416Z Running 34 items in this shard: test/nn/test_pruning.py::TestPruningNN::test_compute_nparams_to_prune, test/nn/test_pruning.py::TestPruningNN::test_custom_from_mask_pruning, test/nn/test_pruning.py::TestPruningNN::test_global_pruning, test/nn/test_pruning.py::TestPruningNN::test_global_pruning_importance_scores, test/nn/test_pruning.py::TestPruningNN::test_identity_pruning, test/nn/test_pruning.py::TestPruningNN::test_l1_unstructured_pruning, test/nn/test_pruning.py::TestPruningNN::test_l1_unstructured_pruning_with_importance_scores, test/nn/test_pruning.py::TestPruningNN::test_ln_structured_pruning, test/nn/test_pruning.py::TestPruningNN::test_ln_structured_pruning_importance_scores, test/nn/test_pruning.py::TestPruningNN::test_multiple_pruning_calls, test/nn/test_pruning.py::TestPruningNN::test_prune, test/nn/test_pruning.py::TestPruningNN::test_prune_importance_scores, test/nn/test_pruning.py::TestPruningNN::test_prune_importance_scores_mimic_default, test/nn/test_pruning.py::TestPruningNN::test_pruning_container, test/nn/test_pruning.py::TestPruningNN::test_pruning_container_compute_mask, test/nn/test_pruning.py::TestPruningNN::test_pruning_id_consistency, test/nn/test_pruning.py::TestPruningNN::test_pruning_rollback, test/nn/test_pruning.py::TestPruningNN::test_pruning_serialization_model, test/nn/test_pruning.py::TestPruningNN::test_pruning_serialization_state_dict, test/nn/test_pruning.py::TestPruningNN::test_random_pruning, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_0perc, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_forward, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_new_weight, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_orig, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_pickle, test/nn/test_pruning.py::TestPruningNN::test_random_pruning_sizes, test/nn/test_pruning.py::TestPruningNN::test_random_structured_pruning_amount, test/nn/test_pruning.py::TestPruningNN::test_remove_pruning, test/nn/test_pruning.py::TestPruningNN::test_remove_pruning_exception, test/nn/test_pruning.py::TestPruningNN::test_remove_pruning_forward, test/nn/test_pruning.py::TestPruningNN::test_rnn_pruning, test/nn/test_pruning.py::TestPruningNN::test_unstructured_pruning_same_magnitude, test/nn/test_pruning.py::TestPruningNN::test_validate_pruning_amount, test/nn/test_pruning.py::TestPruningNN::test_validate_pruning_amount_init
2025-08-14T22:40:16.9435619Z 
2025-08-14T22:40:20.0895970Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:40:20.0898844Z   import pkg_resources
2025-08-14T22:40:20.2177657Z Running test_itt 1/1 ... [2025-08-14 22:40:20.217319]
2025-08-14T22:40:20.2178278Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:40:20.2180238Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_itt.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:40:20.217708]
2025-08-14T22:40:23.7374099Z 
2025-08-14T22:40:23.7374985Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_25fec2fb68394df4_.log
2025-08-14T22:40:23.7375839Z Running 1 items in this shard: test/test_itt.py::TestItt::test_itt
2025-08-14T22:40:23.7376155Z 
2025-08-14T22:40:27.5727744Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:40:27.5730672Z   import pkg_resources
2025-08-14T22:40:27.7014556Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-08-14 22:40:27.700507]
2025-08-14T22:40:27.7015110Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:40:27.7016571Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:40:27.700956]
2025-08-14T22:40:36.9362079Z 
2025-08-14T22:40:36.9364144Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_9b68f54e42ee7b2d_.log
2025-08-14T22:40:36.9464113Z Running 273 items in this shard: test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_copies, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_negative_resize, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_repeats, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_reshape_from_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_zeroresize, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_choose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_clip, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_compress, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_count_nonzero, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_cumproduct, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_diagonal, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_accuracy, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype3, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype4, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype5, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype6, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype7, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-10, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-9, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_mean, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_prod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ptp, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ravel, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_repeat, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_reshape, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_py_consistency, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_searchsorted, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_size, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_squeeze, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_std, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_sum, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_swapaxes, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_take, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_trace, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_transpose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_var, test/torch_np/numpy_tests/core/test_numeric.py::TestIsscalar::test_isscalar, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_logical, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_all_any, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_and_or_xor, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_not_abs, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_double, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_float, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_default, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_divide_err, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_errobj, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_set, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_warnings, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_values, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_promote_types_endian, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_result_type, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_tesult_type_2, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_5, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_9, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_empty_result, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_failed_itemsetting, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_lengths, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_too_few_items, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_types, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_values, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_?, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_B, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_b, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_h, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_i, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_l, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_list, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_axis_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_keepdims, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_twodim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean_edgecase, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_large_neg_int64, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_neg_width_boundaries, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_sufficient_width, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base3, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base_range, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal_equal_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equiv, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_none_compares_elementwise, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_array_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_func_takes_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_array, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_non_contig, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_property, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_scalar_nan_propagation_arr0_amin0_amax0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin2_amax2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax1, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax_0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_outint32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_memory_overlap, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_transposed, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_noncontig_inplace, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_D, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_F, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_e, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_?, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_B, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_b, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_d, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_f, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_h, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_i, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_l, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting_unsafe, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_inout, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_nonnative, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_03, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_04, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_05, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_06, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_07, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_08, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_09, 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test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_none_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_no_parameter_modification, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_non_finite_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_scalar_return, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof1, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof2, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_out_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_for_reference_leak, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_full, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_ones, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_zeros, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype1, 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test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_no_overwrite, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_numpy_doc_examples, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_object, test/torch_np/numpy_tests/core/test_numeric.py::TestDtypePositional::test_dtype_positional, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_2D, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_list, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_0, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_1, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_2, test/torch_np/numpy_tests/core/test_numeric.py::TestStringFunction::test_set_string_function, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll1d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll2d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_exceptions, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_results, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_errors, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_multiples, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_new_position, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_to_end, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_preserve_order, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x2, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_3x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting_shapes, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_uint8_int32_mixed_dtypes, test/torch_np/numpy_tests/core/test_numeric.py::TestOuterMisc::test_outer_out_param, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_scalar_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_single_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_C_and_F_simul, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_non_array_input, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_require_each, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_unknown_requirement, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_error_kwargs, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_in_args, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_single_arg, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_number_of_arguments, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_shape_mismatch_error_message, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension_einsum, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimensional
2025-08-14T22:40:36.9561966Z 
2025-08-14T22:40:40.4404084Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:40:40.4406920Z   import pkg_resources
2025-08-14T22:40:40.5698133Z Running test_sympy_utils 1/1 ... [2025-08-14 22:40:40.569403]
2025-08-14T22:40:40.5698583Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:40:40.5701200Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:40:40.569807]
2025-08-14T22:41:04.4887313Z 
2025-08-14T22:41:04.4888697Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_85f3e8cb4bbd27a6_.log
2025-08-14T22:41:04.4953722Z Running 209 items in this shard: test/test_sympy_utils.py::TestNumbers::test_float_cast, test/test_sympy_utils.py::TestNumbers::test_int_infinity, test/test_sympy_utils.py::TestNumbers::test_lt_self, test/test_sympy_utils.py::TestNumbers::test_mixed_oo_int_oo, test/test_sympy_utils.py::TestNumbers::test_relation, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_and_, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_or_, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_add_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_add_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_and_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_and_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_or_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_or_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_floordiv_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_floordiv_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_maximum_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_maximum_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_minimum_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_minimum_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mod_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mod_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mul_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mul_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_by_natural_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_by_natural_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_sub_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_sub_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_truediv_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_truediv_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_add, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_eq, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_floordiv, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_ge, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_gt, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_le, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_lt, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_maximum, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_minimum, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_mod, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_mul, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_ne, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_pow, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_pow_by_natural, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_sub, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_truediv, test/test_sympy_utils.py::TestValueRanges::test_bitwise_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_bitwise_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_mul_zero_unknown, test/test_sympy_utils.py::TestValueRanges::test_pow_half, test/test_sympy_utils.py::TestValueRanges::test_unary_bool_ref_range_fn_not_, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_abs_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_abs_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_ceil_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_ceil_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_exp_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_exp_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_floor_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_floor_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_log_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_log_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_neg_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_neg_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_reciprocal_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_reciprocal_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_sqrt_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_sqrt_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_square_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_square_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_abs, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_ceil, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_exp, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_floor, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_log, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_neg, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_reciprocal, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_sqrt, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_truediv, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_truediv, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_truediv, test/test_sympy_utils.py::TestSympySolve::test_addition, test/test_sympy_utils.py::TestSympySolve::test_floordiv_Equality, test/test_sympy_utils.py::TestSympySolve::test_floordiv_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_LessThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_Unequality, test/test_sympy_utils.py::TestSympySolve::test_floordiv_eq_simplify, test/test_sympy_utils.py::TestSympySolve::test_give_up, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_Equality, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_Unequality, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_LessThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_Equality, test/test_sympy_utils.py::TestSympySolve::test_noop_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_LessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_Unequality, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_Equality, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_LessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_Unequality, test/test_sympy_utils.py::TestSympySolve::test_simple_floordiv_gcd, test/test_sympy_utils.py::TestSympySolve::test_z3_proof_floordiv_eq_simplify, test/test_sympy_utils.py::TestSympyFunctions::test_pickle, test/test_sympy_utils.py::TestSingletonInt::test_basic, test/test_sympy_utils.py::TestIdentity::test_cast_identity_float, test/test_sympy_utils.py::TestIdentity::test_cast_identity_illegal, test/test_sympy_utils.py::TestIdentity::test_cast_identity_int, test/test_sympy_utils.py::TestIdentity::test_expand_identity, test/test_sympy_utils.py::TestTypedExpr::test_typed_expr
2025-08-14T22:41:04.5014498Z 
2025-08-14T22:41:07.6905589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:41:07.6908823Z   import pkg_resources
2025-08-14T22:41:07.8151412Z Running torch_np/test_indexing 1/1 ... [2025-08-14 22:41:07.814777]
2025-08-14T22:41:07.8152294Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:41:07.8155259Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:41:07.815191]
2025-08-14T22:41:15.3938871Z 
2025-08-14T22:41:15.3940750Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_b6408b4ab7d567f6_.log
2025-08-14T22:41:15.3946271Z Running 5 items in this shard: test/torch_np/test_indexing.py::TestAdvancedIndexing::test_advanced_separation_patterns, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_broadcast_and_numpy_compatibility, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_comprehensive_indexing, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_ellipsis, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_special_index_types
2025-08-14T22:41:15.4041057Z 
2025-08-14T22:41:18.7504610Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:41:18.7508123Z   import pkg_resources
2025-08-14T22:41:18.8768250Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-08-14 22:41:18.876270]
2025-08-14T22:41:18.8769245Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:41:18.8776364Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:41:18.876685]
2025-08-14T22:41:25.3171366Z 
2025-08-14T22:41:25.3173216Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_84b48ee6fd14afaa_.log
2025-08-14T22:41:25.3399660Z Running 505 items in this shard: test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_rotation_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_4d, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_lr, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_ud, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_default_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_multiple_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_order, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_average_class_without_dtype, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic_keepdims_x0_axis0_expected_avg0_weights0_expected_wavg0_expected_wsum0, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic_keepdims_x1_axis_0_expected_avg1_weights1_expected_wavg1_expected_wsum1, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_returned, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_upcasting, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_weights, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_broadcasting, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_deprecated_empty, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_many_arguments, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_non_bool_deprecation, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_return_dtype, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_0d, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_array_copied, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_floats, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_out_of_bounds_idx_-4, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_out_of_bounds_idx_4, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_multidim, test/torch_np/numpy_tests/lib/test_function_base.py::TestAmax::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAmin::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestPtp::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCumsum::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestProd::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCumprod::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_append, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_n, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_prepend, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_0d, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_array_order_preserve, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_fancy, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_index_floats, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_[1], test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_array([1]), test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_non_int, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_slices, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_args, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_badargs, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_decreasing_unsigned_int_f_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype1, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype2, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype3, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_inexact_dtypes, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_second_order_accurate, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_spacing, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_specific_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_values, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_x_decreasing_unsigned_x_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_x_signed_int_big_jump_x_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_x_signed_int_big_jump_x_dtype1, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_x_signed_int_big_jump_x_dtype2, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_x_signed_int_big_jump_x_dtype3, test/torch_np/numpy_tests/lib/test_function_base.py::TestAngle::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_all_zero, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_leading_skip, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_list_to_list, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_no_trim, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_overflow_arr0, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_size_zero, test/torch_np/numpy_tests/lib/test_function_base.py::TestTrimZeros::test_trailing_skip, test/torch_np/numpy_tests/lib/test_function_base.py::TestExtins::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestExtins::test_both, test/torch_np/numpy_tests/lib/test_function_base.py::TestExtins::test_place, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_casting_error, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_forward, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_large_integers_decreasing, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_large_integers_increasing, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_monotonic, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_random, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_reverse, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_right_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_right_open, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_right_open_random, test/torch_np/numpy_tests/lib/test_function_base.py::TestDigitize::test_right_open_reverse, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_B_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_B_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_B_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_b_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_b_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_b_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_d_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_d_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_d_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_e_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_e_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_e_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_f_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_f_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_f_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_h_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_h_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_h_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_i_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_i_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_i_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_l_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_l_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_bartlett_dtype_l_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_B_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_B_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_B_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_b_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_b_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_b_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_d_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_d_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_d_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_e_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_e_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_e_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_f_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_f_M_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_f_M_10, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_h_M_0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFilterwindows::test_blackman_dtype_h_M_1, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_q, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_no_p_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_out_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_empty_dim, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_list, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_no_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_scalar_q, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_scalar_q_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_sequence, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_complex, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_correct_quantile_value, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_fraction, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_max_ulp, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_no_p_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_hypo, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_averaged_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_closest_observation, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_hazen, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_higher, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_interpolated_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_linear, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_lower, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_median_unbiased, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_midpoint, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_nearest, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_normal_unbiased, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_weibull, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_scalar_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_array_like, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_axis_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_empty, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis_invalid, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis4, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_overwrite_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_complex, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_B_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_H_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_b_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_g_type_out_G, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_h_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_l_type_out_D
2025-08-14T22:41:25.3611650Z 
2025-08-14T22:41:28.5652497Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:41:28.5655534Z   import pkg_resources
2025-08-14T22:41:28.6885519Z Running test_jit 1/1 ... [2025-08-14 22:41:28.688145]
2025-08-14T22:41:28.6886500Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:41:28.6889816Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:41:28.688607]
2025-08-14T22:41:43.3873703Z 
2025-08-14T22:41:43.3875041Z test_jit_fuser_te 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_fuser_te_1.1_c2d145fd9a8cd712_.log
2025-08-14T22:41:43.8079271Z Running 6842 items in this shard: test/test_jit_fuser_te.py::TestFuserCommon::test_autodiff_fallback, test/test_jit_fuser_te.py::TestTEFuserStatic::test_abs, test/test_jit_fuser_te.py::TestTEFuserStatic::test_adaptive_avg_pool2d, test/test_jit_fuser_te.py::TestTEFuserStatic::test_add_bool, test/test_jit_fuser_te.py::TestTEFuserStatic::test_addcmul, test/test_jit_fuser_te.py::TestTEFuserStatic::test_arg_configurations_smoke, test/test_jit_fuser_te.py::TestTEFuserStatic::test_autocast_down, test/test_jit_fuser_te.py::TestTEFuserStatic::test_autocast_up, test/test_jit_fuser_te.py::TestTEFuserStatic::test_batch_norm, test/test_jit_fuser_te.py::TestTEFuserStatic::test_binary_div_ops, test/test_jit_fuser_te.py::TestTEFuserStatic::test_binary_ops, test/test_jit_fuser_te.py::TestTEFuserStatic::test_binary_pow, test/test_jit_fuser_te.py::TestTEFuserStatic::test_binary_scalar_ops, test/test_jit_fuser_te.py::TestTEFuserStatic::test_binary_tensor_scalar_ops, 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test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_short_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sigmoid_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sign_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sin_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sinh_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sqrt_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sub_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_sum_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_t_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_tan_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_tanh_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_transpose_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_true_divide_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_trunc_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_unsqueeze_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_view_as_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_view_cpu_float32, test/test_jit_fuser_te.py::TestNNCOpInfoCPU::test_working_where_cpu_float32, test/test_jit_fuser_te.py::TestLoopnestRandomizationCPU::test_relu_cpu
2025-08-14T22:41:44.2279159Z 
2025-08-14T22:41:48.3560839Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:41:48.3562968Z   import pkg_resources
2025-08-14T22:41:48.5686640Z Running nn/test_packed_sequence 1/1 ... [2025-08-14 22:41:48.568212]
2025-08-14T22:41:48.5687128Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:41:48.5691274Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:41:48.568771]
2025-08-14T22:41:52.7412199Z 
2025-08-14T22:41:52.7414096Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_c7e8833d8780df7b_.log
2025-08-14T22:41:52.7423578Z Running 12 items in this shard: test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_padded_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_non_iterable_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_tensor_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to_memory_format, test/nn/test_packed_sequence.py::PackedSequenceTest::test_total_length, test/nn/test_packed_sequence.py::PackedSequenceTest::test_type_casts, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_wrong_order
2025-08-14T22:41:52.7431811Z 
2025-08-14T22:41:56.8093694Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:41:56.8096752Z   import pkg_resources
2025-08-14T22:41:57.0384693Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-08-14 22:41:57.037912]
2025-08-14T22:41:57.0386047Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:41:57.0391662Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:41:57.038510]
2025-08-14T22:42:05.9686513Z 
2025-08-14T22:42:05.9688914Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_9f8f2ee4f038b3dd_.log
2025-08-14T22:42:05.9714621Z Running 19 items in this shard: test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_default_constructor_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_device_guard_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_device_guard_set_index_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_divide_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_exp_neg_is_leaf_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_fill_infinity_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_get_current_device_index_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_identity_does_not_hog_memory_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_is_contiguous_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_abs_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_empty_like_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_narrow_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_ones_like_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_pad_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_transpose_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_zero__cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_slow_sgd_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_stream_cpu
2025-08-14T22:42:05.9737674Z 
2025-08-14T22:42:11.1692509Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:42:11.1695667Z   import pkg_resources
2025-08-14T22:42:11.3709452Z Running functorch/test_ops 1/8 ... [2025-08-14 22:42:11.370414]
2025-08-14T22:42:11.3711049Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:42:11.3716150Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:42:11.370897]
2025-08-14T22:43:23.6713502Z 
2025-08-14T22:43:23.6714699Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_00384182037fd293_.log
2025-08-14T22:43:23.8197998Z Running 2461 items in this shard: test/test_jit.py::TestTracer::test_call_traced_fn_from_traced_module, test/test_jit.py::TestTracer::test_call_traced_module_from_traced_module, test/test_jit.py::TestTracer::test_canonicalize_tensor_iterator, test/test_jit.py::TestTracer::test_constant, test/test_jit.py::TestTracer::test_conv, test/test_jit.py::TestTracer::test_export_no_reorder, test/test_jit.py::TestTracer::test_force_outplace_check_fill, test/test_jit.py::TestTracer::test_force_outplace_check_zero, test/test_jit.py::TestTracer::test_ge, test/test_jit.py::TestTracer::test_ge_cuda, test/test_jit.py::TestTracer::test_ge_optimized, test/test_jit.py::TestTracer::test_ge_unoptimized, test/test_jit.py::TestTracer::test_index_put, test/test_jit.py::TestTracer::test_index_put_trace_with_view, test/test_jit.py::TestTracer::test_index_put_trace_without_view, test/test_jit.py::TestTracer::test_inplace_check, test/test_jit.py::TestTracer::test_inplace_copy, test/test_jit.py::TestTracer::test_inplace_copy_force_outplace, test/test_jit.py::TestTracer::test_inplace_flags, test/test_jit.py::TestTracer::test_inplace_transplant, test/test_jit.py::TestTracer::test_inplace_warn, test/test_jit.py::TestTracer::test_input_dict_checkTrace_mut, test/test_jit.py::TestTracer::test_input_dict_empty, test/test_jit.py::TestTracer::test_input_dict_empty_list, test/test_jit.py::TestTracer::test_input_dict_insertion_order, test/test_jit.py::TestTracer::test_input_dict_of_dicts, test/test_jit.py::TestTracer::test_input_dict_of_lists, test/test_jit.py::TestTracer::test_input_dict_recursive, test/test_jit.py::TestTracer::test_input_dict_remembers_keys, test/test_jit.py::TestTracer::test_input_dict_unify, test/test_jit.py::TestTracer::test_input_flatten, test/test_jit.py::TestTracer::test_input_list_mixed_type, test/test_jit.py::TestTracer::test_input_list_of_tuples, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten_direct, test/test_jit.py::TestTracer::test_input_tuple_of_dicts, test/test_jit.py::TestTracer::test_interpolate_trace, test/test_jit.py::TestTracer::test_large_nbr_kernel_args, test/test_jit.py::TestTracer::test_lhs_index_fails, test/test_jit.py::TestTracer::test_lhs_index_trivial, test/test_jit.py::TestTracer::test_max_pool, test/test_jit.py::TestTracer::test_nested_inplace, test/test_jit.py::TestTracer::test_non_tensor_tracing, test/test_jit.py::TestTracer::test_output_unflatten, test/test_jit.py::TestTracer::test_python_function, test/test_jit.py::TestTracer::test_python_function_tup, test/test_jit.py::TestTracer::test_repeated_input, test/test_jit.py::TestTracer::test_repeated_output, test/test_jit.py::TestTracer::test_shared_param, test/test_jit.py::TestTracer::test_simple, test/test_jit.py::TestTracer::test_tensor_with_grad_as_constant, test/test_jit.py::TestTracer::test_trace_aliased_parameter, test/test_jit.py::TestTracer::test_trace_annotation, test/test_jit.py::TestTracer::test_trace_arange, test/test_jit.py::TestTracer::test_trace_arange_with_grad, test/test_jit.py::TestTracer::test_trace_autograd_function, test/test_jit.py::TestTracer::test_trace_casts, test/test_jit.py::TestTracer::test_trace_checker_control_flow, test/test_jit.py::TestTracer::test_trace_checker_dot_data, test/test_jit.py::TestTracer::test_trace_checker_dropout_notrain, test/test_jit.py::TestTracer::test_trace_checker_dropout_train, test/test_jit.py::TestTracer::test_trace_checker_inplace_on_view, test/test_jit.py::TestTracer::test_trace_checker_memoization, test/test_jit.py::TestTracer::test_trace_checker_slice_lhs, test/test_jit.py::TestTracer::test_trace_checking_with_deprecated_name, test/test_jit.py::TestTracer::test_trace_checking_with_global_name, test/test_jit.py::TestTracer::test_trace_contiguous, test/test_jit.py::TestTracer::test_trace_contiguous_short_circuit, test/test_jit.py::TestTracer::test_trace_detach, test/test_jit.py::TestTracer::test_trace_detach_inplace, test/test_jit.py::TestTracer::test_trace_detach_inplace_redispatch, test/test_jit.py::TestTracer::test_trace_detach_redispatch, test/test_jit.py::TestTracer::test_trace_dict_input, test/test_jit.py::TestTracer::test_trace_dict_output, test/test_jit.py::TestTracer::test_trace_export_fns, test/test_jit.py::TestTracer::test_trace_export_fns_recursive, test/test_jit.py::TestTracer::test_trace_fork_join_and_module, test/test_jit.py::TestTracer::test_trace_full_dynamic_shape, test/test_jit.py::TestTracer::test_trace_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_index, test/test_jit.py::TestTracer::test_trace_index_constant, test/test_jit.py::TestTracer::test_trace_indexed_assignment, test/test_jit.py::TestTracer::test_trace_inline_shape, test/test_jit.py::TestTracer::test_trace_inverse, test/test_jit.py::TestTracer::test_trace_invert_module_hierarchy, test/test_jit.py::TestTracer::test_trace_legacy_ctor, test/test_jit.py::TestTracer::test_trace_module_argument_names_captured, test/test_jit.py::TestTracer::test_trace_modulelist, test/test_jit.py::TestTracer::test_trace_multi_output_function, test/test_jit.py::TestTracer::test_trace_namedtuple, test/test_jit.py::TestTracer::test_trace_nested_datatypes, test/test_jit.py::TestTracer::test_trace_nested_fn, test/test_jit.py::TestTracer::test_trace_no_duplicated_lifted_input_output, test/test_jit.py::TestTracer::test_trace_numel, test/test_jit.py::TestTracer::test_trace_optioanl_dtype, test/test_jit.py::TestTracer::test_trace_optional, test/test_jit.py::TestTracer::test_trace_out_operator_with_two_output, test/test_jit.py::TestTracer::test_trace_partial_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_random, test/test_jit.py::TestTracer::test_trace_records_names, test/test_jit.py::TestTracer::test_trace_save, test/test_jit.py::TestTracer::test_trace_save_load_copy, test/test_jit.py::TestTracer::test_trace_single_tuple, test/test_jit.py::TestTracer::test_trace_size, test/test_jit.py::TestTracer::test_trace_size_with_grad, test/test_jit.py::TestTracer::test_trace_skip_none_submodule, test/test_jit.py::TestTracer::test_trace_slice, test/test_jit.py::TestTracer::test_trace_slice_expr_complete_type, test/test_jit.py::TestTracer::test_trace_slice_full_dim, test/test_jit.py::TestTracer::test_trace_slice_setitem_dynamic_shape, test/test_jit.py::TestTracer::test_trace_slice_with_grad, test/test_jit.py::TestTracer::test_trace_tensor_factory, test/test_jit.py::TestTracer::test_trace_topk, test/test_jit.py::TestTracer::test_trace_tuple, test/test_jit.py::TestTracer::test_trace_variable_instantiation, test/test_jit.py::TestTracer::test_trace_warn, test/test_jit.py::TestTracer::test_trace_with_conditional_property, test/test_jit.py::TestTracer::test_trace_with_nested_strided_tensor_output, test/test_jit.py::TestTracer::test_trace_with_nested_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_number_list_output, test/test_jit.py::TestTracer::test_trace_with_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_tuple_tensor, test/test_jit.py::TestTracer::test_traced_module_cuda, test/test_jit.py::TestTracer::test_tracing_backward_hook_error, test/test_jit.py::TestTracer::test_tracing_hooks, test/test_jit.py::TestTracer::test_tracing_multiple_methods, test/test_jit.py::TestTracer::test_type_same_device, test/test_jit.py::TestTracer::test_typeas_trace_check, test/test_jit.py::TestTracer::test_wrapped_number, test/test_jit.py::TestMixTracingScripting::test_call_script_fn_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_script_module_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_traced_fn_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_traced_mod_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_tracing_fn_from_script_module, test/test_jit.py::TestMixTracingScripting::test_call_tracing_mod_from_script_module, test/test_jit.py::TestMixTracingScripting::test_jit_trace_callfunction_return_shapes, test/test_jit.py::TestMixTracingScripting::test_script_inline_trace_multiple_args, test/test_jit.py::TestMixTracingScripting::test_trace_dict_mix_script, test/test_jit.py::TestMixTracingScripting::test_trace_hierarchy, test/test_jit.py::TestMixTracingScripting::test_trace_linear, test/test_jit.py::TestMixTracingScripting::test_trace_mixed_by_script_with_dict_output, test/test_jit.py::TestMixTracingScripting::test_trace_of_script, test/test_jit.py::TestMixTracingScripting::test_trace_parameter, test/test_jit.py::TestMixTracingScripting::test_trace_returning_dict_with_tensor_tuples, test/test_jit.py::TestMixTracingScripting::test_trace_script, test/test_jit.py::TestMixTracingScripting::test_trace_script_returning_complex_dict, test/test_jit.py::TestMixTracingScripting::test_trace_with_size, test/test_jit.py::TestMixTracingScripting::test_traced_module_contains_scripted_interface_types, test/test_jit.py::TestMixTracingScripting::test_traced_module_implements_interface, test/test_jit.py::TestMixTracingScripting::test_tracing_indexing, test/test_jit.py::TestMixTracingScripting::test_tracing_slicing, test/test_jit.py::TestRecursiveScript::test_attributes, test/test_jit.py::TestRecursiveScript::test_class_compile, test/test_jit.py::TestRecursiveScript::test_constants_with_final, test/test_jit.py::TestRecursiveScript::test_dir, test/test_jit.py::TestRecursiveScript::test_error_stack, test/test_jit.py::TestRecursiveScript::test_error_stack_annotation, test/test_jit.py::TestRecursiveScript::test_error_stack_class, test/test_jit.py::TestRecursiveScript::test_error_stack_module, test/test_jit.py::TestRecursiveScript::test_failed_function_compilation, test/test_jit.py::TestRecursiveScript::test_function_attribute_in_submodule, test/test_jit.py::TestRecursiveScript::test_ignore_class, test/test_jit.py::TestRecursiveScript::test_inferred_nonetype, test/test_jit.py::TestRecursiveScript::test_init_error, test/test_jit.py::TestRecursiveScript::test_inner_traced_module, test/test_jit.py::TestRecursiveScript::test_iterable_modules, test/test_jit.py::TestRecursiveScript::test_method_call, test/test_jit.py::TestRecursiveScript::test_module_basic, test/test_jit.py::TestRecursiveScript::test_module_function_export, test/test_jit.py::TestRecursiveScript::test_module_name, test/test_jit.py::TestRecursiveScript::test_module_repr, test/test_jit.py::TestRecursiveScript::test_optional_module, test/test_jit.py::TestRecursiveScript::test_override_instance_method_ignore, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_basic, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_cycle, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_escape_hatch, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_iterable_modules, test/test_jit.py::TestRecursiveScript::test_python_function_attribute, test/test_jit.py::TestRecursiveScript::test_repeated_error_stack, test/test_jit.py::TestRecursiveScript::test_script_after_eval, test/test_jit.py::TestRecursiveScript::test_script_basic, test/test_jit.py::TestRecursiveScript::test_script_function_attribute, test/test_jit.py::TestRecursiveScript::test_script_loaded_module, test/test_jit.py::TestRecursiveScript::test_thread_safe_error_stacks, test/test_jit.py::TestTypeSharing::test_assign_python_attr, test/test_jit.py::TestTypeSharing::test_basic, test/test_jit.py::TestTypeSharing::test_builtin_function_different, test/test_jit.py::TestTypeSharing::test_builtin_function_same, test/test_jit.py::TestTypeSharing::test_constants, test/test_jit.py::TestTypeSharing::test_diff_attr_values, test/test_jit.py::TestTypeSharing::test_failed_attribute_compilation, test/test_jit.py::TestTypeSharing::test_ignored_fns, test/test_jit.py::TestTypeSharing::test_linear, test/test_jit.py::TestTypeSharing::test_loaded_modules_work, test/test_jit.py::TestTypeSharing::test_module_dict_same_type_different_name, test/test_jit.py::TestTypeSharing::test_mutate_attr_value, test/test_jit.py::TestTypeSharing::test_param_vs_attribute, test/test_jit.py::TestTypeSharing::test_python_function_attribute_different, test/test_jit.py::TestTypeSharing::test_python_function_attribute_same, test/test_jit.py::TestTypeSharing::test_same_but_different_classes, test/test_jit.py::TestTypeSharing::test_script_function_attribute_different, test/test_jit.py::TestTypeSharing::test_script_function_attribute_same, test/test_jit.py::TestTypeSharing::test_script_module_containing_traced_module, test/test_jit.py::TestTypeSharing::test_submodules, test/test_jit.py::TestTypeSharing::test_tracing_gives_different_types, test/test_jit.py::TestTypeSharing::test_type_not_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_sharing_define_in_init, test/test_jit.py::TestTypeSharing::test_type_sharing_disabled, test/test_jit.py::TestLogging::test_bump_numeric_counter, test/test_jit.py::TestLogging::test_counter_aggregation, test/test_jit.py::TestLogging::test_logging_levels_set, test/test_jit.py::TestLogging::test_time_measurement_counter, test/test_jit.py::TestLogging::test_time_measurement_counter_script, test/test_jit.py::TestLogging::test_trace_numeric_counter, test/test_jit.py::TestBackends::test_errors, test/test_jit.py::TestBackends::test_execution, test/test_jit.py::TestBackends::test_save_load, test/test_jit.py::TestBackendsWithCompiler::test_errors, test/test_jit.py::TestBackendsWithCompiler::test_execution, test/test_jit.py::TestNnapiBackend::test_adaptive_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_cat, test/test_jit.py::TestNnapiBackend::test_compile_spec_santiy, test/test_jit.py::TestNnapiBackend::test_conv2d, test/test_jit.py::TestNnapiBackend::test_conv2d_transpose, test/test_jit.py::TestNnapiBackend::test_dequantize, test/test_jit.py::TestNnapiBackend::test_detach, test/test_jit.py::TestNnapiBackend::test_flatten, test/test_jit.py::TestNnapiBackend::test_hardtanh, test/test_jit.py::TestNnapiBackend::test_linear, test/test_jit.py::TestNnapiBackend::test_log_softmax, test/test_jit.py::TestNnapiBackend::test_max_pool2d, test/test_jit.py::TestNnapiBackend::test_mean, test/test_jit.py::TestNnapiBackend::test_multi_output, test/test_jit.py::TestNnapiBackend::test_pointwise_binary, test/test_jit.py::TestNnapiBackend::test_pointwise_binary_const, test/test_jit.py::TestNnapiBackend::test_pointwise_unary, test/test_jit.py::TestNnapiBackend::test_prelu, test/test_jit.py::TestNnapiBackend::test_qadd, test/test_jit.py::TestNnapiBackend::test_qlinear, test/test_jit.py::TestNnapiBackend::test_quantize, test/test_jit.py::TestNnapiBackend::test_reshape, test/test_jit.py::TestNnapiBackend::test_seblock_mul, test/test_jit.py::TestNnapiBackend::test_slice, test/test_jit.py::TestNnapiBackend::test_softmax, test/test_jit.py::TestNnapiBackend::test_tensor_input, test/test_jit.py::TestNnapiBackend::test_to, test/test_jit.py::TestNnapiBackend::test_unsqueeze, test/test_jit.py::TestNnapiBackend::test_upsample_nearest2d, test/test_jit.py::TestList::test_comprehension_iterable, test/test_jit.py::TestList::test_comprehension_out_type_not_in_type, test/test_jit.py::TestList::test_comprehensions_basic, test/test_jit.py::TestList::test_comprehensions_basic_float, test/test_jit.py::TestList::test_comprehensions_two_comps, test/test_jit.py::TestList::test_copy_list_immutable, test/test_jit.py::TestList::test_copy_list_mutable, test/test_jit.py::TestList::test_del, test/test_jit.py::TestList::test_dict_keyword_is_correctly_typed, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_empty_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_empty_iterable, test/test_jit.py::TestList::test_dict_keyword_with_internal_aggregate_function, test/test_jit.py::TestList::test_dict_keyword_with_iterable, test/test_jit.py::TestList::test_dict_keyword_with_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_kwargs_using_container_values, test/test_jit.py::TestList::test_dict_keyword_with_mapping, test/test_jit.py::TestList::test_dict_keyword_with_mapping_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_mismatched_annotations, test/test_jit.py::TestList::test_dict_keyword_with_nested_call, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable_and_kwargs, test/test_jit.py::TestList::test_extend_list_immutable, test/test_jit.py::TestList::test_extend_list_mutable, test/test_jit.py::TestList::test_in_check, test/test_jit.py::TestList::test_list_bool_conversion, test/test_jit.py::TestList::test_list_count, test/test_jit.py::TestList::test_list_count_not_existing, test/test_jit.py::TestList::test_list_gather, test/test_jit.py::TestList::test_list_index, test/test_jit.py::TestList::test_list_index_not_existing, test/test_jit.py::TestList::test_list_keyword, test/test_jit.py::TestList::test_list_len, test/test_jit.py::TestList::test_list_literal, test/test_jit.py::TestList::test_list_none, test/test_jit.py::TestList::test_list_ops, test/test_jit.py::TestList::test_list_slice, test/test_jit.py::TestList::test_list_sort, test/test_jit.py::TestList::test_list_unification_hint, test/test_jit.py::TestList::test_list_variance, test/test_jit.py::TestList::test_min_bool_list, test/test_jit.py::TestList::test_min_max_list, test/test_jit.py::TestList::test_min_max_single_list, test/test_jit.py::TestList::test_mutable_list_append, test/test_jit.py::TestList::test_mutable_list_append_2, test/test_jit.py::TestList::test_mutable_list_append_if, test/test_jit.py::TestList::test_mutable_list_append_if_else, test/test_jit.py::TestList::test_mutable_list_append_loop, test/test_jit.py::TestList::test_mutable_list_append_loop_if, test/test_jit.py::TestList::test_mutable_list_clear, test/test_jit.py::TestList::test_mutable_list_clear_empty, test/test_jit.py::TestList::test_mutable_list_function_inline, test/test_jit.py::TestList::test_mutable_list_insert, test/test_jit.py::TestList::test_mutable_list_insert_neg_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_insert_negative, test/test_jit.py::TestList::test_mutable_list_insert_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_nested_loop, test/test_jit.py::TestList::test_mutable_list_pop, test/test_jit.py::TestList::test_mutable_list_pop2, test/test_jit.py::TestList::test_mutable_list_pop_at, test/test_jit.py::TestList::test_mutable_list_pop_at2, test/test_jit.py::TestList::test_mutable_list_pop_at_negative, test/test_jit.py::TestList::test_mutable_list_pop_at_negative2, test/test_jit.py::TestList::test_mutable_list_pop_empty, test/test_jit.py::TestList::test_mutable_list_pop_slice, test/test_jit.py::TestList::test_mutable_list_remove, test/test_jit.py::TestList::test_mutable_list_remove2, test/test_jit.py::TestList::test_mutable_list_remove_not_existing, test/test_jit.py::TestList::test_mutable_list_remove_tensor, test/test_jit.py::TestList::test_mutable_list_reverse, test/test_jit.py::TestList::test_mutable_list_reverse_empty, test/test_jit.py::TestList::test_mutable_tensor_list_reverse, test/test_jit.py::TestList::test_no_element_type_annotation, test/test_jit.py::TestList::test_slice_index, test/test_jit.py::TestList::test_tensor_list_count, test/test_jit.py::TestList::test_tensor_list_count_not_existing, test/test_jit.py::TestList::test_tensor_list_index, test/test_jit.py::TestList::test_tensor_list_index_not_existing, test/test_jit.py::TestList::test_to_list, test/test_jit.py::TestList::test_to_list_gpu, test/test_jit.py::TestDict::test_aug_assign, test/test_jit.py::TestDict::test_basic, test/test_jit.py::TestDict::test_clear, test/test_jit.py::TestDict::test_copy, test/test_jit.py::TestDict::test_del, test/test_jit.py::TestDict::test_dict_bool_conversion, test/test_jit.py::TestDict::test_dict_preserves_order, test/test_jit.py::TestDict::test_dict_to_python, test/test_jit.py::TestDict::test_dict_variance, test/test_jit.py::TestDict::test_get, test/test_jit.py::TestDict::test_get_boolkey, test/test_jit.py::TestDict::test_items, test/test_jit.py::TestDict::test_key_type, test/test_jit.py::TestDict::test_keys, test/test_jit.py::TestDict::test_len, test/test_jit.py::TestDict::test_loop, test/test_jit.py::TestDict::test_membership, test/test_jit.py::TestDict::test_mutability, test/test_jit.py::TestDict::test_optional_dict_construct, test/test_jit.py::TestDict::test_ordered_dict, test/test_jit.py::TestDict::test_pop, test/test_jit.py::TestDict::test_popitem, test/test_jit.py::TestDict::test_setdefault, test/test_jit.py::TestDict::test_type_annotation_missing_contained_type, test/test_jit.py::TestDict::test_update, test/test_jit.py::TestDict::test_update_existing_key, test/test_jit.py::TestDict::test_values, test/test_jit.py::TestDict::test_view, test/test_jit.py::TestNamedTuple::test_namedtuple, test/test_jit.py::TestNamedTuple::test_namedtuple_as_attr, test/test_jit.py::TestNamedTuple::test_namedtuple_constant, test/test_jit.py::TestNamedTuple::test_namedtuple_input_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_inside_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_kwarg_construct, test/test_jit.py::TestNamedTuple::test_namedtuple_lower, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_serialization, test/test_jit.py::TestNamedTuple::test_namedtuple_slice_unpack, test/test_jit.py::TestNamedTuple::test_namedtuple_type_annotation, test/test_jit.py::TestNamedTuple::test_namedtuple_wrong_types, test/test_jit.py::TestNamedTuple::test_return_named_tuple, test/test_jit.py::TestScriptDict::test_bool, test/test_jit.py::TestScriptDict::test_contains, test/test_jit.py::TestScriptDict::test_delitem, test/test_jit.py::TestScriptDict::test_getitem, test/test_jit.py::TestScriptDict::test_items, test/test_jit.py::TestScriptDict::test_iter, test/test_jit.py::TestScriptDict::test_len, test/test_jit.py::TestScriptDict::test_nested, test/test_jit.py::TestScriptDict::test_reference_semantics, test/test_jit.py::TestScriptDict::test_repr, test/test_jit.py::TestScriptDict::test_setitem, test/test_jit.py::TestScriptList::test_append, test/test_jit.py::TestScriptList::test_bool, test/test_jit.py::TestScriptList::test_clear, test/test_jit.py::TestScriptList::test_contains, test/test_jit.py::TestScriptList::test_count, test/test_jit.py::TestScriptList::test_defaultdict, test/test_jit.py::TestScriptList::test_delitem, test/test_jit.py::TestScriptList::test_extend, test/test_jit.py::TestScriptList::test_getitem, test/test_jit.py::TestScriptList::test_insert, test/test_jit.py::TestScriptList::test_iter, test/test_jit.py::TestScriptList::test_len, test/test_jit.py::TestScriptList::test_nested, test/test_jit.py::TestScriptList::test_pop, test/test_jit.py::TestScriptList::test_reference_semantics, test/test_jit.py::TestScriptList::test_remove, test/test_jit.py::TestScriptList::test_repr, test/test_jit.py::TestScriptList::test_setitem, test/test_jit.py::TestAsync::test_async_future_type_python, test/test_jit.py::TestAsync::test_async_grad_guard_no_grad, test/test_jit.py::TestAsync::test_async_grad_guard_with_grad, test/test_jit.py::TestAsync::test_async_kwargs, test/test_jit.py::TestAsync::test_async_parsing, test/test_jit.py::TestAsync::test_async_python, test/test_jit.py::TestAsync::test_async_script, test/test_jit.py::TestAsync::test_async_script_capture, test/test_jit.py::TestAsync::test_async_script_error, test/test_jit.py::TestAsync::test_async_script_multi_forks, test/test_jit.py::TestAsync::test_async_script_multi_waits, test/test_jit.py::TestAsync::test_async_script_nested, test/test_jit.py::TestAsync::test_async_script_no_script_mod, test/test_jit.py::TestAsync::test_async_script_trace, test/test_jit.py::TestAsync::test_future_subtyping, test/test_jit.py::TestAsync::test_no_future_subtype_message, test/test_jit.py::TestAsync::test_trace_fork_wait, test/test_jit.py::TestAsync::test_trace_fork_wait_inline, test/test_jit.py::TestAsync::test_trace_fork_wait_leaking, test/test_jit.py::TestAsync::test_trace_fork_wait_list_modulecalls, test/test_jit.py::TestAsync::test_trace_modulecalls_with_different_output_types, test/test_jit.py::TestAwait::test_await_class_arg, test/test_jit.py::TestAwait::test_await_class_return, test/test_jit.py::TestAwait::test_await_eager_lazy, test/test_jit.py::TestAwait::test_await_func_arg, test/test_jit.py::TestAwait::test_await_getattr_implicit_convertion, test/test_jit.py::TestAwait::test_await_isinstance, test/test_jit.py::TestAwait::test_await_multiout_save, test/test_jit.py::TestAwait::test_await_nested, test/test_jit.py::TestAwait::test_await_out_of_interpreter, test/test_jit.py::TestAwait::test_await_python, test/test_jit.py::TestAwait::test_await_type_python, test/test_jit.py::TestAwait::test_awaitable_to_await, test/test_jit.py::TestAwait::test_eager_await_non_scriptable, test/test_jit.py::TestAwait::test_jit_trace, test/test_jit.py::TestAwait::test_nowait, test/test_jit.py::TestAwait::test_nowait_class, test/test_jit.py::TestAwait::test_script, test/test_jit.py::TestDataParallel::test_python_submodule_script, test/test_jit.py::TestDataParallel::test_shared_module, test/test_jit.py::TestDataParallel::test_tensor_sharing, test/test_jit.py::TestDataParallel::test_tensor_sharing_with_forward, test/test_jit.py::TestDataParallel::test_traced_module, test/test_jit.py::TestModels::test_alexnet, test/test_jit.py::TestModels::test_dcgan_models, test/test_jit.py::TestModels::test_dcgan_models_cuda, test/test_jit.py::TestModels::test_mnist, test/test_jit.py::TestModels::test_mnist_cuda, test/test_jit.py::TestModels::test_mnist_training_leaks_no_memory_cuda, test/test_jit.py::TestModels::test_neural_style, test/test_jit.py::TestModels::test_neural_style_cuda, test/test_jit.py::TestModels::test_reinforcement_learning, test/test_jit.py::TestModels::test_reinforcement_learning_cuda, test/test_jit.py::TestModels::test_script_module_script_resnet, test/test_jit.py::TestModels::test_script_module_trace_resnet18, test/test_jit.py::TestModels::test_snli, test/test_jit.py::TestModels::test_snli_cuda, test/test_jit.py::TestModels::test_super_resolution, test/test_jit.py::TestModels::test_super_resolution_cuda, test/test_jit.py::TestModels::test_time_sequence_prediction, test/test_jit.py::TestModels::test_vae, test/test_jit.py::TestModels::test_vae_cuda, test/test_jit.py::TestModules::test_script_module_with_constants_list, test/test_jit.py::TestAutodiffJit::test_autodiff_requires_grad_nograd, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_profiled_twice, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_side_effects, test/test_jit.py::TestAutodiffJit::test_undefined_tensor_lists, test/test_jit.py::TestAutodiffSubgraphSlicing::test_aliased_outputs, test/test_jit.py::TestAutodiffSubgraphSlicing::test_bias_as_arg, test/test_jit.py::TestAutodiffSubgraphSlicing::test_bias_as_module_attr, test/test_jit.py::TestAutodiffSubgraphSlicing::test_chunk_constant_script_ad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_constructed_bias, test/test_jit.py::TestAutodiffSubgraphSlicing::test_diff_graph_inline_threshold, test/test_jit.py::TestAutodiffSubgraphSlicing::test_differentiable_graph_ops_requires_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_create_cycles, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_merge_unrelated, test/test_jit.py::TestAutodiffSubgraphSlicing::test_has_profiled_info_aliasing_outputs, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merge_respects_aliasing, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_dense, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_down, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_up, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_without_cycles, test/test_jit.py::TestAutodiffSubgraphSlicing::test_prune_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_requires_grad_for_tensor_list, test/test_jit.py::TestAutodiffSubgraphSlicing::test_respects_lexical_scoping, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_merge, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_no_merge, test/test_jit.py::TestCustomOperators::test_calling_scripted_custom_op, test/test_jit.py::TestCustomOperators::test_calling_traced_custom_op, test/test_jit.py::TestCustomOperators::test_default_arguments_are_used, test/test_jit.py::TestCustomOperators::test_dynamic_op_registry, test/test_jit.py::TestCustomOperators::test_generic_list, test/test_jit.py::TestCustomOperators::test_getting_invalid_attr, test/test_jit.py::TestCustomOperators::test_passing_and_returning_lists, test/test_jit.py::TestCustomOperators::test_passing_one_positional_but_not_the_second, test/test_jit.py::TestCustomOperators::test_passing_too_few_args, test/test_jit.py::TestCustomOperators::test_passing_too_many_args, test/test_jit.py::TestCustomOperators::test_passing_unknown_kwargs, test/test_jit.py::TestCustomOperators::test_script_graph_contains_custom_op, test/test_jit.py::TestCustomOperators::test_script_graph_for_custom_ops_matches_traced_graph, test/test_jit.py::TestCustomOperators::test_simply_calling_an_operator, test/test_jit.py::TestCustomOperators::test_where_no_scalar, test/test_jit.py::TestGraphRewritePasses::test_fuse_linear, test/test_jit.py::TestClassType::test_cast_overloads, test/test_jit.py::TestClassType::test_class_attribute_wrong_type, test/test_jit.py::TestClassType::test_class_constant, test/test_jit.py::TestClassType::test_class_constructs_itself, test/test_jit.py::TestClassType::test_class_inheritance, test/test_jit.py::TestClassType::test_class_inheritance_implicit, test/test_jit.py::TestClassType::test_class_sorting, test/test_jit.py::TestClassType::test_class_specialization, test/test_jit.py::TestClassType::test_class_type_as_param, test/test_jit.py::TestClassType::test_classmethod, test/test_jit.py::TestClassType::test_conditional_set_attr, test/test_jit.py::TestClassType::test_custom_delete, test/test_jit.py::TestClassType::test_default_args, test/test_jit.py::TestClassType::test_get_attr, test/test_jit.py::TestClassType::test_get_attr_not_initialized, test/test_jit.py::TestClassType::test_get_with_method, test/test_jit.py::TestClassType::test_imported_classes, test/test_jit.py::TestClassType::test_in, test/test_jit.py::TestClassType::test_init_compiled_first, test/test_jit.py::TestClassType::test_interface, test/test_jit.py::TestClassType::test_optional_type_promotion, test/test_jit.py::TestClassType::test_out_of_order_methods, test/test_jit.py::TestClassType::test_overloaded_fn, test/test_jit.py::TestClassType::test_properties, test/test_jit.py::TestClassType::test_py_class_to_ivalue_missing_attribute, test/test_jit.py::TestClassType::test_python_interop, test/test_jit.py::TestClassType::test_recursive_class, test/test_jit.py::TestClassType::test_recursive_script_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_script_module_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_scripting, test/test_jit.py::TestClassType::test_recursive_scripting_failed, test/test_jit.py::TestClassType::test_reference_semantics, test/test_jit.py::TestClassType::test_save_load_with_classes, test/test_jit.py::TestClassType::test_save_load_with_classes_nested, test/test_jit.py::TestClassType::test_save_load_with_classes_returned, test/test_jit.py::TestClassType::test_schema_human_readable, test/test_jit.py::TestClassType::test_self_referential_method, test/test_jit.py::TestClassType::test_set_attr_in_method, test/test_jit.py::TestClassType::test_set_attr_non_initialized, test/test_jit.py::TestClassType::test_set_attr_type_mismatch, test/test_jit.py::TestClassType::test_staticmethod, test/test_jit.py::TestClassType::test_type_annotation, test/test_jit.py::TestClassType::test_type_annotations, test/test_jit.py::TestClassType::test_unresolved_class_attributes, test/test_jit.py::TestClassType::test_unused_method, test/test_jit.py::TestBuiltins::test_del, test/test_jit.py::TestBuiltins::test_del_multiple_operands, test/test_jit.py::TestBuiltins::test_has_attr, test/test_jit.py::TestBuiltins::test_has_attr_invalid_args, test/test_jit.py::TestBuiltins::test_torch_check, test/test_jit.py::TestBuiltins::test_torch_check_invalid_args, test/test_jit.py::TestTensorBuiltins::test_method_on_number, test/test_jit.py::TestTensorBuiltins::test_scalar_to_num_conversions, test/test_jit.py::TestTensorBuiltins::test_tensor_item, test/test_jit.py::TestTensorBuiltins::test_tensor_properties, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign_device, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_inp_out, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_inp, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_out, test/test_jit.py::TestSymbolicShapeAnalysis::test_adaptive_avg_pool2d, test/test_jit.py::TestSymbolicShapeAnalysis::test_arange_shape, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_conv_deconv, test/test_jit.py::TestSymbolicShapeAnalysis::test_convolution_backward, test/test_jit.py::TestSymbolicShapeAnalysis::test_cross_entropy_loss, test/test_jit.py::TestSymbolicShapeAnalysis::test_if_propagation, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_graph_conv, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_refinement_through_graph_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_register_function_error_checking, test/test_jit.py::TestSymbolicShapeAnalysis::test_returning_input_symbolic_shapes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_analysis, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_embedding_bag, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_function_includes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shared_shape_graph, test/test_jit.py::TestSymbolicShapeAnalysis::test_size_and_sizes, test/test_jit.py::TestSymbolicShapeAnalysis::test_squeeze_dims, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_multi_output, test/test_jit.py::TestSymbolicShapeAnalysis::test_sym_ir_parsing, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_write, test/test_jit.py::TestOpDecompositions::test_op_decomposition, test/test_jit.py::TestOpDecompositions::test_registered_decomposition, test/test_jit.py::TestUnsupportedOps::test_factory_ops_requires_grad_fail, test/test_jit.py::TestUnsupportedOps::test_init_ops, test/test_jit.py::TestFreezing::test_freeze_interface_swapping_two_methods, test/test_jit.py::TestFreezing::test_freeze_interface_within_object, test/test_jit.py::TestFreezing::test_freeze_module, test/test_jit.py::TestFreezing::test_freeze_module_detach_gradient, test/test_jit.py::TestFreezing::test_freeze_module_in_training_mode, test/test_jit.py::TestFreezing::test_freeze_module_inlining, test/test_jit.py::TestFreezing::test_freeze_module_no_forward, test/test_jit.py::TestFreezing::test_freeze_module_return_self, test/test_jit.py::TestFreezing::test_freeze_module_return_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr4, test/test_jit.py::TestFreezing::test_freeze_module_with_call_method, test/test_jit.py::TestFreezing::test_freeze_module_with_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_fork2, test/test_jit.py::TestFreezing::test_freeze_module_with_fork_calling_module_method, test/test_jit.py::TestFreezing::test_freeze_module_with_helperfunction, test/test_jit.py::TestFreezing::test_freeze_module_with_inplace_mutable, test/test_jit.py::TestFreezing::test_freeze_module_with_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_dict, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_nested_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasing, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasingscalar, test/test_jit.py::TestFreezing::test_freeze_module_with_non_static_module_container_index, test/test_jit.py::TestFreezing::test_freeze_module_with_overlapping_attrs, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module_and_mutation, test/test_jit.py::TestFreezing::test_freeze_module_with_sharedclasstype, test/test_jit.py::TestFreezing::test_freeze_module_with_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_tuple, test/test_jit.py::TestFreezing::test_freeze_module_with_tupleoutput_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_unused_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method2, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method_on_submodule, test/test_jit.py::TestFreezing::test_freeze_no_forward, test/test_jit.py::TestFreezing::test_freeze_non_interface_module_swap, test/test_jit.py::TestFreezing::test_freeze_non_module_class_getattr, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_same_name, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_with_reassignment, test/test_jit.py::TestFreezing::test_freeze_with_interface_mutable, test/test_jit.py::TestFreezing::test_freeze_with_swapping_interfaces, test/test_jit.py::TestFreezing::test_module_getattr_indirection, test/test_jit.py::TestFreezing::test_module_with_shared_type_instances, test/test_jit.py::TestFrozenOptimizations::test_bn_not_broadcast_with_linear, test/test_jit.py::TestFrozenOptimizations::test_collapse_adjacent_conversions, test/test_jit.py::TestFrozenOptimizations::test_conv_add_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_not_forward, test/test_jit.py::TestFrozenOptimizations::test_conv_hardswish, test/test_jit.py::TestFrozenOptimizations::test_conv_mul_add_bn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn_no_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion_not_forward, test/test_jit.py::TestFrozenOptimizations::test_freeze_mkdlnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_dropout, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_feature_dropout, test/test_jit.py::TestFrozenOptimizations::test_hardswish_hardsigmoid, test/test_jit.py::TestFrozenOptimizations::test_incompatible_perf_formats, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_linear_concat, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_complex, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_different_input, test/test_jit.py::TestFrozenOptimizations::test_linear_multiple_blocks, test/test_jit.py::TestFrozenOptimizations::test_linear_non_constant_weight, test/test_jit.py::TestFrozenOptimizations::test_linear_transpose, test/test_jit.py::TestFrozenOptimizations::test_maxpool_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_fuser_broadcasting, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_inplace_removal, test/test_jit.py::TestFrozenOptimizations::test_numel_less_than_size_with_padding, test/test_jit.py::TestFrozenOptimizations::test_optimize_freeze_module, test/test_jit.py::TestFrozenOptimizations::test_pool2d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_pool3d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_remove_detach, test/test_jit.py::TestFrozenOptimizations::test_remove_detach_not_applied, test/test_jit.py::TestFrozenOptimizations::test_scalar_mul, test/test_jit.py::TestMKLDNNReinplacing::test_always_alive_values, test/test_jit.py::TestMKLDNNReinplacing::test_merge_liveness, test/test_jit.py::TestMKLDNNReinplacing::test_successful, test/test_jit.py::TestMKLDNNReinplacing::test_switch_inputs_to_inplace, test/test_jit.py::TestPeephole::test_conv_dim_folding, test/test_jit.py::TestPeephole::test_integer_refinement, test/test_jit.py::TestPeephole::test_noop_peephole, test/test_jit.py::TestPeephole::test_normalized_is_op, test/test_jit.py::TestPeephole::test_normalized_isnot_op, test/test_jit.py::TestPeephole::test_normalized_rsub, test/test_jit.py::TestPeephole::test_optimize_out_comparison_same_value, test/test_jit.py::TestPeephole::test_peephole, test/test_jit.py::TestPeephole::test_peephole_add_zero, test/test_jit.py::TestPeephole::test_peephole_arith, test/test_jit.py::TestPeephole::test_peephole_cuda, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_dict_modified, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_get_input_arg, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_missing_key, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_simple, test/test_jit.py::TestPeephole::test_peephole_dict_len, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dynamic, test/test_jit.py::TestPeephole::test_peephole_int, test/test_jit.py::TestPeephole::test_peephole_len_list, test/test_jit.py::TestPeephole::test_peephole_list_len, test/test_jit.py::TestPeephole::test_peephole_list_ops, test/test_jit.py::TestPeephole::test_peephole_no_output_aliasing, test/test_jit.py::TestPeephole::test_peephole_optional_refine, test/test_jit.py::TestPeephole::test_peephole_slice_all_three_args, test/test_jit.py::TestPeephole::test_peephole_slice_one_empty_arg, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_list_modified, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_non_const_args, test/test_jit.py::TestPeephole::test_peephole_slice_two_empty_args, test/test_jit.py::TestPeephole::test_peephole_type_refinements, test/test_jit.py::TestPeephole::test_peephole_with_non_output_writes, test/test_jit.py::TestPeephole::test_peephole_with_writes, test/test_jit.py::TestPeephole::test_refine_integer_values, test/test_jit.py::TestPeephole::test_short_circuit_optimization, test/test_jit.py::TestAliasAnalysis::test_becomes_wildcard_annotations, test/test_jit.py::TestAliasAnalysis::test_multiple_compilation_units, test/test_jit.py::TestAliasAnalysis::test_nested_list_construct_not_wildcard, test/test_jit.py::TestAliasAnalysis::test_recursive_calls, test/test_jit.py::TestSaveLoad::test_different_functions, test/test_jit.py::TestSaveLoad::test_different_interfaces, test/test_jit.py::TestSaveLoad::test_different_modules, test/test_jit.py::TestSaveLoad::test_many_collisions, test/test_jit.py::TestSaveLoad::test_save_load_large_string_attribute, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors_to_device, test/test_jit.py::TestSaveLoad::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoad::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoad::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoad::test_save_load_with_saved_traced_inputs, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only_forwardref, test/test_jit.py::TestSaveLoad::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoad::test_save_nonexit_file, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_functions, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_interfaces, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_modules, test/test_jit.py::TestSaveLoadFlatbuffer::test_many_collisions, test/test_jit.py::TestSaveLoadFlatbuffer::test_module_info_flatbuffer, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_reciprocal, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace_out, test/test_jit.py::TestModuleContainers::test_custom_container_forward, test/test_jit.py::TestModuleContainers::test_empty_dict_override_contains, test/test_jit.py::TestModuleContainers::test_module_inplace_construct, test/test_jit.py::TestModuleContainers::test_module_interface_special_methods, test/test_jit.py::TestModuleContainers::test_module_properties, test/test_jit.py::TestModuleContainers::test_moduledict, test/test_jit.py::TestModuleContainers::test_moduledict_getitem, test/test_jit.py::TestModuleContainers::test_moduledict_keyerror, test/test_jit.py::TestModuleContainers::test_normal_list_attribute_with_modules_error, test/test_jit.py::TestModuleContainers::test_parameterdict_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_iter, test/test_jit.py::TestModuleContainers::test_script_module_list_sequential, test/test_jit.py::TestModuleContainers::test_script_modulelist_index, test/test_jit.py::TestModuleContainers::test_sequential_intermediary_types, test/test_jit.py::TestModuleContainers::test_special_method_with_override, test/test_jit.py::TestModuleContainers::test_typed_module_dict, test/test_jit.py::TestModuleContainers::test_typed_module_list, test/test_jit.py::TestPythonBindings::test_add_input, test/test_jit.py::TestPythonBindings::test_aliasdb, test/test_jit.py::TestPythonBindings::test_canonicalize, test/test_jit.py::TestPythonBindings::test_cu_create_function, test/test_jit.py::TestPythonBindings::test_cu_get_functions, test/test_jit.py::TestPythonBindings::test_graph_create, test/test_jit.py::TestPythonBindings::test_graph_iterator_keepalive, test/test_jit.py::TestPythonBindings::test_invalidation, test/test_jit.py::TestPythonIr::test_param_strides, test/test_jit.py::TestPythonIr::test_permute_inputs_binding, test/test_jit.py::TestPythonIr::test_python_ir_utils, test/test_jit.py::TestPythonIr::test_python_ir_utils_graph, test/test_jit.py::TestFunctionalBlocks::test_subgraph_creation, test/test_jit.py::TestRemoveMutation::test_aten_inplace, test/test_jit.py::TestRemoveMutation::test_common_pytorch_list_ops, test/test_jit.py::TestRemoveMutation::test_if_output, test/test_jit.py::TestRemoveMutation::test_if_output_fail, test/test_jit.py::TestRemoveMutation::test_list_indexing_removal, test/test_jit.py::TestRemoveMutation::test_lists_append, test/test_jit.py::TestRemoveMutation::test_lists_insert, test/test_jit.py::TestRemoveMutation::test_special_mapped_op, test/test_jit.py::TestTorchbind::test_default_args, test/test_jit.py::TestTorchbind::test_hasattr, test/test_jit.py::TestTorchbind::test_lambda_as_constructor, test/test_jit.py::TestTorchbind::test_profiler_custom_op, test/test_jit.py::TestTorchbind::test_staticmethod, test/test_jit.py::TestTorchbind::test_torchbind, test/test_jit.py::TestTorchbind::test_torchbind_attr_exception, test/test_jit.py::TestTorchbind::test_torchbind_class_attr_recursive, test/test_jit.py::TestTorchbind::test_torchbind_class_attribute, test/test_jit.py::TestTorchbind::test_torchbind_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_def_property_getter_setter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_just_getter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_readwrite, test/test_jit.py::TestTorchbind::test_torchbind_getattr, test/test_jit.py::TestTorchbind::test_torchbind_getstate, test/test_jit.py::TestTorchbind::test_torchbind_instantiate_missing_class, test/test_jit.py::TestTorchbind::test_torchbind_lambda_method, test/test_jit.py::TestTorchbind::test_torchbind_no_init, test/test_jit.py::TestTorchbind::test_torchbind_optional_explicit_attr, test/test_jit.py::TestTorchbind::test_torchbind_pass_wrong_type, test/test_jit.py::TestTorchbind::test_torchbind_pickle_serialization, test/test_jit.py::TestTorchbind::test_torchbind_python_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_return_instance, test/test_jit.py::TestTorchbind::test_torchbind_return_instance_from_method, test/test_jit.py::TestTorchbind::test_torchbind_return_tuple, test/test_jit.py::TestTorchbind::test_torchbind_save_load, test/test_jit.py::TestTorchbind::test_torchbind_take_as_arg, test/test_jit.py::TestTorchbind::test_torchbind_take_instance_as_method_arg, test/test_jit.py::TestTorchbind::test_torchbind_tracing, test/test_jit.py::TestTorchbind::test_torchbind_tracing_nested, test/test_jit.py::TestModuleInterface::test_freeze_module_with_inplace_mutation_in_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface_and_fork, test/test_jit.py::TestModuleInterface::test_freeze_module_with_mutated_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_setattr_in_interface, test/test_jit.py::TestModuleInterface::test_module_apis_interface, test/test_jit.py::TestModuleInterface::test_module_doc_string, test/test_jit.py::TestModuleInterface::test_module_interface, test/test_jit.py::TestModuleInterface::test_module_interface_inheritance, test/test_jit.py::TestModuleInterface::test_module_interface_subtype, test/test_jit.py::TestModuleInterface::test_module_swap, test/test_jit.py::TestModuleInterface::test_module_swap_no_lazy_compile, test/test_jit.py::TestModuleInterface::test_module_swap_no_module_interface, test/test_jit.py::TestModuleInterface::test_module_swap_wrong_module, test/test_jit.py::TestModuleInterface::test_not_submodule_interface_call, test/test_jit.py::TestModuleInterface::test_script_module_as_interface_swap, test/test_jit.py::TestWith::test_with_as, test/test_jit.py::TestWith::test_with_errors, test/test_jit.py::TestWith::test_with_exceptions, test/test_jit.py::TestWith::test_with_no_as, test/test_jit.py::TestWith::test_with_no_grad, test/test_jit.py::TestWith::test_with_record_function, test/test_jit.py::TestEnum::test_closed_over_enum_constant, test/test_jit.py::TestEnum::test_enum_as_const, test/test_jit.py::TestEnum::test_enum_as_module_attribute, test/test_jit.py::TestEnum::test_enum_comp, test/test_jit.py::TestEnum::test_enum_comp_diff_classes, test/test_jit.py::TestEnum::test_enum_explicit_script, test/test_jit.py::TestEnum::test_enum_iterate, test/test_jit.py::TestEnum::test_enum_ivalue_type, test/test_jit.py::TestEnum::test_enum_module_return, test/test_jit.py::TestEnum::test_enum_name, test/test_jit.py::TestEnum::test_enum_return, test/test_jit.py::TestEnum::test_enum_value, test/test_jit.py::TestEnum::test_enum_value_types, test/test_jit.py::TestEnum::test_heterogenous_value_type_enum_error, test/test_jit.py::TestEnum::test_non_existent_enum_value, test/test_jit.py::TestEnum::test_string_enum_as_module_attribute, test/test_jit.py::TestEnum::test_typed_enum, test/test_jit.py::TestStringFormatting::test_modulo_operator, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_alternate_digit_placeholder, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_capital_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_char_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_true_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_double_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_exponent_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_float_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_lowercase_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_multiple_placeholders, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_format_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_subscript, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_few_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_many_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_unknown_format_specifier, test/test_jit.py::TestProfiler::test_aliasing_merge, test/test_jit.py::TestProfiler::test_autograd_fallback_graph, test/test_jit.py::TestProfiler::test_fallback_graph_not_specialized, test/test_jit.py::TestProfiler::test_iterative_fusion, test/test_jit.py::TestProfiler::test_local_fusion_strategy, test/test_jit.py::TestProfiler::test_not_fusing_scalar_ops, test/test_jit.py::TestProfiler::test_not_optimizing_property, test/test_jit.py::TestProfiler::test_specialize_backward, test/test_jit.py::TestProfiler::test_specialized_types, test/test_jit.py::TestProfiler::test_tensor_constant, test/test_jit.py::TestProfiler::test_tensor_type_not_determined_by_inputs, test/test_jit.py::TestProfiler::test_use_not_profiled, test/test_jit.py::TestSlice::test_module_list_slicing, test/test_jit.py::TestSlice::test_slice_as_variable, test/test_jit.py::TestSlice::test_slice_dynamic_index, test/test_jit.py::TestSlice::test_slice_kwarg, test/test_jit.py::TestSlice::test_slice_one_none, test/test_jit.py::TestSlice::test_slice_start_stop, test/test_jit.py::TestSlice::test_slice_start_stop_step, test/test_jit.py::TestSlice::test_slice_start_stop_with_none, test/test_jit.py::TestSlice::test_slice_stop_clipped, test/test_jit.py::TestSlice::test_slice_stop_only, test/test_jit.py::TestSlice::test_slice_stop_only_with_nones, test/test_jit.py::TestSlice::test_slice_string, test/test_jit.py::TestSlice::test_slice_tensor, test/test_jit.py::TestSlice::test_slice_tensor_multidim, test/test_jit.py::TestSlice::test_slice_tensor_multidim_with_dots, test/test_jit.py::TestSlice::test_slice_three_nones, test/test_jit.py::TestSlice::test_slice_two_nones, test/test_jit.py::TestSlice::test_tuple_slicing, test/test_jit.py::TestIgnorableArgs::test_add_out_ignorable_args, test/test_jit.py::TestIgnorableArgs::test_slice_ignorable_args_for_slice, test/test_jit.py::TestHooks::test_forward_tuple_input, test/test_jit.py::TestHooks::test_hook_compilation_hint, test/test_jit.py::TestHooks::test_hook_hook_name_collision, test/test_jit.py::TestHooks::test_hook_method_name_collision, test/test_jit.py::TestHooks::test_module_direct_forward_invocation, test/test_jit.py::TestHooks::test_module_forward_multiple_inputs, test/test_jit.py::TestHooks::test_module_forward_single_input, test/test_jit.py::TestHooks::test_module_hook_return_nothing, test/test_jit.py::TestHooks::test_module_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_module_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_module_no_forward_input, test/test_jit.py::TestHooks::test_module_same_hook_repeated, test/test_jit.py::TestHooks::test_submodule_called_directly_with_hooks, test/test_jit.py::TestHooks::test_submodule_direct_forward_invocation, test/test_jit.py::TestHooks::test_submodule_forward_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_forward_single_input, test/test_jit.py::TestHooks::test_submodule_forward_single_input_return_not_tupled, test/test_jit.py::TestHooks::test_submodule_hook_return_nothing, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_submodule_no_forward_input, test/test_jit.py::TestHooks::test_submodule_same_hook_repeated, test/test_jit.py::TestHooks::test_wrong_hook_signatures, test/test_jit.py::TestHooks::test_wrong_pre_hook_signatures, test/test_jit.py::TestWarn::test_warn, test/test_jit.py::TestWarn::test_warn_multiple_calls_multiple_warnings, test/test_jit.py::TestWarn::test_warn_multiple_calls_same_func_diff_stack, test/test_jit.py::TestWarn::test_warn_once_per_func, test/test_jit.py::TestWarn::test_warn_once_per_func_in_loop, test/test_jit.py::TestWarn::test_warn_only_once, test/test_jit.py::TestWarn::test_warn_only_once_in_loop_func, test/test_jit.py::TestIsinstance::test_bool, test/test_jit.py::TestIsinstance::test_dict, test/test_jit.py::TestIsinstance::test_dict_nested, test/test_jit.py::TestIsinstance::test_dict_no_contained_type, test/test_jit.py::TestIsinstance::test_dict_tensor, test/test_jit.py::TestIsinstance::test_empty_container_special_cases, test/test_jit.py::TestIsinstance::test_empty_container_throws_warning_in_eager, test/test_jit.py::TestIsinstance::test_float, test/test_jit.py::TestIsinstance::test_if_else, test/test_jit.py::TestIsinstance::test_in_if, test/test_jit.py::TestIsinstance::test_in_while_loop, test/test_jit.py::TestIsinstance::test_int, test/test_jit.py::TestIsinstance::test_list, test/test_jit.py::TestIsinstance::test_list_nested, test/test_jit.py::TestIsinstance::test_list_no_contained_type, test/test_jit.py::TestIsinstance::test_list_tensor, test/test_jit.py::TestIsinstance::test_list_tensor_type_true, test/test_jit.py::TestIsinstance::test_nontuple_container_rhs_throws_in_eager, test/test_jit.py::TestIsinstance::test_optional, test/test_jit.py::TestIsinstance::test_optional_nested, test/test_jit.py::TestIsinstance::test_optional_no_contained_type, test/test_jit.py::TestIsinstance::test_optional_none, test/test_jit.py::TestIsinstance::test_tensor_type_false, test/test_jit.py::TestIsinstance::test_tuple, test/test_jit.py::TestIsinstance::test_tuple_nested, test/test_jit.py::TestIsinstance::test_tuple_no_contained_type, test/test_jit.py::TestIsinstance::test_tuple_rhs, test/test_jit.py::TestIsinstance::test_tuple_tensor, test/test_jit.py::TestIsinstance::test_type_refinement, test/test_jit.py::TestPythonBuiltinOP::test_add, test/test_jit.py::TestPythonBuiltinOP::test_adv_indexing_list, test/test_jit.py::TestPythonBuiltinOP::test_advancedindex, test/test_jit.py::TestPythonBuiltinOP::test_gather, test/test_jit.py::TestPythonBuiltinOP::test_index, test/test_jit.py::TestPythonBuiltinOP::test_index_ellipses, test/test_jit.py::TestPythonBuiltinOP::test_inf, test/test_jit.py::TestPythonBuiltinOP::test_matmul_py3, test/test_jit.py::TestPythonBuiltinOP::test_mul, test/test_jit.py::TestPythonBuiltinOP::test_pow, test/test_jit.py::TestPythonBuiltinOP::test_random, test/test_jit.py::TestPythonBuiltinOP::test_slice, test/test_jit.py::TestPythonBuiltinOP::test_stepped_tuple_slicing, test/test_jit.py::TestPythonBuiltinOP::test_str_to_float, test/test_jit.py::TestPythonBuiltinOP::test_triple, test/test_jit.py::TestTyping::test_bool_list_io, test/test_jit.py::TestTyping::test_dict_comprehension, test/test_jit.py::TestTyping::test_dict_comprehension_scope, test/test_jit.py::TestTyping::test_dict_comprehension_with_type_annotation, test/test_jit.py::TestTyping::test_dict_in_not_in, test/test_jit.py::TestTyping::test_dict_invalid_annotations, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_key_mismatch, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_value_mismatch, test/test_jit.py::TestTyping::test_for_in_dict, test/test_jit.py::TestTyping::test_for_in_string, test/test_jit.py::TestTyping::test_for_tuple_assign, test/test_jit.py::TestTyping::test_for_tuple_unpack, test/test_jit.py::TestTyping::test_inherited_annotations_python_310, test/test_jit.py::TestTyping::test_list_io, test/test_jit.py::TestTyping::test_list_iterables, test/test_jit.py::TestTyping::test_list_sum, test/test_jit.py::TestTyping::test_list_type_refinement_annotation_element_mismatch, test/test_jit.py::TestTyping::test_list_unification, test/test_jit.py::TestTyping::test_multiple_assign, test/test_jit.py::TestTyping::test_namedtuple_error_source_attribution, test/test_jit.py::TestTyping::test_namedtuple_good_error, test/test_jit.py::TestTyping::test_namedtuple_py2, test/test_jit.py::TestTyping::test_namedtuple_redefine, test/test_jit.py::TestTyping::test_nested_list, test/test_jit.py::TestTyping::test_opt_opt_refinement, test/test_jit.py::TestTyping::test_optional_conversion, test/test_jit.py::TestTyping::test_optional_refinement, test/test_jit.py::TestTyping::test_optional_tuple, test/test_jit.py::TestTyping::test_singleton_tuple_unpack, test/test_jit.py::TestTyping::test_sum_list_diff_elms, test/test_jit.py::TestTyping::test_sum_list_empty, test/test_jit.py::TestTyping::test_sum_list_literal, test/test_jit.py::TestTyping::test_sum_list_one, test/test_jit.py::TestTyping::test_sum_list_wrong_type, test/test_jit.py::TestTyping::test_tuple_assignments, test/test_jit.py::TestTyping::test_tuple_create_return, test/test_jit.py::TestTyping::test_tuple_io, test/test_jit.py::TestTyping::test_tuple_keyword, test/test_jit.py::TestTyping::test_tuple_specialization, test/test_jit.py::TestHash::test_hash_bool, test/test_jit.py::TestHash::test_hash_device, test/test_jit.py::TestHash::test_hash_float, test/test_jit.py::TestHash::test_hash_int, test/test_jit.py::TestHash::test_hash_none, test/test_jit.py::TestHash::test_hash_string, test/test_jit.py::TestHash::test_hash_tensor, test/test_jit.py::TestHash::test_hash_tuple, test/test_jit.py::TestHash::test_hash_tuple_nested_unhashable_type, test/test_jit.py::TestComplex::test_binary_op_complex_tensor, test/test_jit.py::TestComplex::test_comparison_ops, test/test_jit.py::TestComplex::test_complex_constants_and_ops, test/test_jit.py::TestComplex::test_complex_constructor, test/test_jit.py::TestComplex::test_complex_list_sum, test/test_jit.py::TestComplex::test_complex_parse, test/test_jit.py::TestComplex::test_complexdict, test/test_jit.py::TestComplex::test_complexlist, test/test_jit.py::TestComplex::test_div, test/test_jit.py::TestComplex::test_infj_nanj_pickle, test/test_jit.py::TestComplex::test_pickle, test/test_jit.py::TestComplex::test_script, test/test_jit.py::TestComplex::test_tensor_attributes, test/test_jit.py::TestComplex::test_torch_complex_constructor_with_tensor, test/test_jit.py::TestJitUtils::test_checkscriptassertraisesregex, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_hybrid, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_keyword_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_or_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_positional, test/test_jit.py::TestJitUtils::test_no_tracer_warn_context_manager, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_and_init_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_only, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_jit_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_tensor, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_falsy_base_type, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_nonempty_container, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_attribute, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_torch_jit_import, test/test_jit.py::TestTypesAndAnnotation::test_annotate_outside_init, test/test_jit.py::TestTypesAndAnnotation::test_bad_types, test/test_jit.py::TestTypesAndAnnotation::test_ignore_with_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_fn_with_nonscriptable_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_module_attributes, test/test_jit.py::TestTypesAndAnnotation::test_inferred_type_error_message, test/test_jit.py::TestTypesAndAnnotation::test_mismatched_annotation, test/test_jit.py::TestTypesAndAnnotation::test_optional_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_parser_bug, test/test_jit.py::TestTypesAndAnnotation::test_pep585_type, test/test_jit.py::TestTypesAndAnnotation::test_python_callable, test/test_jit.py::TestTypesAndAnnotation::test_reannotate, test/test_jit.py::TestTypesAndAnnotation::test_tuple_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_type_annotate_py3, test/test_jit.py::TestTypesAndAnnotation::test_types_as_values, test/test_jit.py::TestTypesAndAnnotation::test_unimported_type_resolution, test/test_jit.py::TestMisc::test_broadcasting_list, test/test_jit.py::TestMisc::test_export_opnames_interface, test/test_jit.py::TestMisc::test_future_isinstance, test/test_jit.py::TestMisc::test_hacked_twin, test/test_jit.py::TestMisc::test_if_returning_any, test/test_jit.py::TestMisc::test_jit_get_operation_order, test/test_jit.py::TestMisc::test_joined_str, test/test_jit.py::TestMisc::test_kwarg_support, test/test_jit.py::TestMisc::test_legacy_tensor_constructor, test/test_jit.py::TestMisc::test_list_literal_infer, test/test_jit.py::TestMisc::test_math_inf, test/test_jit.py::TestMisc::test_parse_ir_annotate, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_negative, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_positive, test/test_jit.py::TestMisc::test_pow_multiple_dtype, test/test_jit.py::TestMisc::test_script_many_decorators, test/test_jit.py::TestMisc::test_str_refine_any, test/test_jit.py::TestMisc::test_subexpression_Dict_int_Future, test/test_jit.py::TestMisc::test_subexpression_Future_annotate, test/test_jit.py::TestMisc::test_subexpression_List_Future, test/test_jit.py::TestMisc::test_subexpression_Optional, test/test_jit.py::TestMisc::test_subexpression_Tuple_int_int_Future, test/test_jit.py::TestMisc::test_tuple_subscripted_assign, test/test_jit.py::TestMisc::test_unsafe_hacked_twin, test/test_jit.py::TestUpgraders::test_add_value_to_version_map, test/test_jit.py::TestUpgraders::test_aten_div_scalar_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_out_at_3, test/test_jit.py::TestUpgraders::test_aten_full_at_4, test/test_jit.py::TestUpgraders::test_aten_full_other_variants, test/test_jit.py::TestUpgraders::test_aten_full_out_at_4, test/test_jit.py::TestUpgraders::test_aten_linspace, test/test_jit.py::TestUpgraders::test_aten_linspace_out, test/test_jit.py::TestUpgraders::test_aten_logspace, test/test_jit.py::TestUpgraders::test_aten_logspace_out, test/test_jit.py::TestUpgraders::test_aten_test_serialization, test/test_jit.py::TestUpgraders::test_populated_test_upgrader_graph, test/test_jit.py::TestUpgraders::test_populated_upgrader_graph, test/test_jit.py::TestTensorCreationOps::test_randperm_default_dtype, test/test_jit.py::TestTensorCreationOps::test_randperm_specifed_dtype, test/test_jit.py::TestTensorCreationOps::test_tril_indices_default_dtype, test/test_jit.py::TestTensorCreationOps::test_tril_indices_specified_dtype, test/test_jit.py::TestTensorCreationOps::test_triu_indices_default_dtype, test/test_jit.py::TestTensorCreationOps::test_triu_indices_specified_dtype, test/test_jit.py::TestModuleAPIs::test_customized_state_dict_methods, test/test_jit.py::TestModuleAPIs::test_default_state_dict_methods, test/test_jit.py::TestModuleAPIs::test_submodule_customized_state_dict_methods, test/test_jit.py::TestScriptProfile::test_basic, test/test_jit.py::TestScriptProfile::test_empty, test/test_jit.py::TestScriptProfile::test_multi, test/test_jit.py::TestScriptProfile::test_script, test/test_jit.py::TestScriptProfile::test_section, test/test_jit.py::TestFunctionalToInplaceActivation::test_check_no_type_promotion, test/test_jit.py::TestFunctionalToInplaceActivation::test_functional_to_inplace_activation, test/test_jit.py::TestFunctionalToInplaceActivation::test_no_functional_to_inplace, test/test_jit.py::TestFunctionalToInplaceActivation::test_resnet18_correctness, test/test_jit.py::TestInplaceToFunctionalActivation::test_inplace_to_functional_activation, test/test_jit.py::TestInplaceToFunctionalActivation::test_resnet18_correctness, test/test_jit.py::TestParametrization::test_scriptable, test/test_jit.py::TestParametrization::test_traceable, test/test_jit.py::TestGetDefaultAttr::test_getattr_named_tuple, test/test_jit.py::TestGetDefaultAttr::test_getattr_tuple, test/test_jit.py::TestGetDefaultAttr::test_getattr_with_default, test/test_jit.py::TestAtenPow::test_aten_pow_zero_negative_exponent, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_1, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_2, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_3, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_4, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_insert_pre_packed_linear_before_inline_and_conv_2d_op, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_insert_pre_packed_linear_op, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_replace_conv1d_with_conv2d, test/test_jit.py::TestUnion::test_check_union_annotation, test/test_jit.py::TestUnion::test_union_T_None_is_equivalent_to_optional_T, test/test_jit.py::TestUnion::test_union_argument_order_is_ignored, test/test_jit.py::TestUnion::test_union_argument_order_is_ignored_container, test/test_jit.py::TestUnion::test_union_as_annotation, test/test_jit.py::TestUnion::test_union_as_annotation_in_typed_container, test/test_jit.py::TestUnion::test_union_as_annotation_py2, test/test_jit.py::TestUnion::test_union_as_dict_key, test/test_jit.py::TestUnion::test_union_as_dict_value, test/test_jit.py::TestUnion::test_union_as_internal_tuple_type, test/test_jit.py::TestUnion::test_union_branching_does_not_autoinfer_undeclared_union, test/test_jit.py::TestUnion::test_union_branching_does_not_widen_existing_inferred_type, test/test_jit.py::TestUnion::test_union_branching_with_union_return_and_homogenous_types, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type_empty_container, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type_union, test/test_jit.py::TestUnion::test_union_in_class_constructor, test/test_jit.py::TestUnion::test_union_memory_aliasing, test/test_jit.py::TestUnion::test_union_module_with_union_class_variable, test/test_jit.py::TestUnion::test_union_module_with_union_instance_variable, test/test_jit.py::TestUnion::test_union_optional_of_union_is_flattened, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_container, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_optional, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_subtyping, test/test_jit.py::TestUnion::test_union_return_type, test/test_jit.py::TestUnion::test_union_schema_matching_on_internal_type, test/test_jit.py::TestUnion::test_union_serialization_preserves_type_annotations, test/test_jit.py::TestUnion::test_union_subclasses_larger_union, test/test_jit.py::TestUnion::test_union_subtractive_refinement, test/test_jit.py::TestUnion::test_union_subtractive_refinement_with_container, test/test_jit.py::TestUnion::test_union_type_refinement, test/test_jit.py::TestUnion::test_union_type_refinement_internal_declaration, test/test_jit.py::TestUnion::test_union_type_refinement_partial_static_refinement_tuple_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_partial_static_refinement_union_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_statically_false, test/test_jit.py::TestUnion::test_union_type_refinement_statically_true, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs_noncontained_type, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs_union, test/test_jit.py::TestUnion::test_union_type_refinement_union_rhs, test/test_jit.py::TestUnion::test_union_variable_can_be_reassigned, test/test_jit.py::TestUnion::test_union_with_collections, test/test_jit.py::TestUnion::test_union_with_dict_assignment, test/test_jit.py::TestUnion::test_union_with_enum, test/test_jit.py::TestUnion::test_union_with_list_assignment, test/test_jit.py::TestUnion::test_union_with_scalar_values, test/test_jit.py::TestUnion::test_unions_of_a_single_argument_vanish, test/test_jit.py::TestUnion::test_unions_of_unions_are_flattened, test/test_jit.py::TestBatchMM::test_batch_mm_no_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_permitted_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation_if_node, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation_multiple_adds, test/test_jit.py::TestBatchMM::test_batch_mm_side_permitted_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_side_prohibited_mutation_common_side, test/test_jit.py::TestBatchMM::test_batch_mm_side_prohibited_mutation_uncommon_side, test/test_jit.py::TestDtypeAnalysis::test_binary_scalar, test/test_jit.py::TestDtypeAnalysis::test_binary_tensors, test/test_jit.py::TestDtypeAnalysis::test_combined, test/test_jit.py::TestDtypeAnalysis::test_conv_no_mixed_args, test/test_jit.py::TestDtypeAnalysis::test_custom_rules, test/test_jit.py::TestDtypeAnalysis::test_unary, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_expected_failure_nn_functional_adaptive_max_pool3d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_expected_failure_nn_functional_adaptive_max_pool3d_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_expected_failure_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_expected_failure_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_adaptive_avg_pool1d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_adaptive_avg_pool1d_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_adaptive_avg_pool1d_cpu_float32, 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test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_avg_pool2d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_avg_pool2d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_avg_pool3d_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_avg_pool3d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_avg_pool3d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_batch_norm_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_batch_norm_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_batch_norm_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_batch_norm_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_complex128, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_complex64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv1d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_complex128, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_complex64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_float16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_float32, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_float64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv2d_cpu_int64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv_transpose2d_cpu_bfloat16, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv_transpose2d_cpu_complex128, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv_transpose2d_cpu_complex64, test/test_jit.py::TestDtypeCustomRulesCPU::test_custom_rules_ints_nn_functional_conv_transpose2d_cpu_float16, 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test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_CrossMapLRN2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_GELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GRUCell, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardsigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardswish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardtanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_margin_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_delta, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_log_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_LSTMCell, test/test_jit.py::TestJitGeneratedModule::test_nn_LayerNorm_3d_no_affine_large_feature, test/test_jit.py::TestJitGeneratedModule::test_nn_LeakyReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_LogSigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Mish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_0d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_margin_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_p_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiheadAttention, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_PReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_lhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_rhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_with_non_default_args, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelShuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelUnshuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_RNNCell, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU6_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SiLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Sigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_zero_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_Softplus_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softsign_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanhshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Threshold_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer_multilayer_coder, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Unflatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_launch_configs, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial_special, test/test_jit.py::TestJitGeneratedModule::test_nn_multimarginloss_1d_input_0d_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_special, test/test_jit.py::TestProducerVersion::test_version
2025-08-14T22:43:23.9597261Z 
2025-08-14T22:43:27.8135935Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:43:27.8139450Z   import pkg_resources
2025-08-14T22:43:27.9432946Z Running functorch/test_ops 5/8 ... [2025-08-14 22:43:27.942900]
2025-08-14T22:43:27.9433689Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:43:27.9436690Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'not serial', '--shard-id=5', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:43:27.943288]
2025-08-14T22:43:40.7961034Z 
2025-08-14T22:43:40.7962501Z test_ops_fwd_gradients 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_2.2_2539ba045b6b71d1_.log
2025-08-14T22:43:40.9408678Z Running 1589 items in this shard: test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_H_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad_T_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___getitem___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmatmul___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmod___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rmul___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rpow___cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rpow___cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_fn_fwgrad_bwgrad___rsub___cpu_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_eigh_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_eigvals_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_householder_product_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_householder_product_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_inv_ex_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_inv_ex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_ldl_factor_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_ldl_factor_ex_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_ldl_factor_ex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_ldl_solve_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_lu_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_lu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_lu_factor_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_lu_factor_ex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_lu_solve_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_matrix_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_matrix_rank_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_multi_dot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_norm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_norm_subgradients_at_zero_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_pinv_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_qr_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_slogdet_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_slogdet_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_solve_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_solve_ex_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_solve_ex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_solve_triangular_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_svd_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_svd_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_svdvals_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_svdvals_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_tensorinv_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_tensorinv_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_tensorsolve_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_vecdot_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_vecdot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linalg_vector_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_linspace_tensor_overload_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log1p_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log2_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log2_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log_normal_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log_softmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_log_softmax_with_dtype_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logaddexp_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logcumsumexp_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logcumsumexp_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logdet_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logical_and_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logical_not_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logical_xor_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logspace_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logspace_tensor_overload_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logspace_tensor_overload_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_logsumexp_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_long_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_lu_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_lu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_lu_solve_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mH_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mT_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_amax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_amin_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_argmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_fill_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_logaddexp_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_median_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_normalize_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_scatter_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_scatter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_softmax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_std_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_sum_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_sum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_masked_var_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_matrix_exp_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_maximum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_median_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_meshgrid_variadic_tensors_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_min_binary_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_min_reduction_no_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_min_reduction_with_dim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_minimum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_mode_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_movedim_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_movedim_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nan_to_num_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanmedian_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nanquantile_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_narrow_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ne_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_neg_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_neg_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_empty_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_full_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_ones_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_zeros_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_new_zeros_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_alpha_dropout_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_avg_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_batch_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv3d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_cosine_embedding_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_ctc_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_dropout3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_embedding_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_gaussian_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_gelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_grid_sample_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_group_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardsigmoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hardswish_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_hinge_embedding_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_area_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_bicubic_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_interpolate_linear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_linear_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_logsigmoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_margin_ranking_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool1d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool2d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_pool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_grad_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multi_head_attention_forward_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_multilabel_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_circular_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_constant_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_constant_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pdist_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_poisson_nll_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_prelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_relu6_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_rrelu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_selu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_softsign_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_threshold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_unfold_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_unfold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nn_functional_upsample_bilinear_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_nonzero_static_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_fro_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_inf_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_inf_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_nuc_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_norm_nuc_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_normal_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_normal_in_place_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_normal_number_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ones_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ones_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ormqr_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_outer_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_permute_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_permute_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_permute_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polygamma_polygamma_n_0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polygamma_polygamma_n_1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_polygamma_polygamma_n_4_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_positive_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_positive_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_prod_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_prod_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_put_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_put_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_qr_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rad2deg_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rand_like_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randn_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_randn_like_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_ravel_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_real_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_renorm_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_renorm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_repeat_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reshape_as_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_reshape_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resize_as__cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resolve_conj_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_resolve_neg_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_roll_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_round_decimals_neg_3_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rsqrt_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_rsub_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_add_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_reduce_amax_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_reduce_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_reduce_prod_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_scatter_reduce_sum_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_select_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sgn_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_short_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_short_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sigmoid_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_bartlett_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_cosine_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_exponential_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_gaussian_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_general_cosine_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signal_windows_kaiser_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_signbit_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_slice_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_slice_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_slice_scatter_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sparse_mm_reduce_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sparse_sampled_addmm_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_bessel_j0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_chebyshev_polynomial_t_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_chebyshev_polynomial_u_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_chebyshev_polynomial_v_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_entr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_hermite_polynomial_h_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_i0e_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_i1_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_log_ndtr_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_i0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_modified_bessel_k0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_polygamma_special_polygamma_n_0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_u_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_v_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_spherical_bessel_j0_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_special_zeta_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_list_args_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_split_with_sizes_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sqrt_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sqrt_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_square_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_square_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_squeeze_multiple_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stack_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stack_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_mean_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_std_unbiased_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stft_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_stft_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_sum_to_size_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_svd_lowrank_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_take_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tan_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tanh_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensor_split_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensor_split_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tensordot_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tile_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_to_sparse_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_topk_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trace_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_transpose_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_trapz_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tril_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_tril_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triu_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_triu_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_true_divide_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_true_divide_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unbind_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unflatten_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unfold_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_uniform_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unique_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_chunk_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsafe_chunk_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_unsqueeze_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_var_mean_unbiased_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vdot_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_as_complex_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_copy_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_copy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_view_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vsplit_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_vstack_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_where_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_where_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_xlogy_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zero__cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zero__cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_cpu_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_like_cpu_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCPU::test_inplace_forward_mode_AD_zeros_like_cpu_float64
2025-08-14T22:43:41.0803059Z 
2025-08-14T22:43:45.5453915Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:43:45.5456737Z   import pkg_resources
2025-08-14T22:43:45.7749385Z Running functorch/test_ops 6/8 ... [2025-08-14 22:43:45.774164]
2025-08-14T22:43:45.7750262Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:43:45.7919376Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'not serial', '--shard-id=6', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:43:45.791374]
2025-08-14T22:49:50.7197975Z 
2025-08-14T22:49:50.7199345Z functorch/test_ops 1/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_1.8_62c6e5a3f10e0df2_.log
2025-08-14T22:49:50.8089463Z Running 1268 items in this shard: test/functorch/test_ops.py::TestOperatorsCPU::test_data_write_errors_under_transform_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_extremal_numerics_cross_entropy_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_extremal_numerics_l1_loss_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_extremal_numerics_log_softmax_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_extremal_numerics_mse_loss_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_angle_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_argmax_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_floor_cpu_complex128, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_floor_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_lt_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_conj_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_contiguous_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_flatten_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_hsplit_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_split_list_args_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_split_list_args_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_reshape_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_resolve_neg_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_unsqueeze_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_unsqueeze_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_kron_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_lerp_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_min_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_relu6_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_round_decimals_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp___rsub___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_isclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logaddexp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_ones_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scatter_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_shifted_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_take_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_tanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjpvmap_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_addmm_decomposed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_as_strided_partial_views_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_rfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_min_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pad_replicate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sparse_sampled_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unique_consecutive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__upsample_bilinear2d_aa_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_amin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_as_strided_scatter_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atleast_3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_block_diag_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bool_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_broadcast_to_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cdouble_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cholesky_inverse_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cross_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumulative_trapezoid_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diagflat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diagonal_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diagonal_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_permuted_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erfc_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erfinv_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_expand_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ihfft2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fill_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_float_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ge_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_gradient_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_half_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_half_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histc_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histogram_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_int_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isfinite_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isposinf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isreal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_unary_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lerp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lgamma_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_cholesky_ex_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_cond_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_cross_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_eigh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_householder_product_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_ldl_factor_ex_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lu_factor_ex_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_svd_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_softmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_and_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_matmul_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_meshgrid_list_of_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_min_binary_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_multinomial_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mv_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_3_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_narrow_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_avg_pool1d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_channel_shuffle_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_no_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_embedding_bag_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_embedding_functorch_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_instance_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_kl_div_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool1d_grad_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multi_head_attention_forward_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pdist_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_scaled_dot_product_attention_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_threshold_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_triplet_margin_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nonzero_static_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_fro_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ones_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ops_aten_index_put_functorch_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_outer_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_positive_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_reshape_as_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_reshape_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scalar_tensor_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sgn_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_general_hamming_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sparse_sampled_addmm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_airy_ai_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_v_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_entr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_i1e_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_ndtr_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sqrt_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_stack_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_mean_unbiased_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_stft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unsafe_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unsafe_split_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_block_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_eq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_rfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___getitem___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_byte_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_eye_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_max_pool2d_with_indices_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_pad_replicate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_rsqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unsafe_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_pad_replicate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_relu6_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ops_aten_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_polygamma_polygamma_n_2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_randn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_i1e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_shifted_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_square_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_unsafe_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_bernoulli_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_clone_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_diagflat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_hsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_inv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_lstsq_grad_oriented_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logaddexp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_rot90_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_ZeroGradientsGenVmapAutogradFunction_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_as_strided_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_half_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_pad_replicate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_hermite_polynomial_he_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_var_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_NumpyCubeAutogradFunction_cpu_float32
2025-08-14T22:49:50.8966003Z 
2025-08-14T22:49:53.9453179Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:49:53.9456135Z   import pkg_resources
2025-08-14T22:49:54.0707267Z Running functorch/test_ops 7/8 ... [2025-08-14 22:49:54.070314]
2025-08-14T22:49:54.0708068Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:49:54.0710456Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'not serial', '--shard-id=7', '--num-shards=8', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:49:54.070702]
2025-08-14T22:50:30.2949700Z 
2025-08-14T22:50:30.2951317Z functorch/test_ops 6/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_6.8_39864d364aad852f_.log
2025-08-14T22:50:30.3976318Z Running 1249 items in this shard: test/functorch/test_ops.py::TestOperatorsCPU::test_grad_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_tan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_var_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_as_strided_partial_views_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_eye_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_igamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_lstsq_grad_oriented_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_randn_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_take_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unique_consecutive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_partial_views_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_eq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_triplet_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_rad2deg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_squeeze_multiple_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_bool_raises_topk_cpu_bool, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_amax_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_argmin_cpu_complex128, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_le_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_sort_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_tensor_with_scalar_list_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_diagonal_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_split_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_mT_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_permute_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_permute_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp___getitem___functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_div_floor_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_dstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_eye_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_rfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_isclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mH_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_interpolate_trilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_hermite_polynomial_he_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_modified_bessel_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp___getitem___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_atleast_3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_byte_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_full_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_igamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nanmedian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nansum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pixel_unshuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_tan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_geqrf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_logaddexp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_meshgrid_list_of_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nanmedian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_padding_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_fractional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_hardshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_rms_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_tanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpyCubeAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_SortGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ZeroGradientsGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmatmul___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmul___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rpow___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addmm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_all_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atleast_1d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cauchy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_chalf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_max_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumsum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diag_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_div_floor_rounding_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_hfft2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_hfft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifft2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_frexp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_full_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_geqrf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_geqrf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_gradient_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_half_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_i0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_add_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_reduce_amin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isclose_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isnan_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isneginf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_kron_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_tensorinv_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log1p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_or_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_long_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_amin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_argmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_argmin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_mean_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_binary_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_reduction_no_dim_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_msort_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ne_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_new_full_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_avg_pool2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_avg_pool2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_avg_pool3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_binary_cross_entropy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_celu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_with_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_embedding_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hinge_embedding_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_area_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_reflect_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_rms_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_selu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_softmin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_upsample_bilinear_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_upsample_nearest_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ops_aten_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_permute_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_3_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_qr_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_renorm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resize__cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_rsub_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_select_scatter_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_nuttall_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_slice_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_u_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_hermite_polynomial_he_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_polygamma_special_polygamma_n_0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_mean_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_svd_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tanh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tensor_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_torch_ops_aten__safe_softmax_default_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_triangular_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_xlogy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_zero__cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall___rsub___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_atleast_3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_fftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_float_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rmod___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_dstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_hsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_isposinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_new_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_rms_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_split_with_sizes_copy_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_einsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_flipud_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_tanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_min_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_interpolate_trilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_randn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_stft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_all_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_arange_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_float_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_gradient_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logical_or_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_min_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_triplet_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_entr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvmapjvp_linalg_solve_cpu
2025-08-14T22:50:30.4966508Z 
2025-08-14T22:50:34.1938209Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:50:34.1941789Z   import pkg_resources
2025-08-14T22:50:34.3368802Z Running functorch/test_aotdispatch 3/6 ... [2025-08-14 22:50:34.336469]
2025-08-14T22:50:34.3369657Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:50:34.3371861Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=3', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:50:34.336835]
2025-08-14T22:54:38.7181627Z 
2025-08-14T22:54:38.7183235Z functorch/test_ops 5/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_5.8_9b07ab17809341c5_.log
2025-08-14T22:54:38.8062057Z Running 1327 items in this shard: test/functorch/test_ops.py::TestOperatorsCPU::test_extremal_numerics_nll_loss_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_block_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_rfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_full_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_kthvalue_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mH_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_max_pool2d_with_indices_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_randn_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_reduce_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_squeeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_argwhere_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_clone_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_hsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_triplet_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_reciprocal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_i1e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_square_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_all_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_bernoulli_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_block_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ceil_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_kthvalue_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_rot90_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_round_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_round_decimals_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_scatter_reduce_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_bool_raises_argmax_cpu_bool, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_bool_raises_argmin_cpu_bool, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_bool_raises_ceil_cpu_bool, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_maximum_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_dsplit_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_resolve_conj_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_resolve_neg_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_select_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_squeeze_multiple_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_unfold_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_view_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_diagflat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_einsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_geometric_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_gradient_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logaddexp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_rms_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_rot90_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_square_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_stft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unique_consecutive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp___getitem___functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_inv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_log1p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_new_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_fractional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_hardsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_randn_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_erfcx_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_squeeze_multiple_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjpvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjpvmap_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap___rmod___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_alias_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_all_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_clamp_min_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_diagflat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_index_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isreal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_hardsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_reciprocal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_rot90_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_scatter_reduce_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_entr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rdiv___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__segment_reduce_lengths_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_acosh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_alias_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argsort_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_as_strided_partial_views_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bernoulli_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_byte_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ceil_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ceil_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clone_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_combinations_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_constant_pad_nd_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cov_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dot_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exponential_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfftn_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_rfft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_geometric_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_geometric_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_grid_sampler_2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hash_tensor_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_inner_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_int_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isreal_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_binary_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_kthvalue_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_inv_ex_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_ldl_factor_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_ldl_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lstsq_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_multi_dot_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_pinv_hermitian_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_qr_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_solve_triangular_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_tensorsolve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vecdot_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vector_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logdet_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_not_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_amax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_median_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_scatter_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_median_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_meshgrid_variadic_tensors_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_min_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nanquantile_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nansum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_max_pool3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_alpha_dropout_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_no_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_cross_entropy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_elu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_gelu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_huber_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_bicubic_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_leaky_relu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_margin_ranking_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_circular_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_constant_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pairwise_distance_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pixel_unshuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_silu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_softplus_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_tanhshrink_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_nuc_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polar_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_pow_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_quantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_randint_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_reciprocal_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_remainder_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resolve_neg_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_rsqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_amax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_hamming_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signbit_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sparse_sampled_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_erfcx_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_hermite_polynomial_h_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_i1_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_log_ndtr_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_modified_bessel_k1_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_with_sizes_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_square_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_svd_lowrank_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_t_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_take_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_transpose_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unbind_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unflatten_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unsafe_chunk_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unsqueeze_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_var_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_vsplit_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__upsample_bilinear2d_aa_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_atleast_3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cummax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_div_floor_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_gradient_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_min_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_embedding_bag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_trilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_normal_number_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_spherical_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_take_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_tan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_var_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_inv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_log1p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logical_or_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mH_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_max_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_min_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_hardshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_normal_number_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_rot90_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scatter_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_modified_bessel_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_squeeze_multiple_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_stft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_tan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp__upsample_bilinear2d_aa_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_clamp_min_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_float_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_full_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_isreal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_triplet_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_rsub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_hermite_polynomial_he_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_multi_head_attention_forward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_i1e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_take_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_byte_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_div_floor_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_fftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mH_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nanmedian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_relu6_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_squeeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_tensor_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_SortGenVmapAutogradFunction_cpu_float32
2025-08-14T22:54:38.8800717Z 
2025-08-14T22:54:42.7217537Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:54:42.7220241Z   import pkg_resources
2025-08-14T22:54:42.8498974Z Running functorch/test_aotdispatch 4/6 ... [2025-08-14 22:54:42.849447]
2025-08-14T22:54:42.8499862Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:54:42.8501883Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=4', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:54:42.849798]
2025-08-14T22:59:26.5912016Z 
2025-08-14T22:59:26.5913445Z functorch/test_ops 7/8 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_7.8_0d14af63b76e297d_.log
2025-08-14T22:59:26.6906103Z Running 1306 items in this shard: test/functorch/test_ops.py::TestOperatorsCPU::test_grad_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_dstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_fftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_igamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_fractional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_ones_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_reciprocal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_hermite_polynomial_he_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_spherical_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_stft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_tensor_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_allclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ceil_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_geometric_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_inv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_mT_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_max_pool2d_with_indices_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_min_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_softshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_quantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_modified_bessel_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_squeeze_multiple_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unflatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_argwhere_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_einsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_full_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_log10_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_stride_padding_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_relu6_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_rms_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_randn_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_spherical_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_square_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_ceil_cpu_complex128, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_ceil_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_lt_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_maximum_cpu_complex128, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_expand_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_unbind_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_mT_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_narrow_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_select_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_special_grad_op_jvp_cpu, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_as_strided_partial_views_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_clamp_min_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_clone_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cummax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_float_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_log10_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_max_pool2d_with_indices_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_geometric_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_kthvalue_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_multi_dot_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_cosine_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atleast_3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bernoulli_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_char_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cummax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isposinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_jiterator_4inputs_with_extra_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_kron_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nonzero_static_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ones_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_H_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ScaleGradGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___getitem___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___getitem___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___radd___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmod___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rsub___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__softmax_backward_data_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_acos_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addmm_decomposed_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_aminmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_as_strided_partial_views_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atanh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bernoulli_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_byte_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cartesian_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_char_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cholesky_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_conj_physical_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumprod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_digamma_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_div_floor_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_eq_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exp2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_hfftn_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ihfft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfft2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_float_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_float_power_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_floor_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_frac_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_gather_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_heaviside_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histogramdd_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hsplit_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hstack_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_igamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_fill_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_reduce_amax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_2inputs_2outputs_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ldexp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_eigvals_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lstsq_grad_oriented_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_lu_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_pinv_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linspace_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log10_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_softmax_with_dtype_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lt_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mT_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_softmin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_std_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_sum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_var_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_maximum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_min_reduction_no_dim_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_minimum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_1_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nanmean_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nanmedian_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_native_dropout_backward_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_native_dropout_backward_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_batch_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv1d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_padding_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv_transpose3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_cosine_similarity_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hardshrink_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hardsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_bilinear_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_unpool3d_grad_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_mse_loss_functorch_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multi_margin_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pixel_unshuffle_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_selu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_unfold_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_pinverse_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_rand_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_roll_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_rsub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_sum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_select_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_blackman_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_gaussian_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_general_cosine_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_bessel_j0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_bessel_y0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_w_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_entr_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_laguerre_polynomial_l_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_shifted_chebyshev_polynomial_t_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_spherical_bessel_j0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_list_args_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_squeeze_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_squeeze_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_stft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tan_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_trunc_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unbind_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unique_consecutive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unique_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_var_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_var_mean_unbiased_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_view_as_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_view_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_zeros_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall___rmod___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_alias_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_byte_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_dstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_gradient_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rsub___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_arange_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_fftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_floor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_frexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_geometric_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_half_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_multinomial_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_mse_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_pixel_unshuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_rad2deg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_entr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_erfcx_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unique_consecutive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_view_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_igamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_cholesky_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_ldl_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logaddexp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nansum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_spherical_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_arange_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_argwhere_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_baddbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_broadcast_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_byte_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_geqrf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_grid_sampler_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_matrix_rank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nextafter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv_transpose1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_grid_sample_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_local_response_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_normal_number_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_reciprocal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_std_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp__upsample_bilinear2d_aa_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_argwhere_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cummax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_div_no_rounding_mode_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_fft_ifft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule___rmod___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule__segment_reduce_lengths_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_addmm_decomposed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_float_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_kron_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_log10_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_hardshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_erfcx_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_special_shifted_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_tensor_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_has_batch_rule_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_isreal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_huber_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_scaled_dot_product_attention_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_quantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_shifted_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_squeeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_tensor_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp__unsafe_masked_index_put_accumulate_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_alias_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_argwhere_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_block_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_clamp_min_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_geqrf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ldexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_log2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_meshgrid_list_of_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_multinomial_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_hardshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_trilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ops_aten_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_randn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_randn_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_legendre_polynomial_p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_trapz_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_NumpyTakeAutogradFunction_cpu_float32
2025-08-14T22:59:26.7637277Z 
2025-08-14T22:59:28.9363734Z Uploading artifacts took 2.34 seconds
2025-08-14T22:59:30.4866589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T22:59:30.4869516Z   import pkg_resources
2025-08-14T22:59:30.6141605Z Running functorch/test_aotdispatch 5/6 ... [2025-08-14 22:59:30.613585]
2025-08-14T22:59:30.6142492Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T22:59:30.6147272Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=5', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 22:59:30.613933]
2025-08-14T23:02:48.9332000Z 
2025-08-14T23:02:48.9333861Z functorch/test_aotdispatch 4/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_4.6_bb54cd279d638214_.log
2025-08-14T23:02:48.9681066Z Running 346 items in this shard: test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_True_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_False_dynamic_shapes_False, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_on_grad_out, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_pass_autocast_off, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_buffer_copied_in_graph_with_different_shapes, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_dupe_arg_returned_as_output, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_dynamic_shape_output_not_in_bw_graph, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_inplace_requires_grad_true, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_aliases_bases_out_of_order, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_false_aliasing, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_requires_grad_detach, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_simple_with_none_and_nontensor, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_storage_resize_up, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_output_view_simple, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_invalid_dupe, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_invalid_requires_grad, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_invalid_requires_grad_fake, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_module, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_nonidempotent_amp, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_and_returned, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_returned_multiple_times, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_multiple_inputs_get_correct_one, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_dict, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_saved_tensors_hooks_mutations_raise, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_set__and_data_mutation_good, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_single_output, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_some_output_requires_grad_input_doesnt, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_squeeze_mutation, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_view_detach, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_ban_dropout_mut_pre_dispatch, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_forward_mutation_multiple_mut, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_forward_mutation_no_buffer_mut, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_input_mutation_on_parameter_banned, test/functorch/test_aotdispatch.py::TestPartitioning::test_meta_tensor_inplace_op, test/functorch/test_aotdispatch.py::TestPartitioning::test_min_cut_partitioner_save_shape, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_incorrect_backward, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_input_mutation_and_output_alias, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_aot_module_simplified_dynamic, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_inference_python_dispatcher, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_base_saved_tensors_hooks_filtering_mode_no_static, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_subclass_parameters, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_nnc_passthrough_cpu, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive___rmatmul___cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive___rmod___cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_addbmm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_addmm_decomposed_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_as_strided_copy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_as_strided_partial_views_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_atan_cpu_float32, 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test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_xlogy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_AvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_BatchNorm1d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_BatchNorm3d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_GRUCell_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm1d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm3d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LSTM_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LazyConvTranspose2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LazyConvTranspose3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MSELoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MarginRankingLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MaxPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Mish_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_RNNCell_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReflectionPad3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Tanh_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AdaptiveMaxPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_BCELoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_BCEWithLogitsLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_BatchNorm2d_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_BatchNorm2d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ConstantPad2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ConstantPad3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Conv3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ConvTranspose1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_FractionalMaxPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_LazyConvTranspose1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_MaxPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_MultiLabelMarginLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_MultiheadAttention_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_NLLLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_PoissonNLLLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReLU6_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReflectionPad3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReplicationPad2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Tanhshrink_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_TransformerDecoderLayer_cpu_float32, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_backward_mutation_forward_inputs, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_backward_mutation_forward_inputs_create_graph, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_batch_norm_amp, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_buffer_batch_norm, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_custom_tensor_metadata, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_dupe_arg, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_inner_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_aliased_with_mutation_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_data_and_metadata_mutation_aliases_other_input, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_aliases_bases_out_of_order, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_aliases_other_input, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_and_output_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_return, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_simple_with_none_and_nontensor, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_storage_resize_down, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_invalid_requires_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_invalid_requires_grad_fake, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_input_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_inplace_view_and_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_multiple_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_no_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_outputs_are_aliased, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_single_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_some_output_requires_grad_input_doesnt, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_synthetic_base_base_attribute_is_none, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_True_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_autocast_disable_guard, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_mutation_forward_inputs_create_graph, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_dupe_arg, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_data_and_metadata_mutation, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_other_input2, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_dupe_left_bias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_input_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_inplace_view_and_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_mutation_linear, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_op_depending_on_symint, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_set__and_data_mutation_bad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_set__steals_view_chain, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_view_and_inplace_view
2025-08-14T23:02:49.0012361Z 
2025-08-14T23:02:52.2174487Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:02:52.2176122Z   import pkg_resources
2025-08-14T23:02:52.3452167Z Running optim/test_swa_utils 1/1 ... [2025-08-14 23:02:52.344810]
2025-08-14T23:02:52.3452636Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:02:52.3455150Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:02:52.345224]
2025-08-14T23:02:55.6780648Z 
2025-08-14T23:02:55.6781892Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_097ec2f80697f6f8_.log
2025-08-14T23:02:55.6782969Z 
2025-08-14T23:02:59.0495819Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:02:59.0499200Z   import pkg_resources
2025-08-14T23:02:59.1949596Z Running functorch/test_vmap 2/2 ... [2025-08-14 23:02:59.194561]
2025-08-14T23:02:59.1950299Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:02:59.1955174Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:02:59.195008]
2025-08-14T23:04:03.4851424Z 
2025-08-14T23:04:03.4853032Z functorch/test_aotdispatch 3/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_3.6_1f684b22f7c0da0d_.log
2025-08-14T23:04:03.5380289Z Running 385 items in this shard: test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_False_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_True_dynamic_shapes_False, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_False_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_forward_inputs, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_forward_inputs_create_graph, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_batch_norm_amp, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_batchnorm_inference, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_buffer_batch_norm, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_complex_linear, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_grad_context, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_inference_mode, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_inner_grad, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_aliased_with_mutation_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_metadata2, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_requires_grad_no_grad_detach_mixed, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_set__nop, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_mark_activations_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_mem_leak_from_save_for_bw, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_multi_output_list, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_nested_subclasses_complicated_inps_mixed, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_input_multi_output_view_should_raise_autograd_error, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_inplace_view, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_inplace_view_with_detach, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_single, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_all_alias_types, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_some_outputs_dont_require_grad_view, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_subclass_metadata_mutation_req_grad_True, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_module_joint, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_multiple_outputs_require_grad_banned, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_buffer_mutation_metadata, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_composite_implicit_linear, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_contiguous, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_map_2, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_with_cond, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_simplified_basic, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_synthetic_bases_banned, test/functorch/test_aotdispatch.py::TestPartitioning::test_default_partitioner_output_tensor_shape_tensor, test/functorch/test_aotdispatch.py::TestPartitioning::test_min_cut_partitioner, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_inference, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_input_mutation, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_aot_module_simplified_preserves_stack_trace_from_mutation, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_False_device_cuda, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_True_device_cuda, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_base_saved_tensors_hooks_filtering_mode_donated, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_donated_buffers, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_make_fx_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_make_fx_no_decompose_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_nnc_jit_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_resnet18_backward_trace_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_scalar_device_cpu, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive__batch_norm_with_update_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_add_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_addcdiv_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_all_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_any_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_argsort_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_as_strided_scatter_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_auto_functionalize_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_broadcast_tensors_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cauchy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cdouble_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cholesky_inverse_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_clone_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cond_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_corrcoef_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cosh_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cumulative_trapezoid_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_diff_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_digamma_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_div_floor_rounding_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_div_no_rounding_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_dstack_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_exp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_hfft_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_hfftn_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_rfft2_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_rfft_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_frexp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_ge_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_gradient_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_half_cpu_float32, 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test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_masked_prod_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_masked_softmin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_mean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_min_reduction_with_dim_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_minimum_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nanmean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nansum_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_native_layer_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_ne_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_new_empty_strided_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_conv2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_dropout_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_elu_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_embedding_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_gelu_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_glu_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_group_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_kl_div_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_pad_replicate_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_pdist_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_softsign_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_unfold_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_normal_in_place_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_ones_like_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_ormqr_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_permute_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_randint_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_ravel_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_resolve_conj_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_roll_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_round_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_scan_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_scatter_add_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_scatter_reduce_mean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_scatter_reduce_prod_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_select_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_sigmoid_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_signal_windows_general_cosine_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_signal_windows_hamming_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_signal_windows_kaiser_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_sinc_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_slice_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_airy_ai_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_hermite_polynomial_h_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_i1_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_modified_bessel_k0_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_split_with_sizes_copy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_std_mean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_stft_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_svd_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_svd_lowrank_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_t_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_tensordot_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_to_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_trace_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_true_divide_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_unbind_copy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_unique_consecutive_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_var_mean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_view_as_complex_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_while_loop_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_symbolic_exhaustive_zeros_like_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_AdaptiveAvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_AdaptiveMaxPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_BCEWithLogitsLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ConstantPad3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Embedding_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_FractionalMaxPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_GELU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_GRU_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm2d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm3d_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LPPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LazyConv3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Linear_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LocalResponseNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MultiMarginLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MultiheadAttention_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_RNN_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReLU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReflectionPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReflectionPad2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReplicationPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Sigmoid_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Softmin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Softplus_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_TransformerEncoder_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AdaptiveAvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AdaptiveMaxPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AvgPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ConstantPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GELU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GRU_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GroupNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_HuberLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_LayerNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_LazyConvTranspose2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Mish_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_MultiLabelSoftMarginLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_RNNCell_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReLU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReplicationPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Tanh_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Threshold_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Transformer_cpu_float32, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_True_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_backward_mutation_on_grad_out, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_batchnorm, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_batchnorm_inference, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_inference_mode, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_metadata_mutation_aliases, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_false_aliasing, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_detach, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_no_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_output_view_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mutation_of_input_in_fw_and_bw, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses_complicated_inps, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses_complicated_inps_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_new_inp_requires_grad_now, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_multi_output_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_output_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_set__and_data_mutation_good, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_subclass_metadata_mutation_req_grad_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_False_dynamic_shapes_False, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_pass_autocast_custom, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_pass_autocast_on, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_batch_norm_amp, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_compilation_context, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_embedding_bag_view_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_and_none_require_gradients, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_and_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_is_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_metadata2, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_output_view_metadata_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_dupe_fake, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_requires_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_mark_outputs_dynamic_use_autograd_False, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_module, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_multi_output_list, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_no_grad_input_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_and_returned, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_single, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_real_weights_in_symbolic_mode_with_inplace_ops, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_saved_tensors_hooks_mutations_raise
2025-08-14T23:04:03.5774506Z 
2025-08-14T23:04:07.0035373Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:07.0038399Z   import pkg_resources
2025-08-14T23:04:07.1332266Z Running nn/test_load_state_dict 1/1 ... [2025-08-14 23:04:07.132761]
2025-08-14T23:04:07.1333001Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:07.1335574Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:07.133202]
2025-08-14T23:04:11.8062594Z 
2025-08-14T23:04:11.8063755Z nn/test_load_state_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_load_state_dict_1.1_d689b772c56d95d9_.log
2025-08-14T23:04:11.8075114Z Running 27 items in this shard: test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_ref_cycle_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_False, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_True
2025-08-14T23:04:11.8085961Z 
2025-08-14T23:04:15.0864545Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:15.0867463Z   import pkg_resources
2025-08-14T23:04:15.2185223Z Running test_shape_ops 1/1 ... [2025-08-14 23:04:15.217500]
2025-08-14T23:04:15.2185854Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:15.2188038Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_shape_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:15.218017]
2025-08-14T23:04:21.7943609Z 
2025-08-14T23:04:21.7945199Z test_shape_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_shape_ops_1.1_2b0f9c644b854008_.log
2025-08-14T23:04:21.7997071Z Running 97 items in this shard: test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_propagates_nans_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_clamp_raises_arg_errors_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_complex_rot90_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_complex_rot90_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_diag_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_diag_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_diagonal_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_diagonal_multidim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_errors_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_large_tensor_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_complex64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_numpy_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_unsupported_dtype_cpu_quint2x4, test/test_shape_ops.py::TestShapeOpsCPU::test_flip_unsupported_dtype_cpu_quint4x2, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_fliplr_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_flipud_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_movedim_invalid_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_astuple_out_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_bfloat16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_bool, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_discontiguous_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_no_warning_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_nonzero_non_diff_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_rot90_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_complex128, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_sparse_dense_dim_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_tolist_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_float32, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_float64, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int16, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int32, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int64, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_int8, test/test_shape_ops.py::TestShapeOpsCPU::test_trace_cpu_uint8, test/test_shape_ops.py::TestShapeOpsCPU::test_unbind_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_all_devices_and_dtypes_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_errors_cpu, test/test_shape_ops.py::TestShapeOpsCPU::test_unfold_scalars_cpu
2025-08-14T23:04:21.8044779Z 
2025-08-14T23:04:25.8880229Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:25.8883294Z   import pkg_resources
2025-08-14T23:04:26.1096168Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-08-14 23:04:26.108980]
2025-08-14T23:04:26.1097194Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:26.1101438Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:26.109647]
2025-08-14T23:04:32.0571164Z 
2025-08-14T23:04:32.0572713Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_f5da6409345f16f0_.log
2025-08-14T23:04:32.0663732Z Running 102 items in this shard: test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_equivalent_dtype_hashing, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_invalid_types, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Bool, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Bytes0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex128, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Complex64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Datetime64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float128, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Float64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Int8, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Object0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Str0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Timedelta64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt16, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_UInt8, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Uint32, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Uint64, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_numeric_style_types_are_invalid_dtype_Void0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation1, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation2, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_comparison_operation3, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_richcompare_invalid_dtype_equality, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t0, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t1, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t2, test/torch_np/numpy_tests/core/test_dtype.py::TestBuiltin::test_run_t3, test/torch_np/numpy_tests/core/test_dtype.py::TestDtypeAttributeDeletion::test_dtype_non_writable_attributes_deletion, test/torch_np/numpy_tests/core/test_dtype.py::TestDtypeAttributeDeletion::test_dtype_writable_attributes_deletion, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t0, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t1, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t2, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t3, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_builtin_t4, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_DType11, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_bool__10, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_complex128_4, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_complex64_3, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float16_0, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float32_1, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_float64_2, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int16_7, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int32_8, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int64_9, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_int8_6, test/torch_np/numpy_tests/core/test_dtype.py::TestPickling::test_pickle_types_uint8_5, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_complex64_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_float16_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_float32_complex64_None, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_other_4294967295_expected1_expected_weak1, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_other_value_based_other_65535_expected0_expected_weak0, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other0_expected0, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other1_expected1, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other2_expected2, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other3_expected3, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other4_expected4, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other5_expected5, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_complex_scalar_value_based_other6_expected6, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes0_expected0, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes1_expected1, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes2_expected2, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes3_expected3, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes4_expected4, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes5_expected5, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes6_expected6, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes7_expected7, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes8_expected8, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_permutations_do_not_influence_result_dtypes9_expected9, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_18446744073709551616, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_2, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_200, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_4294967296, test/torch_np/numpy_tests/core/test_dtype.py::TestPromotion::test_python_integer_promotion_val_9223372036854775808, test/torch_np/numpy_tests/core/test_dtype.py::TestMisc::test_dtypes_are_true, test/torch_np/numpy_tests/core/test_dtype.py::TestMisc::test_keyword_argument, test/torch_np/numpy_tests/core/test_dtype.py::TestFromDTypeAttribute::test_recursion, test/torch_np/numpy_tests/core/test_dtype.py::TestFromDTypeAttribute::test_simple, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_?, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_B, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_D, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_F, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_b, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_d, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_e, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_f, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_h, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_i, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_dtype_subclass_code_l, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_scalar, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_0, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_1, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_2, test/torch_np/numpy_tests/core/test_dtype.py::TestClassGetItem::test_subscript_tuple_arg_len_3
2025-08-14T23:04:32.0744057Z 
2025-08-14T23:04:36.3953554Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:36.3956349Z   import pkg_resources
2025-08-14T23:04:36.5840817Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-08-14 23:04:36.583581]
2025-08-14T23:04:36.5841618Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:36.5846319Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:36.584209]
2025-08-14T23:04:42.2179485Z 
2025-08-14T23:04:42.2181737Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_cad3bf1a2bf90de3_.log
2025-08-14T23:04:42.2289135Z Running 119 items in this shard: test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast1d::test_r1array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast2d::test_r2array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestAtleast3d::test_3D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_casting_and_dtype, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_casting_and_dtype_type_error, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_empty_input, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_generator, test/torch_np/numpy_tests/core/test_shape_base.py::TestHstack::test_non_iterable, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_0D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_1D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_2D_array, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_2D_array2, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_casting_and_dtype, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_casting_and_dtype_type_error, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_empty_input, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_generator, test/torch_np/numpy_tests/core/test_shape_base.py::TestVstack::test_non_iterable, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_bad_out_shape, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_concatenate, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_concatenate_axis_None, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_exceptions, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_large_concatenate_axis_None, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_operator_concat, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_axis_0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_out_and_dtype_simple, test/torch_np/numpy_tests/core/test_shape_base.py::TestConcatenate::test_returns_copy, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_c8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f4_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_f8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_equiv, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_no, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_safe, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_same_kind, test/torch_np/numpy_tests/core/test_shape_base.py::TestStackMisc::test_stack_out_and_dtype_axis_0_out_dtype_i8_casting_unsafe, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_3d, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_complicated, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_memory_order, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_mixed_1d_and_2d, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_simple_column_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_simple_row_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_total_size_estimate, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_column_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_multiple_rows, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_1d_arrays_row_wise, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_block_with_mismatched_shape, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_different_ndims, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_different_ndims_depths, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_empty_lists, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_invalid_nesting, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_nested, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_no_lists, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_returns_copy, test/torch_np/numpy_tests/core/test_shape_base.py::TestBlock::test_tuple
2025-08-14T23:04:42.2390883Z 
2025-08-14T23:04:46.5950928Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:46.5954235Z   import pkg_resources
2025-08-14T23:04:46.7962069Z Running test_type_info 1/1 ... [2025-08-14 23:04:46.795712]
2025-08-14T23:04:46.7962858Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:46.7968387Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_info.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:46.796348]
2025-08-14T23:04:51.7281979Z 
2025-08-14T23:04:51.7283713Z test_type_info 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_info_1.1_5d01fd50ca8b6bcf_.log
2025-08-14T23:04:51.7287294Z Running 5 items in this shard: test/test_type_info.py::TestDTypeInfo::test_finfo, test/test_type_info.py::TestDTypeInfo::test_iinfo, test/test_type_info.py::TestDTypeInfo::test_invalid_input, test/test_type_info.py::TestDTypeInfo::test_to_complex, test/test_type_info.py::TestDTypeInfo::test_to_real
2025-08-14T23:04:51.7289821Z 
2025-08-14T23:04:56.3576481Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:04:56.3579507Z   import pkg_resources
2025-08-14T23:04:56.5511899Z Running test_dataloader 1/1 ... [2025-08-14 23:04:56.550756]
2025-08-14T23:04:56.5512731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:04:56.5519211Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dataloader.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:04:56.551492]
2025-08-14T23:06:30.3259431Z 
2025-08-14T23:06:30.3261141Z functorch/test_aotdispatch 5/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_5.6_6b6292d63c72a2a2_.log
2025-08-14T23:06:30.3611091Z Running 336 items in this shard: test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_metadata, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_custom_autograd, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_custom_tensor_metadata, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_dupe_arg, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_dupe_arg_torture, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_duplicated_arguments_on_tensor_overlap, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_hidden_from_autograd_aliasing, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_output_view_metadata_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_list_codegen, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_multi_output, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_mutates_input_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_nested_subclasses_non_nested_grad, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_no_grad, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_view_and_inplace_view, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_func_composite_implicit, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_func_view, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_output_requires_grad_in_no_grad_views, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_aot_module_simplified, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_grads_no_force_contiguous_nested_subclass, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_grads_no_force_contiguous_nested_tensor_tangent, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_lift_fresh_copy_in_graph, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_False_device_cpu, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_True_device_cpu, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_True_test_subclasses_True_device_cpu, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_params, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_make_fx_functionalize_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_nnc_pytrees_cpu, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_T_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive___rsub___cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive__native_batch_norm_legit_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_amin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_aminmax_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_argwhere_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_atleast_2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_bucketize_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cfloat_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_chalf_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cross_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_diagonal_copy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_dist_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_dot_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_empty_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_erfc_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_ifft2_cpu_float32, 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test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_qr_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_svd_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_log_normal_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_logcumsumexp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_logical_not_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_std_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_sum_cpu_float32, 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test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_embedding_bag_view_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_aliases_and_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_metadata, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_modifies_autograd_meta_of_aliases, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_output_view_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_no_grad_detach_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_no_grad_inference_graph, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_set__nop, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_simple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_output_aliase_custom_autograd_function, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_output_view_metadata_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_output_view_simple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_invalid_dupe_fake, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mark_outputs_dynamic_use_autograd_False, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mem_leak_from_save_for_bw, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_module, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_multi_output_list, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mutates_input_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nonidempotent_amp, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_input_multi_output_view_should_raise_autograd_error, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_and_returned, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_inplace_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_returned_multiple_times, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_multiple_inputs_get_correct_one, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_op_depending_on_symint, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_set__and_data_mutation_bad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_set__not_allowed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_subclasses_mixed_mode, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_view_and_inplace_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_mutation_forward_inputs, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_batchnorm_inference, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_buffer_copied_in_graph, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_custom_tensor_metadata, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_alias_everything, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_other_input, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_false_aliasing, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_output_view_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_requires_grad_no_grad_inference_graph, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_return, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_simple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_inputs_overlapping_with_mutation_guard_base, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_dupe, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_multi_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_mutates_input_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_nested_subclasses, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_nonidempotent_amp, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_input_multi_output_view_should_raise_autograd_error, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_and_returned_different_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_inplace_view_with_detach, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_multi_output_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_subclass_metadata_mutation_req_grad_False
2025-08-14T23:06:30.3947796Z 
2025-08-14T23:06:34.6471345Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:06:34.6474107Z   import pkg_resources
2025-08-14T23:06:34.8478724Z Running test_jit_llga_fuser 1/1 ... [2025-08-14 23:06:34.846812]
2025-08-14T23:06:34.8479532Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:06:34.8481539Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_llga_fuser.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:06:34.847273]
2025-08-14T23:07:52.8527895Z 
2025-08-14T23:07:52.8534100Z test_jit_llga_fuser 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_llga_fuser_1.1_752a4b90e22bed45_.log
2025-08-14T23:07:52.8606908Z Running 107 items in this shard: test/test_jit_llga_fuser.py::TestEnableDisableLlgaFuser::test_context_manager, test/test_jit_llga_fuser.py::TestDynamoAOT::test_dynamo_aot_ts_onednn, test/test_jit_llga_fuser.py::TestModel::test_vision_alexnet_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_alexnet_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet121_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet121_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet161_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet161_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet169_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet169_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet201_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet201_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b1_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b1_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b2_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b3_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b3_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b4_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b4_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b5_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b5_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b6_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b6_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b7_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b7_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_googlenet_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_googlenet_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mnasnet1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mnasnet1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v2_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v3_large_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v3_large_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_regnet_y_400mf_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_regnet_y_400mf_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnet50_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnet50_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext101_32x8d_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext101_32x8d_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext50_32x4d_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext50_32x4d_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_shufflenet_v2_x1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_shufflenet_v2_x1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_squeezenet1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_squeezenet1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_vgg16_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_vgg16_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_wide_resnet50_2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_wide_resnet50_2_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_bn2d_eltwise_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_bn2d_eltwise_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_bn_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_bn_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_bn_relu_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_bn_relu_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_clamp_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_clamp_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_eltwise_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_eltwise_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_silu_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_silu_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_sum_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_conv2d_sum_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_ensure_tensor_is_rewrapped_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_ensure_tensor_is_rewrapped_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_linear_eltwise_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_linear_eltwise_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_rewrap_tensor_input_to_pytorch_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_rewrap_tensor_input_to_pytorch_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_wildcard_cpu_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_wildcard_cpu_float32, test/test_jit_llga_fuser.py::TestFusionPatternCPU::test_wildcard_unsupported_dtype_cpu_int32, test/test_jit_llga_fuser.py::TestOpCPU::test_add_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_add_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_add_scalar_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_add_scalar_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_addmm_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_addmm_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_avg_pool2d_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_avg_pool2d_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_bn2d_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_bn2d_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_cat_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_cat_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_conv2d_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_conv2d_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_eltwise_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_eltwise_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_identity_binary_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_identity_binary_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_layer_norm_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_layer_norm_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_linear_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_linear_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_max_pool2d_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_max_pool2d_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_mul_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_mul_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_softmax_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_softmax_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_typecheck_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_typecheck_cpu_float32, test/test_jit_llga_fuser.py::TestOpCPU::test_variable_kernel_avg_pool2d_cpu_bfloat16, test/test_jit_llga_fuser.py::TestOpCPU::test_variable_kernel_avg_pool2d_cpu_float32
2025-08-14T23:07:52.8712143Z 
2025-08-14T23:07:58.0548528Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:07:58.0551474Z   import pkg_resources
2025-08-14T23:07:58.2540787Z Running torch_np/test_function_base 1/1 ... [2025-08-14 23:07:58.253539]
2025-08-14T23:07:58.2541692Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:07:58.2549605Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_function_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:07:58.254486]
2025-08-14T23:08:03.4820511Z 
2025-08-14T23:08:03.4822052Z torch_np/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_function_base_1.1_971c7f4d1d0de4d8_.log
2025-08-14T23:08:03.4920332Z Running 1 items in this shard: test/torch_np/test_function_base.py::TestAppend::test_basic
2025-08-14T23:08:03.4925407Z 
2025-08-14T23:08:08.0278225Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:08:08.0281049Z   import pkg_resources
2025-08-14T23:08:08.1514198Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-08-14 23:08:08.150915]
2025-08-14T23:08:08.1515118Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:08:08.1518012Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:08:08.151301]
2025-08-14T23:08:13.9276382Z 
2025-08-14T23:08:13.9278268Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_1f020d354d1dfacc_.log
2025-08-14T23:08:13.9298712Z Running 34 items in this shard: test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_2d, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_bool, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_diag, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_diag2d, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_eye_bounds, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestEye::test_order, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_diag_bounds, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_failure, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_fortran_order, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_matrix, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestDiag::test_vector, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestFliplr::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestFlipud::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_all_outliers, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_asym, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_bad_length_x_len_10_y_len_11, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_bad_length_x_len_20_y_len_19, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_binparameter_combination, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_density, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_empty, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestHistogram2d::test_simple, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_dtype, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_mask_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_dtype, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_ndim2, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_ndim3, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTri::test_tril_triu_with_inf, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTriuIndices::test_triu_indices, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTrilIndicesFrom::test_exceptions, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestTriuIndicesFrom::test_exceptions, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestVander::test_basic, test/torch_np/numpy_tests/lib/test_twodim_base.py::TestVander::test_dtypes
2025-08-14T23:08:13.9322982Z 
2025-08-14T23:08:18.1005133Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:08:18.1008580Z   import pkg_resources
2025-08-14T23:08:18.2338739Z Running torch_np/test_scalars_0D_arrays 1/1 ... [2025-08-14 23:08:18.233384]
2025-08-14T23:08:18.2345537Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:08:18.2347621Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_scalars_0D_arrays.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:08:18.233866]
2025-08-14T23:08:23.2162550Z 
2025-08-14T23:08:23.2164566Z torch_np/test_scalars_0D_arrays 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_scalars_0D_arrays_1.1_10cca4929be85e4c_.log
2025-08-14T23:08:23.2189788Z Running 33 items in this shard: test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_array_scalar_basic_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_conversion_to_int_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_array, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_asarray, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_asarray_int, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_decay_to_py_scalar_int64, test/torch_np/test_scalars_0D_arrays.py::TestArrayScalars::test_scalar_comparisons, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value0, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value1, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value10, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value11, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value4, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value5, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value6, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value7, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value8, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value9, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value_s, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_not_scalar_value_string, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_0D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_1D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_array_2D, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_float32, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_int, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_list, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_list-list, test/torch_np/test_scalars_0D_arrays.py::TestIsScalar::test_is_scalar_literal
2025-08-14T23:08:23.2213704Z 
2025-08-14T23:08:27.8341105Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:08:27.8343930Z   import pkg_resources
2025-08-14T23:08:28.0253756Z Running nn/test_module_hooks 1/1 ... [2025-08-14 23:08:28.023916]
2025-08-14T23:08:28.0254854Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:08:28.0257306Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_module_hooks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:08:28.024379]
2025-08-14T23:08:33.3063705Z 
2025-08-14T23:08:33.3065542Z nn/test_module_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_module_hooks_1.1_f8c70326e5dbcd21_.log
2025-08-14T23:08:33.3107548Z Running 53 items in this shard: test/nn/test_module_hooks.py::TestModuleHooks::test_always_called_forward_hooks, test/nn/test_module_hooks.py::TestModuleHooks::test_bw_hook_warning_for_non_tensor_or_tuple, test/nn/test_module_hooks.py::TestModuleHooks::test_forward_hooks_named_tuple_False, test/nn/test_module_hooks.py::TestModuleHooks::test_forward_hooks_named_tuple_True, test/nn/test_module_hooks.py::TestModuleHooks::test_forward_pre_hooks_named_tuple_False, test/nn/test_module_hooks.py::TestModuleHooks::test_forward_pre_hooks_named_tuple_True, test/nn/test_module_hooks.py::TestModuleHooks::test_full_backward_hooks_named_tuple_False, test/nn/test_module_hooks.py::TestModuleHooks::test_full_backward_hooks_named_tuple_True, test/nn/test_module_hooks.py::TestModuleHooks::test_full_backward_pre_hooks_named_tuple_False, test/nn/test_module_hooks.py::TestModuleHooks::test_full_backward_pre_hooks_named_tuple_True, test/nn/test_module_hooks.py::TestModuleHooks::test_kwarg_hooks, test/nn/test_module_hooks.py::TestModuleHooks::test_mixed_hooks_named_tuple_False, test/nn/test_module_hooks.py::TestModuleHooks::test_mixed_hooks_named_tuple_True, test/nn/test_module_hooks.py::TestModuleHooks::test_remove_kwarg_hooks, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_module_pre_hook_swap_False, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_module_pre_hook_swap_True, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_post_hook_backward_compatibility_swap_False, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_post_hook_backward_compatibility_swap_True, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_post_hook_swap_False, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_post_hook_swap_True, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_pre_hook_swap_False, test/nn/test_module_hooks.py::TestStateDictHooks::test_load_state_dict_pre_hook_swap_True, test/nn/test_module_hooks.py::TestStateDictHooks::test_no_extra_ref_to_module, test/nn/test_module_hooks.py::TestStateDictHooks::test_pickled_hook, test/nn/test_module_hooks.py::TestStateDictHooks::test_register_state_dict_post_hook_private_False, test/nn/test_module_hooks.py::TestStateDictHooks::test_register_state_dict_post_hook_private_True, test/nn/test_module_hooks.py::TestStateDictHooks::test_register_state_dict_pre_hook, test/nn/test_module_hooks.py::TestStateDictHooks::test_register_state_dict_pre_hook_backward_compat, test/nn/test_module_hooks.py::TestStateDictHooks::test_register_state_dict_pre_hook_lazy_module, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_global_and_local_hooks_order, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_backward_global_hook_writeable, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_forward_forward_hook_removable, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_forward_preforward_hook_removable, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_global_forward_preforward_hook_writeable, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_global_hook_invalid_outputs, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_global_hooks, test/nn/test_module_hooks.py::TestModuleGlobalHooks::test_module_global_hooks_with_kwargs, test/nn/test_module_hooks.py::TestModuleHookNN::test_backward_hooks_interaction, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_backward_size, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_backward_writeable, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_buffer_registration, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_cpp, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_extra_input, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_forward_preforward_writable, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_inplace, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_invalid_outputs, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_last_arg_requires_grad, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_no_requires_grad, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_non_full_warning, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_parameter_registration, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_requires_grad, test/nn/test_module_hooks.py::TestModuleHookNN::test_hook_submodule_registration, test/nn/test_module_hooks.py::TestModuleHookNN::test_hooks
2025-08-14T23:08:33.3145000Z 
2025-08-14T23:08:37.7483121Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:08:37.7485988Z   import pkg_resources
2025-08-14T23:08:37.8738188Z Running test_numa_binding 1/1 ... [2025-08-14 23:08:37.873399]
2025-08-14T23:08:37.8738880Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:08:37.8741490Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numa_binding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:08:37.873795]
2025-08-14T23:08:47.4861652Z 
2025-08-14T23:08:47.4863177Z test_numa_binding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numa_binding_1.1_e5ba23975a6806cf_.log
2025-08-14T23:08:47.4923228Z Running 19 items in this shard: test/test_numa_binding.py::NumaBindingTest::test_binds_to_node_0_if_node_stored_as_minus_one, test/test_numa_binding.py::NumaBindingTest::test_callable_entrypoint_basic, test/test_numa_binding.py::NumaBindingTest::test_core_complex_numa_binding_with_extra_l3, test/test_numa_binding.py::NumaBindingTest::test_core_complex_numa_binding_with_fewer_l3_than_gpu, test/test_numa_binding.py::NumaBindingTest::test_core_complex_prefers_caches_with_more_cpus, test/test_numa_binding.py::NumaBindingTest::test_core_complex_tiebreak_prefers_lower_cache_key, test/test_numa_binding.py::NumaBindingTest::test_default_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_exclusive_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_exclusive_raises_if_too_few_physical_cores, test/test_numa_binding.py::NumaBindingTest::test_explicit_numa_options_overrides_default, test/test_numa_binding.py::NumaBindingTest::test_fallback, test/test_numa_binding.py::NumaBindingTest::test_fork_start_method_does_not_call_get_default_numa_options, test/test_numa_binding.py::NumaBindingTest::test_get_range_str_from_ints, test/test_numa_binding.py::NumaBindingTest::test_get_set_of_int_from_ranges_str, test/test_numa_binding.py::NumaBindingTest::test_no_numa_binding_if_numa_options_not_provided, test/test_numa_binding.py::NumaBindingTest::test_node_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_raises_error_if_numactl_unavailable, test/test_numa_binding.py::NumaBindingTest::test_socket_numa_binding_with_multiple_numa_per_socket, test/test_numa_binding.py::NumaBindingTest::test_socket_numa_binding_with_single_numa_per_socket
2025-08-14T23:08:47.4936917Z 
2025-08-14T23:08:52.0021874Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:08:52.0024928Z   import pkg_resources
2025-08-14T23:08:52.1888871Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-08-14 23:08:52.188310]
2025-08-14T23:08:52.1889870Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:08:52.1898293Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:08:52.188792]
2025-08-14T23:08:57.0127418Z 
2025-08-14T23:08:57.0129174Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_19234ab1c69edc47_.log
2025-08-14T23:08:57.0142350Z Running 17 items in this shard: test/torch_np/numpy_tests/core/test_getlimits.py::TestPythonFloat::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestHalf::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestSingle::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestDouble::test_singleton, test/torch_np/numpy_tests/core/test_getlimits.py::TestFinfo::test_basic, test/torch_np/numpy_tests/core/test_getlimits.py::TestFinfo::test_basic_missing, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_basic, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T0, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T1, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T2, test/torch_np/numpy_tests/core/test_getlimits.py::TestIinfo::test_unsigned_max_T3, test/torch_np/numpy_tests/core/test_getlimits.py::TestRepr::test_finfo_repr, test/torch_np/numpy_tests/core/test_getlimits.py::TestRepr::test_iinfo_repr, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_instances, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_known_types, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_plausible_finfo, test/torch_np/numpy_tests/core/test_getlimits.py::TestMisc::test_subnormal_warning
2025-08-14T23:08:57.0154715Z 
2025-08-14T23:09:01.3565017Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:01.3567753Z   import pkg_resources
2025-08-14T23:09:01.5512978Z Running torch_np/test_ndarray_methods 1/1 ... [2025-08-14 23:09:01.550810]
2025-08-14T23:09:01.5513731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:01.5517332Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:01.551400]
2025-08-14T23:09:14.4858321Z 
2025-08-14T23:09:14.4859938Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_7a1f362978997c0a_.log
2025-08-14T23:09:14.5163415Z Running 342 items in this shard: test/torch_np/test_ndarray_methods.py::TestIndexing::test_indexing_simple, test/torch_np/test_ndarray_methods.py::TestIndexing::test_setitem, test/torch_np/test_ndarray_methods.py::TestReshape::test_reshape_function, test/torch_np/test_ndarray_methods.py::TestReshape::test_reshape_method, test/torch_np/test_ndarray_methods.py::TestTranspose::test_transpose_function, test/torch_np/test_ndarray_methods.py::TestTranspose::test_transpose_method, test/torch_np/test_ndarray_methods.py::TestRavel::test_ravel_function, test/torch_np/test_ndarray_methods.py::TestRavel::test_ravel_method, test/torch_np/test_ndarray_methods.py::TestNonzero::test_array_method, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_onedim, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_trivial, test/torch_np/test_ndarray_methods.py::TestNonzero::test_nonzero_twodim, 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test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_vs_ndarray_positional_arr_method_argmax_np_method0, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_np_vs_ndarray_positional_arr_method_argmin_np_method1, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_output_shape_method_argmax, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_output_shape_method_argmin, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_ret_is_out_ndim_0_method_argmax, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_ret_is_out_ndim_0_method_argmin, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_ret_is_out_ndim_1_method_argmax, test/torch_np/test_ndarray_methods.py::TestArgmaxArgminCommon::test_ret_is_out_ndim_1_method_argmin, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data0, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data1, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data10, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data11, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data12, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data13, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data14, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data15, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data16, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data17, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data18, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data19, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data2, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data20, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data21, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data22, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data23, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data24, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data25, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data26, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data27, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data28, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data29, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data3, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data30, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data31, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data32, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data33, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data34, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data35, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data36, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data37, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data38, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data39, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data4, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data40, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data41, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data42, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data43, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data44, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data45, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data46, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data47, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data48, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data49, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data5, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data50, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data51, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data52, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data53, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data54, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data55, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data56, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data57, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data58, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data59, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data6, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data60, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data61, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data62, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data63, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data64, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data65, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data66, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data67, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data68, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data69, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data7, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data70, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data71, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data72, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data73, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data8, test/torch_np/test_ndarray_methods.py::TestArgmax::test_combinations_data9, test/torch_np/test_ndarray_methods.py::TestArgmax::test_maximum_signed_integers, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data0, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data1, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data10, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data11, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data12, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data13, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data14, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data15, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data16, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data17, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data18, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data19, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data2, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data20, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data21, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data22, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data23, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data24, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data25, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data26, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data27, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data28, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data29, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data3, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data30, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data31, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data32, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data33, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data34, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data35, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data36, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data37, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data38, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data39, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data4, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data40, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data41, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data42, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data43, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data44, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data45, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data46, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data47, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data48, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data49, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data5, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data50, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data51, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data52, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data53, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data54, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data55, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data56, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data57, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data58, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data59, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data6, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data60, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data61, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data62, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data63, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data64, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data65, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data66, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data67, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data68, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data69, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data7, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data70, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data71, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data72, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data73, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data8, test/torch_np/test_ndarray_methods.py::TestArgmin::test_combinations_data9, test/torch_np/test_ndarray_methods.py::TestArgmin::test_minimum_signed_integers, test/torch_np/test_ndarray_methods.py::TestAmax::test_basic, test/torch_np/test_ndarray_methods.py::TestAmin::test_basic, test/torch_np/test_ndarray_methods.py::TestContains::test_contains, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_fn, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_ivar, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_method, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_name, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_plain, test/torch_np/test_ndarray_methods.py::TestNoExtraMethods::test_extra_methods_name_rvar, test/torch_np/test_ndarray_methods.py::TestIter::test_iter_1d, test/torch_np/test_ndarray_methods.py::TestIter::test_iter_2d
2025-08-14T23:09:14.5445983Z 
2025-08-14T23:09:18.9367130Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:18.9370368Z   import pkg_resources
2025-08-14T23:09:19.0725290Z Running lazy/test_debug_util 1/1 ... [2025-08-14 23:09:19.072025]
2025-08-14T23:09:19.0729838Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:19.0732141Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:19.072680]
2025-08-14T23:09:24.0052604Z 
2025-08-14T23:09:24.0054247Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_a9cc0aee4591c964_.log
2025-08-14T23:09:24.0055523Z Running 1 items in this shard: test/lazy/test_debug_util.py::DebugUtilTest::test_get_python_frames
2025-08-14T23:09:24.0056024Z 
2025-08-14T23:09:27.7337380Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:27.7340913Z   import pkg_resources
2025-08-14T23:09:27.8636912Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-08-14 23:09:27.863194]
2025-08-14T23:09:27.8640694Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:27.8645690Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:27.863679]
2025-08-14T23:09:33.8089202Z 
2025-08-14T23:09:33.8090407Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_edaf72be4f5f7231_.log
2025-08-14T23:09:33.8135614Z Running 73 items in this shard: test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_argequivalent, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_broadcast, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTakeAlongAxis::test_invalid, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestPutAlongAxis::test_broadcast, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestPutAlongAxis::test_replace_max, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_0d_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_3d, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_axis_insertion, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_axis_insertion_ma, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_scalar_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_simple101, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_tuple_func1d, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyAlongAxis::test_with_iterable_object, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestApplyOverAxes::test_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_axis_out_of_range, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_axis_tuple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_functionality, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestExpandDims::test_repeated_axis, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_high_bound, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_low_bound, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_index_split_simple, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_0_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_cols, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_default, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_rows, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestArraySplit::test_integer_split_2D_rows_greater_max_int32, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSplit::test_equal_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSplit::test_unequal_split, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_1D_arrays, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_2D_arrays, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_generator, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestColumnStack::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_2D_array2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_generator, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDstack::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestHsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestVsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_0D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_1D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_2D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_3D_array, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestDsplit::test_non_iterable, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_basic_2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_axis, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_axis_handling, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_contiguous, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestSqueeze::test_squeeze_type, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a0_shape_b0, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a1_shape_b1, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a2_shape_b2, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a3_shape_b3, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a4_shape_b4, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestKron::test_kron_shape_shape_a5_shape_b5, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_basic, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_empty, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_kroncompare, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestTile::test_tile_one_repetition_on_array_gh4679, test/torch_np/numpy_tests/lib/test_shape_base_.py::TestMayShareMemory::test_basic
2025-08-14T23:09:33.8182875Z 
2025-08-14T23:09:37.6387327Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:37.6390677Z   import pkg_resources
2025-08-14T23:09:37.7678741Z Running torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-08-14 23:09:37.767088]
2025-08-14T23:09:37.7679883Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:37.7685218Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/linalg/test_linalg.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:37.767554]
2025-08-14T23:09:52.8062577Z 
2025-08-14T23:09:52.8063684Z functorch/test_vmap 2/2 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_2.2_13288e5257bbc2cb_.log
2025-08-14T23:09:52.9027425Z Running 1069 items in this shard: test/functorch/test_vmap.py::TestVmapAPI::test_backward_unsupported_interaction, test/functorch/test_vmap.py::TestVmapAPI::test_batched_gradient_basic, test/functorch/test_vmap.py::TestVmapAPI::test_checkpoint, test/functorch/test_vmap.py::TestVmapAPI::test_different_map_dim_size_raises, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_does_not_warn_by_default, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_multiple_returns, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_warns_when_warnings_are_enabled, test/functorch/test_vmap.py::TestVmapAPI::test_fallback_zero_dim, test/functorch/test_vmap.py::TestVmapAPI::test_func_with_no_inputs, test/functorch/test_vmap.py::TestVmapAPI::test_func_with_no_tensors, test/functorch/test_vmap.py::TestVmapAPI::test_functools_partial, test/functorch/test_vmap.py::TestVmapAPI::test_in_dims_wrong_type_err_msg, test/functorch/test_vmap.py::TestVmapAPI::test_inplace_fallback_nary_same_levels, test/functorch/test_vmap.py::TestVmapAPI::test_integer_in_dim_but_not_tensor_input_err_msg, test/functorch/test_vmap.py::TestVmapAPI::test_multiple_outputs, test/functorch/test_vmap.py::TestVmapAPI::test_multiple_outputs2, test/functorch/test_vmap.py::TestVmapAPI::test_nested_out_dims, test/functorch/test_vmap.py::TestVmapAPI::test_nested_with_different_map_dim, test/functorch/test_vmap.py::TestVmapAPI::test_nn_module, test/functorch/test_vmap.py::TestVmapAPI::test_non_default_in_dims_out_dims, test/functorch/test_vmap.py::TestVmapAPI::test_non_tensor_output_raises, test/functorch/test_vmap.py::TestVmapAPI::test_nonzero_out_dims, test/functorch/test_vmap.py::TestVmapAPI::test_out_dims_must_be_int_or_collection_of_int_err_msg, test/functorch/test_vmap.py::TestVmapAPI::test_out_dims_none, test/functorch/test_vmap.py::TestVmapAPI::test_pytree_returns, test/functorch/test_vmap.py::TestVmapAPI::test_pytree_returns_broadcast_nested, test/functorch/test_vmap.py::TestVmapAPI::test_reshape_dim_into, test/functorch/test_vmap.py::TestVmapAPI::test_restore_vmap_pytree_input_output, test/functorch/test_vmap.py::TestVmapAPI::test_restore_vmap_unexpanded_outputs, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_add, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_add_dunder, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_mul, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_mul_dunder, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_pow, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_pow_dunder, test/functorch/test_vmap.py::TestVmapOperators::test_arithmetic_sub, test/functorch/test_vmap.py::TestVmapOperators::test_as_strided, test/functorch/test_vmap.py::TestVmapOperators::test_bmm, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_0_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_0_out_dim_2_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_chunk_vmap_in_dim_1_out_dim_2_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_clamp, test/functorch/test_vmap.py::TestVmapOperators::test_clamp_inplace_variant_clamp_max_, test/functorch/test_vmap.py::TestVmapOperators::test_clamp_inplace_variant_clamp_min_, test/functorch/test_vmap.py::TestVmapOperators::test_clamp_variant_clamp_min, test/functorch/test_vmap.py::TestVmapOperators::test_conj, test/functorch/test_vmap.py::TestVmapOperators::test_conj_bit, test/functorch/test_vmap.py::TestVmapOperators::test_contiguous, test/functorch/test_vmap.py::TestVmapOperators::test_conv2d, test/functorch/test_vmap.py::TestVmapOperators::test_copy_, test/functorch/test_vmap.py::TestVmapOperators::test_diagonal, test/functorch/test_vmap.py::TestVmapOperators::test_imag, test/functorch/test_vmap.py::TestVmapOperators::test_is_contiguous, test/functorch/test_vmap.py::TestVmapOperators::test_mean_dim, test/functorch/test_vmap.py::TestVmapOperators::test_mm, test/functorch/test_vmap.py::TestVmapOperators::test_mv, test/functorch/test_vmap.py::TestVmapOperators::test_narrow, test/functorch/test_vmap.py::TestVmapOperators::test_real, test/functorch/test_vmap.py::TestVmapOperators::test_repeat, test/functorch/test_vmap.py::TestVmapOperators::test_reshape_as, test/functorch/test_vmap.py::TestVmapOperators::test_roll_no_dims, test/functorch/test_vmap.py::TestVmapOperators::test_slogdet, test/functorch/test_vmap.py::TestVmapOperators::test_squeeze, test/functorch/test_vmap.py::TestVmapOperators::test_sum, test/functorch/test_vmap.py::TestVmapOperators::test_sum_dim, test/functorch/test_vmap.py::TestVmapOperators::test_trace, test/functorch/test_vmap.py::TestVmapOperators::test_transpose, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_acos, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_asin, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_ceil, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_cosh, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_digamma, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_exp, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_expm1, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_frac, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_lgamma, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_log1p, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_relu, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_round, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_rsqrt, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_sign, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_sinh, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_tanh, test/functorch/test_vmap.py::TestVmapOperators::test_unary_pointwise_trunc, test/functorch/test_vmap.py::TestVmapOperators::test_unbind, test/functorch/test_vmap.py::TestVmapOperators::test_unsafe_view, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_0_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_0_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_0_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_1_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_1_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_composition_in_dim_1_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_0_out_dim_0_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_0_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_0_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_0_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_1_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_1_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_error_in_dim_1_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_0_out_dim_2_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_1_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_1_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_1_out_dim_2_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_2_out_dim_0_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_2_out_dim_1_randomness_error, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_2_out_dim_1_randomness_same, test/functorch/test_vmap.py::TestVmapOperators::test_vmap_chunksize_in_dim_2_out_dim_2_randomness_error, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_0d_tensor_index_put_inplace_False_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_0d_tensor_index_put_inplace_True_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_False_track_running_stats_False_affine_True_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_False_track_running_stats_True_affine_False_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_False_track_running_stats_True_affine_True_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_True_track_running_stats_False_affine_True_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_batch_norm_training_True_track_running_stats_True_affine_True_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_flatten_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_foo_like_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_group_norm_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_linalg_svd_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_nested_advanced_indexing_cpu, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyCatCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyCubeCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyNMSCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyNonzeroCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpySortAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpySplitCopyCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpySplitCopyWithIntCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_NumpyViewCopyCustomOp_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule___getitem___functorch_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_op_has_batch_rule___radd___cpu_float32, 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test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_spherical_bessel_j0_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_special_zeta_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_split_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_split_with_sizes_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_split_with_sizes_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_sqrt_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_square_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_squeeze_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_squeeze_multiple_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_std_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_std_mean_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_stft_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_sum_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_sum_to_size_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_t_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_take_along_dim_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_take_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tan_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tanh_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tensordot_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_to_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_topk_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_trapezoid_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_trapz_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tril_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_tril_indices_cpu_int64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_triu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unbind_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_uniform_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unique_consecutive_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unsafe_chunk_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unsqueeze_copy_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_unsqueeze_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_var_unbiased_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_view_as_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_view_as_real_cpu_complex64, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_view_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_vsplit_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_vstack_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_exhaustive_zeros_like_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_cholesky_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_cholesky_ex_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_det_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_diagonal_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_eigvalsh_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_householder_product_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_inv_ex_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_ldl_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_lstsq_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_lu_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_lu_factor_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_lu_factor_ex_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_matrix_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_matrix_rank_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_pinv_hermitian_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_pinv_singular_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_qr_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_slogdet_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_solve_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_solve_ex_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_solve_triangular_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_vecdot_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_linalg_failure_1D_input_linalg_vector_norm_cpu_float32, test/functorch/test_vmap.py::TestVmapOperatorsOpInfoCPU::test_vmap_multi_dot_failure_1D_input_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_add_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_binary_cross_entropy_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_diagonal_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_expand_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_index_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_inplace_view_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_log_softmax_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_logsumexp_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_permute_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_randomness_backend0_randomness_error_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_reshape_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_sdpa_backend0_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_sigmoid_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_slice_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_threshold_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_unrelated_output_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_unrelated_output_multiple_grad_cpu, test/functorch/test_vmap.py::TestVmapBatchedGradientCPU::test_vmap_fallback_check, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_grad_cpu, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_jacrev_cpu, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_vjp_cpu, test/functorch/test_vmap.py::TestTransformFailureCPU::test_fails_with_autograd_function_transform_vmap_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_different_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_error_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_same_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_alpha_dropout_randomness_same_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_first_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_last_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_last_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_last_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_none_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_none_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_different_batched_input_none_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_error_batched_input_first_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_error_batched_input_last_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_error_batched_input_last_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_error_batched_input_none_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_error_batched_input_none_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_same_batched_input_first_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_same_batched_input_first_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_False_randomness_same_batched_input_none_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_first_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_first_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_last_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_last_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_different_batched_input_none_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_first_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_first_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_last_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_none_batched_probability_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_error_batched_input_none_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_first_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_last_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_last_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_none_batched_probability_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_bernoulli_in_place_use_generator_True_randomness_same_batched_input_none_batched_probability_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_0_out_dim_1_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_1_out_dim_0_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_1_out_dim_1_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_1_out_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_2_out_dim_0_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_chunk_vmap_in_dim_2_out_dim_1_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_different_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_different_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_randomness_same_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_unbatched_randomness_different_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_dropout_unbatched_randomness_same_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_different_use_generator_False_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_error_use_generator_False_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_error_use_generator_True_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_factory_ops_randomness_same_use_generator_True_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_different_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_error_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_error_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_alpha_dropout_randomness_same_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_first_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_last_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_last_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_different_batched_input_none_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_error_batched_input_last_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_error_batched_input_last_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_error_batched_input_none_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_error_batched_input_none_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_same_batched_input_first_dim_2_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_same_batched_input_last_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_feature_dropout_randomness_same_batched_input_none_dim_3_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_jacfwd_with_random_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_different_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_different_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_error_batched_input_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_like_functions_randomness_same_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_False_randomness_different_batched_call_False_batched_input_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_False_randomness_different_batched_call_False_batched_input_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_multinomial_use_generator_False_randomness_error_batched_call_True_batched_input_last_cpu, 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test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_different_batched_input_last_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_different_batched_input_none_batched_other_last_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_first_batched_other_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_last_batched_other_first_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_error_batched_input_last_batched_other_none_cpu, test/functorch/test_vmap.py::TestRandomnessCPU::test_random_binary_out_of_place_use_generator_True_randomness_same_batched_input_first_batched_other_first_cpu, 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test/functorch/test_vmap.py::TestVmapNestedTensorCPU::test_vmap_fallback_check
2025-08-14T23:09:52.9964582Z 
2025-08-14T23:09:52.9991715Z 
2025-08-14T23:09:52.9993372Z torch_np/numpy_tests/linalg/test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.linalg.test_linalg_1.1_d00244c5e2a467d8_.log
2025-08-14T23:09:53.0179778Z Running 268 items in this shard: test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_0_size_k, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_generalized_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_generalized_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_types_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_types_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_types_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestSolve::test_types_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_generalized_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_generalized_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_types_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_types_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_types_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestInv::test_types_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvals::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvals::test_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvals::test_generalized_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvals::test_generalized_sq_cases, 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test/torch_np/numpy_tests/linalg/test_linalg.py::TestDet::test_types_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestDet::test_types_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestDet::test_zero, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_0_n_0_n_rhs_0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_0_n_4_n_rhs_1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_0_n_4_n_rhs_2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_4_n_0_n_rhs_1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_4_n_0_n_rhs_2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_a_b_m_4_n_2_n_rhs_2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_nonsq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_empty_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_future_rcond, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_incompatible_dims, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_nonsq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestLstsq::test_sq_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalshCases::test_generalized_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalshCases::test_generalized_empty_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalshCases::test_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalshCases::test_empty_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_UPLO, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_invalid, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_types_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_types_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_types_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigvalsh::test_types_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEighCases::test_generalized_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEighCases::test_generalized_empty_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEighCases::test_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEighCases::test_empty_herm_cases, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_UPLO, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_invalid, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_types_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_types_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_types_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestEigh::test_types_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNorm_NonSystematic::test_intmin, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_axis, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_bad_args, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_keepdims, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_matrix_2x2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_matrix_3x3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_matrix_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_matrix_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_vector, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormDouble::test_vector_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_axis, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_bad_args, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_keepdims, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_matrix_2x2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_matrix_3x3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_matrix_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_matrix_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_vector, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormSingle::test_vector_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_axis, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_bad_args, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_keepdims, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_matrix_2x2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_matrix_3x3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_matrix_empty, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_matrix_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_vector, test/torch_np/numpy_tests/linalg/test_linalg.py::TestNormInt64::test_vector_return_type, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMatrixRank::test_matrix_rank, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMatrixRank::test_reduced_rank, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMatrixRank::test_symmetric_rank, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_mode_all_but_economic, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_mode_raw, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_qr_empty_m_0_n_0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_qr_empty_m_0_n_3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_qr_empty_m_3_n_0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size0_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size0_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size0_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size0_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size1_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size1_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size1_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size1_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size2_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size2_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size2_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size0_outer_size2_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size0_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size0_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size0_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size0_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size1_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size1_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size1_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size1_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size2_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size2_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size2_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size1_outer_size2_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size0_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size0_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size0_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size0_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size1_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size1_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size1_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size1_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size2_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size2_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size2_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size2_outer_size2_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size0_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size0_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size0_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size0_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size1_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size1_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size1_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size1_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size2_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size2_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size2_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size3_outer_size2_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size0_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size0_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size0_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size0_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size1_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size1_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size1_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size1_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size2_dt0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size2_dt1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size2_dt2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestQR::test_stacked_inputs_size4_outer_size2_dt3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_0_size, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape0_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape0_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape0_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape0_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape1_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape1_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape1_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape1_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape2_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape2_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape2_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape2_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape3_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape3_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape3_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape3_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape4_dtype0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape4_dtype1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape4_dtype2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestCholesky::test_basic_property_shape4_dtype3, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc::test_byteorder_check, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc::test_generalized_raise_multiloop, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc::test_sdot_bug_8577, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc::test_xerbla_override, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_basic_function_with_dynamic_programming_optimization, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_basic_function_with_three_arguments, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_basic_function_with_two_arguments, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_dynamic_programming_logic, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_dynamic_programming_optimization_and_out, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_three_arguments_and_out, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_too_few_input_arrays, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_two_arguments_and_out, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_vector_as_first_and_last_argument, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_vector_as_first_argument, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMultiDot::test_vector_as_last_argument, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_non_square_handling_arr0_ind_2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_non_square_handling_arr1_ind_1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_tensorinv_ind_limit_ind_-2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_tensorinv_ind_limit_ind_0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_tensorinv_result, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_tensorinv_shape_shape0_ind_2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorinv::test_tensorinv_shape_shape1_ind_1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorsolve::test_non_square_handling_a0_axes0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorsolve::test_non_square_handling_a1_axes1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorsolve::test_tensorsolve_result_shape0, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorsolve::test_tensorsolve_result_shape1, test/torch_np/numpy_tests/linalg/test_linalg.py::TestTensorsolve::test_tensorsolve_result_shape2, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc2::test_blas64_dot, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc2::test_blas64_geqrf_lwork_smoketest, test/torch_np/numpy_tests/linalg/test_linalg.py::TestMisc2::test_unsupported_commontype
2025-08-14T23:09:53.0363160Z 
2025-08-14T23:09:56.3190904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:56.3193879Z   import pkg_resources
2025-08-14T23:09:56.4464129Z Running test_sparse_csr 1/1 ... [2025-08-14 23:09:56.445968]
2025-08-14T23:09:56.4464991Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:56.4466977Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_csr.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:56.446358]
2025-08-14T23:09:56.4532330Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:09:56.4535086Z   import pkg_resources
2025-08-14T23:09:56.5856196Z Running test_view_ops 1/1 ... [2025-08-14 23:09:56.585189]
2025-08-14T23:09:56.5856869Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:09:56.5860475Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_view_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:09:56.585645]
2025-08-14T23:10:17.9211444Z 
2025-08-14T23:10:17.9214693Z test_dataloader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dataloader_1.1_ce21ebafed048348_.log
2025-08-14T23:10:17.9281273Z Running 186 items in this shard: test/test_dataloader.py::TestDatasetRandomSplit::test_incomplete_fractional_splits, test/test_dataloader.py::TestDatasetRandomSplit::test_lengths_must_equal_dataset_size, test/test_dataloader.py::TestDatasetRandomSplit::test_slicing_of_subset_of_dataset, test/test_dataloader.py::TestDatasetRandomSplit::test_slicing_of_subset_of_subset, test/test_dataloader.py::TestDatasetRandomSplit::test_splits_are_mutually_exclusive, test/test_dataloader.py::TestDatasetRandomSplit::test_splits_generator, test/test_dataloader.py::TestDatasetRandomSplit::test_splits_have_correct_size, test/test_dataloader.py::TestDatasetRandomSplit::test_splits_indexing_type, test/test_dataloader.py::TestDatasetRandomSplit::test_splits_reproducibility, test/test_dataloader.py::TestTensorDataset::test_getitem, test/test_dataloader.py::TestTensorDataset::test_getitem_1d, test/test_dataloader.py::TestTensorDataset::test_len, test/test_dataloader.py::TestTensorDataset::test_many_tensors, test/test_dataloader.py::TestTensorDataset::test_single_tensor, test/test_dataloader.py::TestStackDataset::test_empty, test/test_dataloader.py::TestStackDataset::test_getitem, test/test_dataloader.py::TestStackDataset::test_getitems, test/test_dataloader.py::TestStackDataset::test_getitems_raises_index_error, test/test_dataloader.py::TestStackDataset::test_getitems_value_error, test/test_dataloader.py::TestStackDataset::test_len, test/test_dataloader.py::TestStackDataset::test_mixed, test/test_dataloader.py::TestStackDataset::test_single, test/test_dataloader.py::TestStackDataset::test_size_mismatch, test/test_dataloader.py::TestConcatDataset::test_add_dataset, test/test_dataloader.py::TestConcatDataset::test_concat_raises_index_error, test/test_dataloader.py::TestConcatDataset::test_concat_two_non_singletons, test/test_dataloader.py::TestConcatDataset::test_concat_two_non_singletons_with_empty, test/test_dataloader.py::TestConcatDataset::test_concat_two_singletons, test/test_dataloader.py::TestConcatDataset::test_iterable_dataset_err, test/test_dataloader.py::TestDataLoader::test_batch_sampler, test/test_dataloader.py::TestDataLoader::test_builtin_collection_conversion, test/test_dataloader.py::TestDataLoader::test_bulk_loading_nobatch, test/test_dataloader.py::TestDataLoader::test_chain_iterable_style_dataset, test/test_dataloader.py::TestDataLoader::test_default_collate_bad_numpy_types, test/test_dataloader.py::TestDataLoader::test_default_collate_bad_sequence_type, test/test_dataloader.py::TestDataLoader::test_default_collate_dtype, test/test_dataloader.py::TestDataLoader::test_default_collate_mapping_keep_type, test/test_dataloader.py::TestDataLoader::test_default_collate_numpy_memmap, test/test_dataloader.py::TestDataLoader::test_default_collate_sequence_dont_keep_type, test/test_dataloader.py::TestDataLoader::test_default_collate_sequence_keep_type, test/test_dataloader.py::TestDataLoader::test_default_collate_shared_tensor, test/test_dataloader.py::TestDataLoader::test_default_convert_mapping_keep_type, test/test_dataloader.py::TestDataLoader::test_default_convert_sequence_dont_keep_type, test/test_dataloader.py::TestDataLoader::test_default_convert_sequence_keep_type, test/test_dataloader.py::TestDataLoader::test_distributed_sampler_invalid_rank, test/test_dataloader.py::TestDataLoader::test_duplicating_data_with_drop_last, test/test_dataloader.py::TestDataLoader::test_error, test/test_dataloader.py::TestDataLoader::test_error_in_init, test/test_dataloader.py::TestDataLoader::test_error_workers, test/test_dataloader.py::TestDataLoader::test_excessive_thread_creation_warning, test/test_dataloader.py::TestDataLoader::test_fd_limit_exceeded, test/test_dataloader.py::TestDataLoader::test_get_worker_info, test/test_dataloader.py::TestDataLoader::test_growing_dataset, test/test_dataloader.py::TestDataLoader::test_invalid_assign_after_init, test/test_dataloader.py::TestDataLoader::test_invalid_ctor_args_combinations, test/test_dataloader.py::TestDataLoader::test_iterable_style_dataset, test/test_dataloader.py::TestDataLoader::test_iterabledataset_len, test/test_dataloader.py::TestDataLoader::test_large_sampler_indices, test/test_dataloader.py::TestDataLoader::test_len, test/test_dataloader.py::TestDataLoader::test_multi_epochs_reproducibility, test/test_dataloader.py::TestDataLoader::test_multiple_dataloaders, test/test_dataloader.py::TestDataLoader::test_multiprocessing_contexts, test/test_dataloader.py::TestDataLoader::test_multiprocessing_iterdatapipe, test/test_dataloader.py::TestDataLoader::test_multiprocessing_iterdatapipe_with_dill, test/test_dataloader.py::TestDataLoader::test_no_segfault, test/test_dataloader.py::TestDataLoader::test_numpy, test/test_dataloader.py::TestDataLoader::test_numpy_gen_state, test/test_dataloader.py::TestDataLoader::test_numpy_scalars, test/test_dataloader.py::TestDataLoader::test_partial_workers, test/test_dataloader.py::TestDataLoader::test_proper_exit, test/test_dataloader.py::TestDataLoader::test_random_sampler, test/test_dataloader.py::TestDataLoader::test_random_sampler_len_with_replacement, test/test_dataloader.py::TestDataLoader::test_random_sampler_len_without_replacement, test/test_dataloader.py::TestDataLoader::test_sampler, test/test_dataloader.py::TestDataLoader::test_sampler_reproducibility, test/test_dataloader.py::TestDataLoader::test_segfault, test/test_dataloader.py::TestDataLoader::test_seqential_batch_workers, test/test_dataloader.py::TestDataLoader::test_seqential_batch_workers_prefetch, test/test_dataloader.py::TestDataLoader::test_sequential_batch, test/test_dataloader.py::TestDataLoader::test_sequential_nonbatch, test/test_dataloader.py::TestDataLoader::test_sequential_pin_memory, test/test_dataloader.py::TestDataLoader::test_sequential_workers, test/test_dataloader.py::TestDataLoader::test_shuffle, test/test_dataloader.py::TestDataLoader::test_shuffle_batch, test/test_dataloader.py::TestDataLoader::test_shuffle_batch_none, test/test_dataloader.py::TestDataLoader::test_shuffle_batch_workers, test/test_dataloader.py::TestDataLoader::test_shuffle_batch_workers_prefetch, test/test_dataloader.py::TestDataLoader::test_shuffle_pin_memory, test/test_dataloader.py::TestDataLoader::test_shuffle_reproducibility, test/test_dataloader.py::TestDataLoader::test_shuffle_workers, test/test_dataloader.py::TestDataLoader::test_timeout, test/test_dataloader.py::TestDataLoader::test_typing, test/test_dataloader.py::TestDataLoader::test_worker_init_fn, test/test_dataloader.py::TestDataLoader::test_worker_seed, test/test_dataloader.py::TestDataLoader::test_worker_seed_reproducibility, test/test_dataloader.py::IntegrationTestDataLoaderDataPipe::test_shuffler_iterdatapipe, test/test_dataloader.py::TestStringDataLoader::test_shuffle_pin_memory, test/test_dataloader.py::TestDictDataLoader::test_pin_memory, test/test_dataloader.py::TestDictDataLoader::test_pin_memory_device, test/test_dataloader.py::TestDictDataLoader::test_pin_memory_no_cuda, test/test_dataloader.py::TestDictDataLoader::test_pin_memory_with_only_device, test/test_dataloader.py::TestDictDataLoader::test_sequential_batch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_batch_sampler, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_builtin_collection_conversion, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_bulk_loading_nobatch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_chain_iterable_style_dataset, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_dataset_not_reset, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_bad_numpy_types, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_bad_sequence_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_dtype, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_mapping_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_numpy_memmap, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_sequence_dont_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_sequence_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_collate_shared_tensor, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_convert_mapping_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_convert_sequence_dont_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_default_convert_sequence_keep_type, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_distributed_sampler_invalid_rank, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_duplicating_data_with_drop_last, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_early_exit, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_error, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_error_in_init, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_error_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_excessive_thread_creation_warning, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_fd_limit_exceeded, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_get_worker_info, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_growing_dataset, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_invalid_assign_after_init, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_invalid_ctor_args_combinations, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_iterable_style_dataset, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_iterabledataset_len, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_large_sampler_indices, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_len, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_multi_epochs_reproducibility, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_multiple_dataloaders, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_multiprocessing_contexts, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_multiprocessing_iterdatapipe, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_multiprocessing_iterdatapipe_with_dill, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_no_segfault, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_numpy, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_numpy_gen_state, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_numpy_scalars, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_partial_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_proper_exit, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_random_sampler, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_random_sampler_len_with_replacement, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_random_sampler_len_without_replacement, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sampler, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sampler_reproducibility, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_segfault, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_seqential_batch_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_seqential_batch_workers_prefetch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sequential_batch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sequential_nonbatch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sequential_pin_memory, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_sequential_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_batch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_batch_none, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_batch_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_batch_workers_prefetch, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_pin_memory, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_reproducibility, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_shuffle_workers, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_timeout, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_typing, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_worker_init_fn, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_worker_seed, test/test_dataloader.py::TestDataLoaderPersistentWorkers::test_worker_seed_reproducibility, test/test_dataloader.py::TestNamedTupleDataLoader::test_dataloader_with_namedtuple, test/test_dataloader.py::TestCustomPinFn::test_custom_batch_pin, test/test_dataloader.py::TestCustomPinFn::test_custom_batch_pin_worker, test/test_dataloader.py::TestIndividualWorkerQueue::test_ind_worker_queue, test/test_dataloader.py::TestSetAffinity::test_set_affinity_in_worker_init, test/test_dataloader.py::TestConvAfterFork::test_conv_after_fork, test/test_dataloader.py::TestOutOfOrderDataLoader::test_in_order_index_ds, test/test_dataloader.py::TestOutOfOrderDataLoader::test_in_order_iterable_ds, test/test_dataloader.py::TestOutOfOrderDataLoader::test_out_of_order_index_ds, test/test_dataloader.py::TestOutOfOrderDataLoader::test_out_of_order_iterable_ds, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_nested_tensor_multiprocessing_context_fork_cpu, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_nested_tensor_multiprocessing_context_forkserver_cpu, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_nested_tensor_multiprocessing_context_spawn_cpu, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_sparse_tensor_multiprocessing_context_fork_cpu, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_sparse_tensor_multiprocessing_context_forkserver_cpu, test/test_dataloader.py::TestDataLoaderDeviceTypeCPU::test_sparse_tensor_multiprocessing_context_spawn_cpu
2025-08-14T23:10:17.9344230Z 
2025-08-14T23:10:19.8856286Z 
2025-08-14T23:10:19.8857362Z test_view_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_view_ops_1.1_1866688d04bc324a_.log
2025-08-14T23:10:19.8993198Z Running 442 items in this shard: test/test_view_ops.py::TestViewOpsCPU::test_T_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_advanced_indexing_assignment_cpu, test/test_view_ops.py::TestViewOpsCPU::test_advanced_indexing_nonview_cpu, test/test_view_ops.py::TestViewOpsCPU::test_as_strided_gradients_cpu, test/test_view_ops.py::TestViewOpsCPU::test_as_strided_inplace_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_as_strided_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_basic_indexing_ellipses_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_basic_indexing_newaxis_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_basic_indexing_slice_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_chunk_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_conj_imag_view_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_conj_imag_view_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_conj_self_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_conj_view_with_shared_memory_cpu, test/test_view_ops.py::TestViewOpsCPU::test_contiguous_nonview_cpu, test/test_view_ops.py::TestViewOpsCPU::test_contiguous_self_cpu, test/test_view_ops.py::TestViewOpsCPU::test_diagonal_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_expand_as_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_expand_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_flatten_nonview_cpu, test/test_view_ops.py::TestViewOpsCPU::test_flatten_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_imag_noncomplex_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_movedim_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_narrow_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_permute_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_real_imag_view_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_real_imag_view_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_reshape_as_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_reshape_nonview_cpu, test/test_view_ops.py::TestViewOpsCPU::test_reshape_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_select_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_bool, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_complex128, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_complex64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_float16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_float32, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_float64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_int16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_int32, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_int64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_int8, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex128_uint8, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_bool, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_complex128, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_complex64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_float16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_float32, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_float64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_int16, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_int32, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_int64, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_int8, test/test_view_ops.py::TestViewOpsCPU::test_set_real_imag_cpu_complex64_uint8, test/test_view_ops.py::TestViewOpsCPU::test_split_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_squeeze_inplace_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_squeeze_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_t_inplace_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_t_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_transpose_inplace_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_transpose_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_unbind_cpu, test/test_view_ops.py::TestViewOpsCPU::test_unbind_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_unfold_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_unsqueeze_inplace_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_unsqueeze_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_as_complex_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_as_real_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_as_real_cpu_complex32, test/test_view_ops.py::TestViewOpsCPU::test_view_as_real_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_as_view_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_copy_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_copy_out_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_copy_output_contiguous_cpu, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_new_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_dtype_upsize_errors_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_dsplit_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_hsplit_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_split_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_bfloat16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_bool, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_complex128, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_complex64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_float16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_float32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_float64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_int16, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_int32, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_int64, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_int8, test/test_view_ops.py::TestViewOpsCPU::test_view_tensor_vsplit_cpu_uint8, test/test_view_ops.py::TestViewOpsCPU::test_view_view_cpu, test/test_view_ops.py::TestViewOpsLAZY::test_T_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_advanced_indexing_assignment_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_advanced_indexing_nonview_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_as_strided_gradients_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_as_strided_inplace_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_as_strided_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_basic_indexing_ellipses_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_basic_indexing_newaxis_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_basic_indexing_slice_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_chunk_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_conj_imag_view_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_conj_imag_view_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_conj_self_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_conj_view_with_shared_memory_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_contiguous_nonview_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_contiguous_self_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_diagonal_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_expand_as_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_expand_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_flatten_nonview_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_flatten_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_imag_noncomplex_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_movedim_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_narrow_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_permute_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_real_imag_view_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_real_imag_view_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_reshape_as_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_reshape_nonview_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_reshape_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_select_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_bool, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_float16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_float32, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_float64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_int16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_int32, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_int64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_int8, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex128_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_bool, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_float16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_float32, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_float64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_int16, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_int32, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_int64, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_int8, test/test_view_ops.py::TestViewOpsLAZY::test_set_real_imag_lazy_complex64_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_split_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_squeeze_inplace_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_squeeze_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_t_inplace_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_t_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_transpose_inplace_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_transpose_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_unbind_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_unbind_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_unfold_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_unsqueeze_inplace_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_unsqueeze_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_as_complex_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_as_real_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_as_real_lazy_complex32, test/test_view_ops.py::TestViewOpsLAZY::test_view_as_real_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_as_view_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_copy_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_copy_out_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_copy_output_contiguous_lazy, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_new_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_dtype_upsize_errors_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_dsplit_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_hsplit_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_split_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_bfloat16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_bool, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_complex128, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_complex64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_float16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_float32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_float64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_int16, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_int32, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_int64, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_int8, test/test_view_ops.py::TestViewOpsLAZY::test_view_tensor_vsplit_lazy_uint8, test/test_view_ops.py::TestViewOpsLAZY::test_view_view_lazy, test/test_view_ops.py::TestOldViewOpsCPU::test_T_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_as_strided_overflow_storage_offset_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_atleast_gradient_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_big_transpose_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_shapes_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_tensors_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_broadcast_to_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_chunk_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_conj_neg_view_numpy_error_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_contiguous_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_crow_col_indices_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_empty_reshape_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_expand_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_flatten_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_memory_format_resize__cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_memory_format_resize_as_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_narrow_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_narrow_tensor_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_python_types_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_ravel_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_bfloat16, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_reshape_view_semantics_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_resize_all_dtypes_and_devices_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_resize_as_all_dtypes_and_devices_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_resize_as_preserves_strides_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_resize_overflow_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_split_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_t_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_errors_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_indices_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_tensor_split_sections_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_invalid_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_invalid_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_invalid_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_vs_numpy_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_vs_numpy_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_transpose_vs_numpy_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_bfloat16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_bfloat16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_bool, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_complex128, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_complex64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_float16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_float32, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_float64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_int16, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_int32, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_int64, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_int8, test/test_view_ops.py::TestOldViewOpsCPU::test_transposes_errors_cpu_uint8, test/test_view_ops.py::TestOldViewOpsCPU::test_unsqueeze_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_view_all_dtypes_and_devices_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_view_cpu, test/test_view_ops.py::TestOldViewOpsCPU::test_view_empty_cpu
2025-08-14T23:10:19.9122143Z 
2025-08-14T23:10:21.2023486Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:21.2025183Z   import pkg_resources
2025-08-14T23:10:21.3286104Z Running test_accelerator 1/1 ... [2025-08-14 23:10:21.328262]
2025-08-14T23:10:21.3286567Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:21.3289902Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_accelerator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:21.328654]
2025-08-14T23:10:23.1965982Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:23.1968732Z   import pkg_resources
2025-08-14T23:10:23.3233827Z Running profiler/test_memory_profiler 1/1 ... [2025-08-14 23:10:23.322979]
2025-08-14T23:10:23.3234690Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:23.3236616Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_memory_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:23.323326]
2025-08-14T23:10:24.5321120Z 
2025-08-14T23:10:24.5322049Z test_accelerator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_accelerator_1.1_751a1685e45e64d2_.log
2025-08-14T23:10:24.5322716Z 
2025-08-14T23:10:27.7910065Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:27.7913040Z   import pkg_resources
2025-08-14T23:10:27.9156986Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-08-14 23:10:27.915301]
2025-08-14T23:10:27.9158023Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:27.9159894Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:27.915682]
2025-08-14T23:10:31.7527927Z 
2025-08-14T23:10:31.7529505Z profiler/test_memory_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_memory_profiler_1.1_687778699cb91dd8_.log
2025-08-14T23:10:31.7555379Z Running 33 items in this shard: test/profiler/test_memory_profiler.py::TestMemoryProfiler::test_config_check, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_module, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_module_and_optimizer, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_low_level, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_complicated, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_non_op_allocations, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_simple, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_simple_backward, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_simple_inplace, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_stacked, test/profiler/test_memory_profiler.py::TestDataFlow::test_data_flow_graph_with_annotations, test/profiler/test_memory_profiler.py::TestDataFlow::test_match_schemas, test/profiler/test_memory_profiler.py::TestDataFlow::test_match_schemas_backward, test/profiler/test_memory_profiler.py::TestDataFlow::test_match_schemas_tensorlist, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_sequential_fwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_sequential_fwd_bwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_fwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_fwd_bwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_fwd_bwd_step, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_module_fwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_module_fwd_bwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_categories_e2e_simple_module_fwd_bwd_step, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_inputs_fwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_inputs_fwd_bwd, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_inputs_fwd_lazy, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_lazily_initialized, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_manual_optimizer_step, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_memory_timeline, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_parameters_and_gradients, test/profiler/test_memory_profiler.py::TestMemoryProfilerE2E::test_parameters_and_gradients_set_to_none, test/profiler/test_memory_profiler.py::TestMemoryProfilerTimelineCPU::test_memory_timeline_no_id_cpu
2025-08-14T23:10:31.7579017Z 
2025-08-14T23:10:35.3970060Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:35.3972421Z   import pkg_resources
2025-08-14T23:10:35.5292235Z Running test_function_schema 1/1 ... [2025-08-14 23:10:35.528814]
2025-08-14T23:10:35.5292977Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:35.5295796Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_function_schema.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:35.529243]
2025-08-14T23:10:36.1151060Z 
2025-08-14T23:10:36.1152943Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_387dafc8c7c4b6cf_.log
2025-08-14T23:10:36.1211350Z Running 79 items in this shard: test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTShift::test_fft_n, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_all_1d_norm_preserving, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_axes_op3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_dtypes_dtype2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype0_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype1_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype2_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_F_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft1, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft3, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft4, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fft_with_order_dtype3_order_non-contiguous_fft5, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_fftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_hfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_identity, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm0, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_backward, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_forward, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifft_norm_ortho, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ifftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_ihfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_irfftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfft2, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFT1D::test_rfftn, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_fft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_ifft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_irfft, test/torch_np/numpy_tests/fft/test_pocketfft.py::TestFFTThreadSafe::test_rfft
2025-08-14T23:10:36.1267257Z 
2025-08-14T23:10:39.2993371Z 
2025-08-14T23:10:39.2994469Z test_function_schema 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_function_schema_1.1_ea62329fa9bae93a_.log
2025-08-14T23:10:39.3001958Z Running 15 items in this shard: test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_arguments, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_outputs, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_structure, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_with_smart_serialization, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_real_use_case, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_with_out, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_without_out, test/test_function_schema.py::TestFunctionSchema::test_hash_schema, test/test_function_schema.py::TestFunctionSchema::test_out_schema, test/test_function_schema.py::TestFunctionSchema::test_schema_error, test/test_function_schema.py::TestFunctionSchema::test_serialize_and_deserialize, test/test_function_schema.py::TestFunctionSchema::test_string_optional_parameter_default_value, test/test_function_schema.py::TestFunctionSchema::test_sym_int_argument_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_list_alias_annotation_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_option_arguments_properly_parsed
2025-08-14T23:10:39.3008495Z 
2025-08-14T23:10:39.4157150Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:39.4158688Z   import pkg_resources
2025-08-14T23:10:39.5450004Z Running torch_np/numpy_tests/lib/test_index_tricks 1/1 ... [2025-08-14 23:10:39.544623]
2025-08-14T23:10:39.5450609Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:39.5453142Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_index_tricks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:39.545037]
2025-08-14T23:10:42.5210689Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:42.5212243Z   import pkg_resources
2025-08-14T23:10:42.6498493Z Running test_scatter_gather_ops 1/1 ... [2025-08-14 23:10:42.649065]
2025-08-14T23:10:42.6499369Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:42.6501528Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_scatter_gather_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:42.649496]
2025-08-14T23:10:43.9167027Z 
2025-08-14T23:10:43.9168792Z torch_np/numpy_tests/lib/test_index_tricks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_index_tricks_1.1_22dd6628cd1ca88a_.log
2025-08-14T23:10:43.9204358Z Running 47 items in this shard: test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_0d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_big_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_clipmodes, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_dtypes, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_clip, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_raise, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_ravel_mode_wrap, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_array_unravel, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_empty_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestRavelUnravelIndex::test_writeability, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_longdouble, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_npcomplexfloating, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_accepts_npfloating, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_linspace_equivalence, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_mgrid_size_none_handling_start0_stop_10_step0_expected0, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_mgrid_size_none_handling_start_-10_stop_20_step1_expected1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_nd, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestGrid::test_sparse, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_0d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_1d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_2d, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_complex_step, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_mixed_type, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestConcatenator::test_more_mixed_type, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestNdenumerate::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIndexExpression::test_regression_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIndexExpression::test_simple_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_1d_only, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_bool, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_regression_1, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_repeated_input, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestIx_::test_shape_and_dtype, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestC::test_c_, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_basic, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_hetero_shape_handling, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_low_dim_handling, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_operate_4d_array, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_tall_matrix, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_tall_matrix_wrap, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestFillDiagonal::test_wide_matrix, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndices::test_diag_indices, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_diag_indices_from, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_error_shape_mismatch, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestDiagIndicesFrom::test_error_small_input, test/torch_np/numpy_tests/lib/test_index_tricks.py::TestNdIndex::test_ndindex
2025-08-14T23:10:43.9238164Z 
2025-08-14T23:10:48.8273625Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:10:48.8276814Z   import pkg_resources
2025-08-14T23:10:49.1052914Z Running test_serialization 1/1 ... [2025-08-14 23:10:49.104766]
2025-08-14T23:10:49.1053764Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:10:49.1060324Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_serialization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:10:49.105345]
2025-08-14T23:10:57.9586946Z 
2025-08-14T23:10:57.9588461Z test_scatter_gather_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_scatter_gather_ops_1.1_6848bcb0969dd95a_.log
2025-08-14T23:10:57.9624921Z Running 84 items in this shard: test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_backward_with_empty_index_tensor_sparse_grad_False_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_backward_with_empty_index_tensor_sparse_grad_False_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_backward_with_empty_index_tensor_sparse_grad_True_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_backward_with_empty_index_tensor_sparse_grad_True_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_bool_cpu_bool, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_expanded_index_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_expanded_index_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_expanded_index_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_large_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_gather_large_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__reductions_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__reductions_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__reductions_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__scalar_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__scalar_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter__scalar_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_add__cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_add__cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_add__cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_add_broadcasted_index_deterministic_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_add_mult_index_base_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_expanded_index_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_expanded_index_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_expanded_index_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_expanded_index_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_bool, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_int16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_int32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_int64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amax_cpu_uint8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_bool, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_int16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_int32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_int64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_amin_cpu_uint8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_complex128, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_int16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_int32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_int64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_mean_cpu_uint8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_bool, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_complex128, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_int16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_int32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_int64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_prod_cpu_uint8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_bfloat16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_complex128, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_complex64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_float16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_float32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_float64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_int16, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_int32, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_int64, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_int8, test/test_scatter_gather_ops.py::TestScatterGatherCPU::test_scatter_reduce_sum_cpu_uint8
2025-08-14T23:10:57.9657649Z 
2025-08-14T23:11:01.6176218Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:11:01.6179060Z   import pkg_resources
2025-08-14T23:11:01.7458940Z Running torch_np/numpy_tests/core/test_dlpack 1/1 ... [2025-08-14 23:11:01.745448]
2025-08-14T23:11:01.7460032Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:11:01.7462512Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dlpack.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:11:01.745826]
2025-08-14T23:11:05.5675149Z 
2025-08-14T23:11:05.5676956Z torch_np/numpy_tests/core/test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dlpack_1.1_527a22094d8f9278_.log
2025-08-14T23:11:05.5696587Z Running 53 items in this shard: test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dlpack_destructor_exception, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dlpack_device, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype1, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype2, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype3, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype4, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype5, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype6, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype7, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype8, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dtype_passthrough_dtype9, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dunder_dlpack_refcount, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_dunder_dlpack_stream, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_from_dlpack_refcount, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_from_torch, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_1, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_10, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_11, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_12, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_13, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_14, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_15, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_16, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_17, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_18, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_19, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_2, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_20, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_21, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_22, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_23, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_24, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_25, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_26, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_27, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_28, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_29, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_3, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_30, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_31, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_32, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_4, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_5, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_6, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_7, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_8, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_higher_dims_ndim_9, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_ndim0, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_non_contiguous, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_readonly, test/torch_np/numpy_tests/core/test_dlpack.py::TestDLPack::test_to_torch
2025-08-14T23:11:05.5715374Z 
2025-08-14T23:11:08.9906415Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:11:08.9909532Z   import pkg_resources
2025-08-14T23:11:09.1158602Z Running test_xnnpack_integration 1/1 ... [2025-08-14 23:11:09.115485]
2025-08-14T23:11:09.1159478Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:11:09.1162119Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_xnnpack_integration.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:11:09.115864]
2025-08-14T23:11:22.5069309Z 
2025-08-14T23:11:22.5070828Z test_xnnpack_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_xnnpack_integration_1.1_85f399a45e9f7849_.log
2025-08-14T23:11:22.5080498Z Running 12 items in this shard: test/test_xnnpack_integration.py::TestXNNPACKOps::test_conv2d, test/test_xnnpack_integration.py::TestXNNPACKOps::test_conv2d_transpose, test/test_xnnpack_integration.py::TestXNNPACKOps::test_linear, test/test_xnnpack_integration.py::TestXNNPACKOps::test_linear_1d_input, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_combined_model, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_conv2d, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_conv2d_transpose, test/test_xnnpack_integration.py::TestXNNPACKSerDes::test_linear, test/test_xnnpack_integration.py::TestXNNPACKRewritePass::test_decomposed_linear, test/test_xnnpack_integration.py::TestXNNPACKRewritePass::test_linear, test/test_xnnpack_integration.py::TestXNNPACKConv1dTransformPass::test_conv1d_basic, test/test_xnnpack_integration.py::TestXNNPACKConv1dTransformPass::test_conv1d_with_relu_fc
2025-08-14T23:11:22.5088730Z 
2025-08-14T23:11:25.3554813Z 
2025-08-14T23:11:25.3556155Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_8b4193ef044de846_.log
2025-08-14T23:11:25.3642105Z Running 203 items in this shard: test/test_serialization.py::TestOldSerialization::test_debug_set_in_ci, test/test_serialization.py::TestOldSerialization::test_load_error_msg, test/test_serialization.py::TestOldSerialization::test_load_nonexistent_device, test/test_serialization.py::TestOldSerialization::test_load_python2_unicode_module, test/test_serialization.py::TestOldSerialization::test_load_unicode_error_msg, test/test_serialization.py::TestOldSerialization::test_pickle_module, test/test_serialization.py::TestOldSerialization::test_safe_load_basic_types, test/test_serialization.py::TestOldSerialization::test_save_different_dtype_error, test/test_serialization.py::TestOldSerialization::test_save_different_dtype_unallocated, test/test_serialization.py::TestOldSerialization::test_serialization, test/test_serialization.py::TestOldSerialization::test_serialization_backwards_compat, test/test_serialization.py::TestOldSerialization::test_serialization_backwards_compat_safe, test/test_serialization.py::TestOldSerialization::test_serialization_container, test/test_serialization.py::TestOldSerialization::test_serialization_container_filelike, test/test_serialization.py::TestOldSerialization::test_serialization_dill, test/test_serialization.py::TestOldSerialization::test_serialization_dill_version_not_supported, test/test_serialization.py::TestOldSerialization::test_serialization_fake_zip, test/test_serialization.py::TestOldSerialization::test_serialization_filelike, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_api_requirements, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_exceptions, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_missing_attrs, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_stress, test/test_serialization.py::TestOldSerialization::test_serialization_filelike_uses_readinto, test/test_serialization.py::TestOldSerialization::test_serialization_gzip, test/test_serialization.py::TestOldSerialization::test_serialization_map_location, test/test_serialization.py::TestOldSerialization::test_serialization_offset, test/test_serialization.py::TestOldSerialization::test_serialization_offset_filelike_weights_only_False, test/test_serialization.py::TestOldSerialization::test_serialization_offset_filelike_weights_only_True, test/test_serialization.py::TestOldSerialization::test_serialization_offset_gzip, test/test_serialization.py::TestOldSerialization::test_serialization_safe, test/test_serialization.py::TestOldSerialization::test_serialization_save_warnings, test/test_serialization.py::TestOldSerialization::test_serialization_sparse, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_bsc_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_bsr_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_csc_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_csr_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_invalid, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_invalid_legacy_ctor, test/test_serialization.py::TestOldSerialization::test_serialization_sparse_safe, test/test_serialization.py::TestOldSerialization::test_serialization_storage_slice, test/test_serialization.py::TestOldSerialization::test_serialization_zipfile_utils, test/test_serialization.py::TestOldSerialization::test_serialize_device, test/test_serialization.py::TestOldSerialization::test_skip_data_load, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_False_filename_False, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_False_filename_True, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_True_filename_False, test/test_serialization.py::TestSerialization::test_crc32_options_compute_crc32_True_filename_True, test/test_serialization.py::TestSerialization::test_debug_set_in_ci, test/test_serialization.py::TestSerialization::test_filewriter_metadata_writing_filename_False, test/test_serialization.py::TestSerialization::test_filewriter_metadata_writing_filename_True, test/test_serialization.py::TestSerialization::test_get_unsafe_globals_in_checkpoint, test/test_serialization.py::TestSerialization::test_has_format_version, test/test_serialization.py::TestSerialization::test_load_error_msg, test/test_serialization.py::TestSerialization::test_load_njt_weights_only_should_import_False, test/test_serialization.py::TestSerialization::test_load_njt_weights_only_should_import_True, test/test_serialization.py::TestSerialization::test_load_nonexistent_device, test/test_serialization.py::TestSerialization::test_load_python2_unicode_module, test/test_serialization.py::TestSerialization::test_load_unicode_error_msg, test/test_serialization.py::TestSerialization::test_lr_scheduler_serialization, test/test_serialization.py::TestSerialization::test_meta_serialization_weights_only_False, test/test_serialization.py::TestSerialization::test_meta_serialization_weights_only_True, test/test_serialization.py::TestSerialization::test_mmap_load_offset_calculation_path_type0, test/test_serialization.py::TestSerialization::test_mmap_load_offset_calculation_path_type1, test/test_serialization.py::TestSerialization::test_pathlike_serialization_weights_only_False, test/test_serialization.py::TestSerialization::test_pathlike_serialization_weights_only_True, test/test_serialization.py::TestSerialization::test_pickle_module, test/test_serialization.py::TestSerialization::test_safe_load_basic_types, test/test_serialization.py::TestSerialization::test_save_different_dtype_error, test/test_serialization.py::TestSerialization::test_save_different_dtype_unallocated, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bfloat16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bfloat16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bool_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_bool_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex128_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex128_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_complex64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float32_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float32_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_float64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int16_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int16_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int32_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int32_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int64_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int64_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int8_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_int8_weights_only_True, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_uint8_weights_only_False, test/test_serialization.py::TestSerialization::test_save_load_preserves_dtype_uint8_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization, test/test_serialization.py::TestSerialization::test_serialization_backwards_compat, test/test_serialization.py::TestSerialization::test_serialization_backwards_compat_safe, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals0_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals0_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals1_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_byte_literal_byte_literals1_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_byteorder_mark, test/test_serialization.py::TestSerialization::test_serialization_dill, test/test_serialization.py::TestSerialization::test_serialization_dill_version_not_supported, test/test_serialization.py::TestSerialization::test_serialization_dtype_complex32_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_complex32_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e4m3fn_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e4m3fn_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e5m2_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_float8_e5m2_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint16_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint16_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint32_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint32_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint64_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_dtype_uint64_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_efficient_zerotensor_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_efficient_zerotensor_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_fake_zip, test/test_serialization.py::TestSerialization::test_serialization_filelike, test/test_serialization.py::TestSerialization::test_serialization_filelike_api_requirements, test/test_serialization.py::TestSerialization::test_serialization_filelike_exceptions, test/test_serialization.py::TestSerialization::test_serialization_filelike_missing_attrs, test/test_serialization.py::TestSerialization::test_serialization_filelike_stress, test/test_serialization.py::TestSerialization::test_serialization_filelike_uses_readinto, test/test_serialization.py::TestSerialization::test_serialization_gzip, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_bfloat16, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_bool, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_cdouble, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_cfloat, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_double, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_float, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_half, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int16, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_int8, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_long, test/test_serialization.py::TestSerialization::test_serialization_load_bom_data_uint8, test/test_serialization.py::TestSerialization::test_serialization_map_location, test/test_serialization.py::TestSerialization::test_serialization_math_bits_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_math_bits_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_ctx, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type0_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type0_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type1_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_options_path_type1_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_mmap_loading_with_map_location, test/test_serialization.py::TestSerialization::test_serialization_nested_class, test/test_serialization.py::TestSerialization::test_serialization_offset_gzip, test/test_serialization.py::TestSerialization::test_serialization_python_attr_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_python_attr_weights_only_True, test/test_serialization.py::TestSerialization::test_serialization_safe, test/test_serialization.py::TestSerialization::test_serialization_save_warnings, test/test_serialization.py::TestSerialization::test_serialization_sparse, test/test_serialization.py::TestSerialization::test_serialization_sparse_bsc_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_bsr_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_csc_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_csr_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_invalid, test/test_serialization.py::TestSerialization::test_serialization_sparse_invalid_legacy_ctor, test/test_serialization.py::TestSerialization::test_serialization_sparse_safe, test/test_serialization.py::TestSerialization::test_serialization_storage_slice, test/test_serialization.py::TestSerialization::test_serialization_uintx_intx, test/test_serialization.py::TestSerialization::test_serialization_warning_s390x, test/test_serialization.py::TestSerialization::test_serialization_with_header, test/test_serialization.py::TestSerialization::test_serialization_zipfile_actually_jit, test/test_serialization.py::TestSerialization::test_serialization_zipfile_utils, test/test_serialization.py::TestSerialization::test_serialization_zipfile_weights_only_False, test/test_serialization.py::TestSerialization::test_serialization_zipfile_weights_only_True, test/test_serialization.py::TestSerialization::test_serialize_device, test/test_serialization.py::TestSerialization::test_skip_data_load, test/test_serialization.py::TestSerialization::test_skip_data_serialization_error_cases, test/test_serialization.py::TestSerialization::test_skip_data_serialization_materialize_fake_False, test/test_serialization.py::TestSerialization::test_skip_data_serialization_materialize_fake_True, test/test_serialization.py::TestSerialization::test_skip_data_serialization_preserves_views_materialize_fake_False, test/test_serialization.py::TestSerialization::test_skip_data_serialization_preserves_views_materialize_fake_True, test/test_serialization.py::TestSerialization::test_storage_alignment, test/test_serialization.py::TestSerialization::test_use_pinned_memory_for_d2h, test/test_serialization.py::TestSerialization::test_weights_only_assert, test/test_serialization.py::TestSerialization::test_weights_only_blocked_func_error_msg, test/test_serialization.py::TestSerialization::test_weights_only_env_variables_force_weights_only_False, test/test_serialization.py::TestSerialization::test_weights_only_env_variables_force_weights_only_True, test/test_serialization.py::TestSerialization::test_weights_only_error_unsafe_global_False, test/test_serialization.py::TestSerialization::test_weights_only_error_unsafe_global_True, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_blocklist, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build_with_slots_slots_all, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_build_with_slots_slots_some, test/test_serialization.py::TestSerialization::test_weights_only_safe_globals_newobj, test/test_serialization.py::TestSerialization::test_weights_only_with_zoneinfo_unpickle_registration_success, test/test_serialization.py::TestSubclassSerialization::test_cloned_deepcopy_requires_grad_False, test/test_serialization.py::TestSubclassSerialization::test_cloned_deepcopy_requires_grad_True, test/test_serialization.py::TestSubclassSerialization::test_empty_class_serialization, test/test_serialization.py::TestSubclassSerialization::test_safe_globals_context_manager_weights_only, test/test_serialization.py::TestSubclassSerialization::test_safe_globals_for_weights_only, test/test_serialization.py::TestSubclassSerialization::test_sets_are_loadable_with_weights_only, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_deepcopy, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_getstate_overwrite, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_map_location, test/test_serialization.py::TestSubclassSerialization::test_tensor_subclass_wrapper_serialization, test/test_serialization.py::TestBothSerializationCPU::test_serialization_new_format_old_format_compat_weights_only_False_cpu, test/test_serialization.py::TestBothSerializationCPU::test_serialization_new_format_old_format_compat_weights_only_True_cpu
2025-08-14T23:11:25.3721730Z 
2025-08-14T23:11:26.0392813Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:11:26.0394366Z   import pkg_resources
2025-08-14T23:11:26.1708181Z Running torch_np/numpy_tests/fft/test_helper 1/1 ... [2025-08-14 23:11:26.170407]
2025-08-14T23:11:26.1711402Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:11:26.1712917Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_helper.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:11:26.170814]
2025-08-14T23:11:28.7336097Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:11:28.7339000Z   import pkg_resources
2025-08-14T23:11:28.8609886Z Running test_mkldnn 1/1 ... [2025-08-14 23:11:28.860588]
2025-08-14T23:11:28.8610356Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:11:28.8612980Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:11:28.861013]
2025-08-14T23:11:36.6049569Z 
2025-08-14T23:11:36.6051563Z torch_np/numpy_tests/fft/test_helper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_helper_1.1_8fe1fd66f3b5f911_.log
2025-08-14T23:11:36.6058620Z Running 8 items in this shard: test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_axes_keyword, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_equal_to_original, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_inverse, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTShift::test_uneven_dims, test/torch_np/numpy_tests/fft/test_helper.py::TestFFTFreq::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestRFFTFreq::test_definition, test/torch_np/numpy_tests/fft/test_helper.py::TestIRFFTN::test_not_last_axis_success
2025-08-14T23:11:36.6064269Z 
2025-08-14T23:11:41.6861356Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:11:41.6864787Z   import pkg_resources
2025-08-14T23:11:41.8976356Z Running test_unary_ufuncs 1/1 ... [2025-08-14 23:11:41.897108]
2025-08-14T23:11:41.8977275Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:11:41.8981160Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_unary_ufuncs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:11:41.897583]
2025-08-14T23:13:18.2681381Z 
2025-08-14T23:13:18.2682923Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_3c79781464710dd4_.log
2025-08-14T23:13:18.2733693Z Running 89 items in this shard: test/test_mkldnn.py::TestMkldnnCPU::test_0_dimension_tensor_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_add_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_from_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_to_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_clone_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_functional_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_legacy_jit_model_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_byte_char_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_copy_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_default_use_parent_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_detach_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_empty_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_generic_precision_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_jit_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_legacy_new_failure_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_non_contiguous_weight_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_lstm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_conv_shapecheck_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_error_on_zero_stride_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_scaled_mm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_setflags_nowarn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mlkdnn_get_set_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mul_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu__cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_inplace_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_repr_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_blocked_format_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnet18_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnext50_32x4d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_set_data_tensorimpl_type_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_sigmoid_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_softmax_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_tanh_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_invalid_dime_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_view_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_zero__cpu
2025-08-14T23:13:18.2912125Z 
2025-08-14T23:13:22.9443263Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:13:22.9446628Z   import pkg_resources
2025-08-14T23:13:23.1560063Z Running test_jit_autocast 1/1 ... [2025-08-14 23:13:23.155572]
2025-08-14T23:13:23.1561451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:13:23.1564526Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_autocast.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:13:23.156079]
2025-08-14T23:13:50.0373014Z 
2025-08-14T23:13:50.0374747Z test_jit_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_autocast_1.1_c1577a96210626ca_.log
2025-08-14T23:13:50.0410700Z Running 54 items in this shard: test/test_jit_autocast.py::TestAutocast::test_autocast_api, test/test_jit_autocast.py::TestAutocast::test_autocast_api_not_supported, test/test_jit_autocast.py::TestAutocast::test_autocast_autodiff, test/test_jit_autocast.py::TestAutocast::test_autocast_decorator, test/test_jit_autocast.py::TestAutocast::test_autocast_decorator_outside_jit, test/test_jit_autocast.py::TestAutocast::test_autocast_mixed_dtypes, test/test_jit_autocast.py::TestAutocast::test_callees, test/test_jit_autocast.py::TestAutocast::test_callees_with_autocast_off, test/test_jit_autocast.py::TestAutocast::test_callees_with_autocast_on, test/test_jit_autocast.py::TestAutocast::test_conditional_autocast, test/test_jit_autocast.py::TestAutocast::test_control_flow, test/test_jit_autocast.py::TestAutocast::test_divergent_autocast, test/test_jit_autocast.py::TestAutocast::test_divergent_types, test/test_jit_autocast.py::TestAutocast::test_duplicate_inputs, test/test_jit_autocast.py::TestAutocast::test_eager_and_script, test/test_jit_autocast.py::TestAutocast::test_explicit_casts, test/test_jit_autocast.py::TestAutocast::test_fp32_policy, test/test_jit_autocast.py::TestAutocast::test_fp32_policy_with_fp64, test/test_jit_autocast.py::TestAutocast::test_fp32_set_opt_dtype_policy, test/test_jit_autocast.py::TestAutocast::test_fp32_set_opt_dtype_policy_fp64, test/test_jit_autocast.py::TestAutocast::test_ignore_amp, test/test_jit_autocast.py::TestAutocast::test_implicitly_nested_autocast, test/test_jit_autocast.py::TestAutocast::test_inplace, test/test_jit_autocast.py::TestAutocast::test_jit_autocast_softmax_cpu, test/test_jit_autocast.py::TestAutocast::test_jit_autocast_softmax_gpu, test/test_jit_autocast.py::TestAutocast::test_jit_call_method_under_autocast, test/test_jit_autocast.py::TestAutocast::test_jit_executor_under_autocast, test/test_jit_autocast.py::TestAutocast::test_jit_freeze_autocast_basic, test/test_jit_autocast.py::TestAutocast::test_jit_freeze_autocast_constants, test/test_jit_autocast.py::TestAutocast::test_jit_generic_autocast, test/test_jit_autocast.py::TestAutocast::test_linear_bf16, test/test_jit_autocast.py::TestAutocast::test_minimal, test/test_jit_autocast.py::TestAutocast::test_minimal_cpu, test/test_jit_autocast.py::TestAutocast::test_minimal_off, test/test_jit_autocast.py::TestAutocast::test_nested_autocast, test/test_jit_autocast.py::TestAutocast::test_promote_policy, test/test_jit_autocast.py::TestAutocast::test_promote_policy_fp64, test/test_jit_autocast.py::TestAutocast::test_reused_autocast, test/test_jit_autocast.py::TestAutocast::test_reused_autocast_expr, test/test_jit_autocast.py::TestAutocast::test_runtime_autocast_state, test/test_jit_autocast.py::TestAutocast::test_runtime_autocast_state_expr, test/test_jit_autocast.py::TestAutocast::test_script_and_tracing, test/test_jit_autocast.py::TestAutocast::test_script_and_tracing_with_autocast, test/test_jit_autocast.py::TestAutocast::test_script_module, test/test_jit_autocast.py::TestAutocast::test_tracing_and_script, test/test_jit_autocast.py::TestAutocast::test_tracing_with_autocast_and_script, test/test_jit_autocast.py::TestJitTraceAutocast::test_cat_promote, test/test_jit_autocast.py::TestJitTraceAutocast::test_generate_autocast_jit_trace_model, test/test_jit_autocast.py::TestJitTraceAutocast::test_nchw_autocast_jit_trace_model, test/test_jit_autocast.py::TestJitTraceAutocast::test_nhwc_autocast_jit_trace_model, test/test_jit_autocast.py::TestJitTraceAutocast::test_script_autocast_cpu, test/test_jit_autocast.py::TestJitTraceAutocast::test_script_autocast_cuda, test/test_jit_autocast.py::TestJitTraceAutocast::test_script_autocast_enable_and_check, test/test_jit_autocast.py::TestJitTraceAutocast::test_scripted_aliasing
2025-08-14T23:13:50.0518118Z 
2025-08-14T23:13:53.4916353Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:13:53.4919675Z   import pkg_resources
2025-08-14T23:13:53.6192841Z Running test_dlpack 1/1 ... [2025-08-14 23:13:53.618837]
2025-08-14T23:13:53.6193792Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:13:53.6196178Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dlpack.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:13:53.619221]
2025-08-14T23:13:58.7932873Z 
2025-08-14T23:13:58.7934218Z test_dlpack 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dlpack_1.1_f893f65e429a4460_.log
2025-08-14T23:13:58.8042489Z Running 142 items in this shard: test/test_dlpack.py::TestTorchDlPackCPU::test_automatically_select_in_creation_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_copy_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_capsule_conversion_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_diff_streams_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_conversion_with_streams_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_convert_default_stream_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_cuda_per_thread_stream_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_default_stream_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_export_is_conj_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_export_non_strided_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_export_requires_grad_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_invalid_cpu_stream_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_invalid_cuda_streams_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_invalid_rocm_streams_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_normalize_strides_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_protocol_conversion_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_shared_storage_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_invalid_stream_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_tensor_on_different_device_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_dlpack_unsupported_dtype_error_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_dtype_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_bfloat16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_bool, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_from_dlpack_noncontinguous_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_max_version_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_needs_copy_error_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_no_copy_cpu, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_complex128, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_complex64, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_float16, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_float32, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_float64, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_int16, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_int32, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_int64, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_int8, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_uint16, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_uint32, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_uint64, test/test_dlpack.py::TestTorchDlPackCPU::test_numpy_dlpack_protocol_conversion_cpu_uint8, test/test_dlpack.py::TestTorchDlPackCPU::test_unsupported_device_error_cpu
2025-08-14T23:13:58.8246585Z 
2025-08-14T23:14:02.3732112Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:02.3735432Z   import pkg_resources
2025-08-14T23:14:02.5012350Z Running profiler/test_profiler_tree 1/1 ... [2025-08-14 23:14:02.500777]
2025-08-14T23:14:02.5013156Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:02.5015542Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_profiler_tree.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:02.501231]
2025-08-14T23:14:06.0235976Z 
2025-08-14T23:14:06.0238260Z profiler/test_profiler_tree 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_profiler_tree_1.1_54e19ead25c26192_.log
2025-08-14T23:14:06.0251844Z Running 10 items in this shard: test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda_detailed, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_cuda_with_stream, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_memory, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_memory_and_stack, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_record_function, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_modules, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_torch_dispatch, test/profiler/test_profiler_tree.py::TestProfilerTree::test_profiler_experimental_tree_with_stack_and_torch_function
2025-08-14T23:14:06.0263952Z 
2025-08-14T23:14:10.2793596Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:10.2796389Z   import pkg_resources
2025-08-14T23:14:10.4638600Z Running torch_np/numpy_tests/core/test_scalar_ctors 1/1 ... [2025-08-14 23:14:10.462903]
2025-08-14T23:14:10.4639510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:10.4641572Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalar_ctors.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:10.463352]
2025-08-14T23:14:15.4858679Z 
2025-08-14T23:14:15.4860259Z torch_np/numpy_tests/core/test_scalar_ctors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalar_ctors_1.1_f2277630f1565f72_.log
2025-08-14T23:14:15.4889744Z Running 65 items in this shard: test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_bool, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_floating, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromString::test_floating_overflow, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromInt::test_intp, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestFromInt::test_uint64_from_negative, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t10_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_complex_t11_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_byte_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_int__t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_intc_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_longlong_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_np_short_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_byte, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_int_, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_intc, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_longlong, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_np_short, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_t25, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_integers_t15_t26, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t10_t23, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t11_t23, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t20, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t21, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t22, test/torch_np/numpy_tests/core/test_scalar_ctors.py::TestArrayFromScalar::test_reals_t12_t23
2025-08-14T23:14:15.4917328Z 
2025-08-14T23:14:19.6985087Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:19.6988726Z   import pkg_resources
2025-08-14T23:14:19.8876280Z Running profiler/test_torch_tidy 1/1 ... [2025-08-14 23:14:19.887078]
2025-08-14T23:14:19.8877756Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:19.8882626Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_torch_tidy.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:19.887650]
2025-08-14T23:14:20.8913926Z 
2025-08-14T23:14:20.8915625Z test_sparse_csr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_csr_1.1_f65c6342d55af163_.log
2025-08-14T23:14:21.4079925Z Running 4709 items in this shard: test/test_sparse_csr.py::TestSparseCSRSampler::test_make_crow_indices, test/test_sparse_csr.py::TestSparseCSRCPU::test_add_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_add_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_add_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_add_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_all_sparse_csr_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_dense_result_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_errors_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_0_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_0_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_0_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_1_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_25_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_25_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_25_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_0_m_25_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_0_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_1_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_addmm_sizes_all_sparse_csr_k_0_n_10_m_1_cpu_complex64, 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test/test_sparse_csr.py::TestSparseCSRCPU::test_csr_to_block_csr_blocksize_4_cpu_float64_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_csr_to_block_csr_errors_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSC_Batched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSC_Batched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSC_NonBatched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSC_NonBatched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSR_Batched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSR_Batched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSR_NonBatched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseBSR_NonBatched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSC_Batched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSC_Batched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSC_NonBatched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSC_NonBatched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSR_Batched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSR_Batched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSR_NonBatched_Hybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_dense_to_from_sparse_compressed_SparseCSR_NonBatched_NonHybrid_cpu, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_int16, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_int32, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_int8, test/test_sparse_csr.py::TestSparseCSRCPU::test_direct_coo_csr_conversion_cpu_uint8, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_bool, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_float16, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_int16, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_int32, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_int8, test/test_sparse_csr.py::TestSparseCSRCPU::test_exercise_detach_cpu_uint8, test/test_sparse_csr.py::TestSparseCSRCPU::test_linalg_solve_sparse_csr_cusolver_cpu_float32, 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test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_cpu_int16, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_cpu_int32, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_cpu_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_cpu_int8, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_cpu_uint8, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_bool, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_float16, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_int16, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_int32, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_int8, test/test_sparse_csr.py::TestSparseCSRCPU::test_resize_errors_cpu_uint8, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_autograd_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_autograd_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_autograd_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_autograd_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_errors_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_errors_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_errors_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_errors_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_zero_sized_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_zero_sized_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_zero_sized_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_sampled_addmm_zero_sized_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_bool, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_complex128, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_complex64, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_float16, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_float32, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_float64, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_int16, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_int32, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_int64, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_int8, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int32_cpu_uint8, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int64_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int64_cpu_bool, test/test_sparse_csr.py::TestSparseCSRCPU::test_select_SparseBSC_int64_cpu_complex128, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSC_cpu_uint8, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_sparse_compressed_tensor_with_dims_SparseCSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSC_cpu_float32, 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test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseBSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSC_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_to_dtype_SparseCSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSC_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseBSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSC_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_bfloat16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_bool, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_complex128, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_complex64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_float64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int16, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int32, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int64, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_int8, test/test_sparse_csr.py::TestSparseCompressedCPU::test_validate_SparseCSR_cpu_uint8, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_TensorAsKey, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_dense_addmm_meta, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_dense_bmm, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_dense_bmm_error_messages, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_scatter_mm, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_bsr_softmax, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_kernel, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_sampled_addmm, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_scaled_dot_product_attention, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_scatter_mm, test/test_sparse_csr.py::TestSparseCompressedTritonKernelsCPU::test_triton_tune
2025-08-14T23:14:21.7879306Z 
2025-08-14T23:14:24.4553763Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:24.5825269Z   import pkg_resources
2025-08-14T23:14:24.5825990Z Running torch_np/test_reductions 1/1 ... [2025-08-14 23:14:24.581867]
2025-08-14T23:14:24.5827037Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:24.5829103Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:24.582313]
2025-08-14T23:14:31.9564344Z 
2025-08-14T23:14:31.9566338Z profiler/test_torch_tidy 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_torch_tidy_1.1_786db9d4a41ec8d3_.log
2025-08-14T23:14:31.9592084Z Running 22 items in this shard: test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_id_uniqueness, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_ids_with_other_ops, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocations, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_extra_fields, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_impl_reuse, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_mkldnn_tensors, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_module_and_optimizer_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_nnmodule_params, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer_parameters_adam, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer_parameters_sgd, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_pointers_and_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_refcounts, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_scalar_ins, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_sparse_tensors, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensor_lists, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensor_properties, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_full, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_keep_alive, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_scalar_args, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_set
2025-08-14T23:14:31.9614669Z 
2025-08-14T23:14:32.1789012Z 
2025-08-14T23:14:32.1790495Z torch_np/test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_reductions_1.1_19f664ef5030722f_.log
2025-08-14T23:14:32.2647843Z Running 966 items in this shard: test/torch_np/test_reductions.py::TestFlatnonzero::test_basic, test/torch_np/test_reductions.py::TestAny::test_basic, test/torch_np/test_reductions.py::TestAny::test_method_vs_function, test/torch_np/test_reductions.py::TestAny::test_nd, test/torch_np/test_reductions.py::TestAll::test_basic, test/torch_np/test_reductions.py::TestAll::test_method_vs_function, test/torch_np/test_reductions.py::TestAll::test_nd, test/torch_np/test_reductions.py::TestMean::test_mean, test/torch_np/test_reductions.py::TestMean::test_mean_float16, test/torch_np/test_reductions.py::TestMean::test_mean_values, test/torch_np/test_reductions.py::TestMean::test_mean_where, test/torch_np/test_reductions.py::TestSum::test_sum, test/torch_np/test_reductions.py::TestSum::test_sum_boolean, test/torch_np/test_reductions.py::TestSum::test_sum_complex_1_dt0, test/torch_np/test_reductions.py::TestSum::test_sum_complex_1_dt1, test/torch_np/test_reductions.py::TestSum::test_sum_complex_2_dt0, test/torch_np/test_reductions.py::TestSum::test_sum_complex_2_dt1, test/torch_np/test_reductions.py::TestSum::test_sum_dtypes_2, test/torch_np/test_reductions.py::TestSum::test_sum_dtypes_warnings, test/torch_np/test_reductions.py::TestSum::test_sum_initial, test/torch_np/test_reductions.py::TestSum::test_sum_stability, test/torch_np/test_reductions.py::TestSum::test_sum_where, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func0, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func1, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func10, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func11, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func2, test/torch_np/test_reductions.py::TestGenericReductions::test_array_axis_func3, 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test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func4_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func5_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func6_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func7_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func8_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_-1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_-2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_axis_keepdims_True_dtype_int32_func9_axis_2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func0, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func1, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func10, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func11, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func2, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func3, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func4, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func5, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func6, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func7, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func8, test/torch_np/test_reductions.py::TestGenericReductions::test_out_scalar_func9, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_array_axis_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_array_axis_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_bad_tuple_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_bad_tuple_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_empty_generic_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_axis_empty_generic_func1, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_bad_axis_func0, test/torch_np/test_reductions.py::TestGenericCumSumProd::test_bad_axis_func1
2025-08-14T23:14:32.3502606Z 
2025-08-14T23:14:35.3267730Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:35.3271027Z   import pkg_resources
2025-08-14T23:14:35.4525303Z Running lazy/test_reuse_ir 1/1 ... [2025-08-14 23:14:35.452008]
2025-08-14T23:14:35.4526439Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:35.4529030Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_reuse_ir.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:35.452465]
2025-08-14T23:14:36.7528772Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:36.7531942Z   import pkg_resources
2025-08-14T23:14:36.9459176Z Running test_functional_autograd_benchmark 1/1 ... [2025-08-14 23:14:36.945474]
2025-08-14T23:14:36.9463868Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:36.9466171Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_functional_autograd_benchmark.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:36.945912]
2025-08-14T23:14:40.5412590Z 
2025-08-14T23:14:40.5414278Z lazy/test_reuse_ir 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_reuse_ir_1.1_dc10268ea3f57aed_.log
2025-08-14T23:14:40.5416954Z Running 4 items in this shard: test/lazy/test_reuse_ir.py::TestLazyReuseIr::testAdd, test/lazy/test_reuse_ir.py::TestLazyReuseIr::testAddSub, test/lazy/test_reuse_ir.py::TestLazyReuseIr::testAddSubFallback, test/lazy/test_reuse_ir.py::TestLazyReuseIr::testBatchNorm
2025-08-14T23:14:40.5418276Z 
2025-08-14T23:14:47.6540027Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:14:47.6542898Z   import pkg_resources
2025-08-14T23:14:48.0716929Z Running test_prims 1/1 ... [2025-08-14 23:14:48.071201]
2025-08-14T23:14:48.0754162Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:14:48.0760313Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_prims.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:14:48.075645]
2025-08-14T23:14:57.7842557Z 
2025-08-14T23:14:57.7843722Z test_prims 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_prims_1.1_b84572aaa148c13a_.log
2025-08-14T23:14:57.7856184Z Running 24 items in this shard: test/test_prims.py::TestPrimsBasic::test_check_deprecation_warning, test/test_prims.py::TestPrimsBasic::test_clone_complex, test/test_prims.py::TestPrimsBasic::test_mul_complex, test/test_prims.py::TestPrimsBasic::test_torch_ops, test/test_prims.py::TestPrimsCPU::test_aten_overload_to_prims_cpu, test/test_prims.py::TestPrimsCPU::test_broadcast_in_dim_cpu_float32, test/test_prims.py::TestPrimsCPU::test_broadcast_in_dim_sum_cpu_float32, test/test_prims.py::TestPrimsCPU::test_cbrt_prim_cpu_float64, test/test_prims.py::TestPrimsCPU::test_cbrt_prim_cpu_int64, test/test_prims.py::TestPrimsCPU::test_collapse_cpu_float32, test/test_prims.py::TestPrimsCPU::test_functional_rng_wrappers_cpu_float32, test/test_prims.py::TestPrimsCPU::test_memory_format_strides_cpu_float32, test/test_prims.py::TestPrimsCPU::test_philox_rand_cpu_float32, test/test_prims.py::TestPrimsCPU::test_reshape_view_method_cpu_float32, test/test_prims.py::TestPrimsCPU::test_var_correction_0_cpu_float32, test/test_prims.py::TestPrimsCPU::test_var_correction_1_cpu_float32, test/test_prims.py::TestRefsCPU::test_constant_pad_nd_memory_format_cpu_float32, test/test_prims.py::TestRefsCPU::test_inferred_tags_cpu, test/test_prims.py::TestRefsCPU::test_infinite_loop_from_py_dispatcher_cpu, test/test_prims.py::TestRefsCPU::test_linspace_with_complex_input_cpu, test/test_prims.py::TestRefsCPU::test_logspace_with_complex_input_cpu, test/test_prims.py::TestRefsCPU::test_unbind_cpu, test/test_prims.py::TestDecompCPU::test_decomposition_method_vararg_ones_cpu_float32, test/test_prims.py::TestDecompCPU::test_decomposition_method_vararg_permute_cpu_float32
2025-08-14T23:14:57.7869316Z 
2025-08-14T23:15:02.5370440Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:15:02.5373743Z   import pkg_resources
2025-08-14T23:15:02.7298043Z Running profiler/test_python_tracer 1/1 ... [2025-08-14 23:15:02.729013]
2025-08-14T23:15:02.7298944Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:15:02.7301600Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_python_tracer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-14 23:15:02.729453]
2025-08-14T23:15:15.0782020Z 
2025-08-14T23:15:15.0784541Z profiler/test_python_tracer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_python_tracer_1.1_3d4d11db5c3a9815_.log
2025-08-14T23:15:15.0794343Z Running 3 items in this shard: test/profiler/test_python_tracer.py::TestPythonTracer::test_method_with_c_function, test/profiler/test_python_tracer.py::TestPythonTracer::test_monitoring_callback, test/profiler/test_python_tracer.py::TestPythonTracer::test_unexpected_c_return_events
2025-08-14T23:15:15.0797531Z 
2025-08-14T23:15:22.2425177Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:15:22.2428501Z   import pkg_resources
2025-08-14T23:15:26.7534049Z 
2025-08-14T23:15:26.7535671Z test_functional_autograd_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functional_autograd_benchmark_1.1_66320d2f3d1acc98_.log
2025-08-14T23:15:26.7537503Z Running 2 items in this shard: test/test_functional_autograd_benchmark.py::TestFunctionalAutogradBenchmark::test_fast_tasks, test/test_functional_autograd_benchmark.py::TestFunctionalAutogradBenchmark::test_slow_tasks
2025-08-14T23:15:31.6645074Z 
2025-08-14T23:15:31.6648113Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:15:31.6651238Z   import pkg_resources
2025-08-14T23:19:07.9415651Z 
2025-08-14T23:19:07.9416572Z test_unary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_unary_ufuncs_1.1_97990f3fd3119355_.log
2025-08-14T23:19:08.9539864Z Running 24601 items in this shard: test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_angle_complex_to_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_angle_complex_to_float_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_big_number_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_signed_zero_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_signed_zero_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_zero_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_abs_zero_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_bool_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing__refs__conversions_byte_cpu_complex64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_elu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_hardtanh_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_prelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_prelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_relu6_cpu_float64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softplus_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softplus_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_batch_vs_slicing_nn_functional_softsign_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_log_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_logical_not_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_logical_not_cpu_bool, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_elu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_hardtanh_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_mish_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu6_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_selu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_selu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_softplus_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_softplus_cpu_float64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_tanhshrink_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other__refs_nn_functional_threshold_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_abs_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_acosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_angle_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_asinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_atanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bfloat16_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_bitwise_not_cpu_uint8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_char_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_conj_physical_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_cosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_deg2rad_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_double_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_erfinv_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_exp_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_expm1_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_fill_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_float_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_floor_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frac_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frexp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frexp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_frexp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_half_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_i0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_imag_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_imag_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_imag_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_int_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isfinite_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isnan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isneginf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isposinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_isreal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_jiterator_unary_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_lgamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log10_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log1p_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_log_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logical_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_logit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_long_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nan_to_num_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_elu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_hardtanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_logsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_mish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_mish_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu6_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_rrelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_rrelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_rrelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_selu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_complex_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softplus_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softplus_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_softsign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_tanhshrink_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_nn_functional_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_polygamma_polygamma_n_4_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_positive_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rad2deg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_real_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_reciprocal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_neg_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_neg_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_round_decimals_neg_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_every_other_rsqrt_cpu_float32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acosh_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_acosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_angle_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bfloat16_cpu_int8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_bool_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_byte_cpu_uint8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_ceil_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cfloat_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_char_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_conj_physical_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_cosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_deg2rad_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_double_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_erfinv_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_exp_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_expm1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_fill_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_float_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_floor_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frac_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_frexp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_half_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_i0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_imag_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_imag_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_imag_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_int_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isfinite_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isnan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isneginf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isposinf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_isreal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_jiterator_unary_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_lgamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log10_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log1p_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_log_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logical_not_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_logit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_long_cpu_complex64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nan_to_num_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_celu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_elu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_hardtanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_logsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_logsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_mish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_mish_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_prelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_prelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu6_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_rrelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_rrelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_rrelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_selu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_selu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_complex_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softplus_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softplus_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_softsign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_tanhshrink_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_nn_functional_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_polygamma_polygamma_n_4_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_positive_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rad2deg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_real_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_reciprocal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_neg_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_neg_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_round_decimals_neg_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_rsqrt_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sgn_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_short_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sigmoid_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_signbit_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sin_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_sinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_airy_ai_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_j1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_bessel_y1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_entr_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_special_erfcx_cpu_int16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tan_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tan_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_tanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_contig_vs_transposed_trunc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_digamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_digamma_special_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_digamma_special_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_exp_slow_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_asin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_atanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_erfinv_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_rsqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_rsqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_multigammaln_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains__refs_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_acosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_asin_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_asin_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_asin_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_asin_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_atanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_erfinv_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log10_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log10_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log10_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log10_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log1p_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log1p_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log1p_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log1p_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log2_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_log_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_logit_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_logit_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_logit_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_logit_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_rsqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_rsqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_rsqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_rsqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_special_ndtri_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_special_ndtri_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_sqrt_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_sqrt_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_sqrt_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_float_domains_sqrt_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_frexp_assert_raises_cpu, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_frexp_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_frexp_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_frexp_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_edge_cases_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_edge_cases_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardshrink_edge_cases_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_backward_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_backward_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_backward_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardswish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardswish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_hardswish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_range3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_special_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_special_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_i0_special_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_common_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_common_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_common_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_common_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_edge_cases_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_edge_cases_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_edge_cases_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_igamma_edge_cases_cpu_float64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_bool_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_byte_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cdouble_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_ceil_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cfloat_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_chalf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_char_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_conj_physical_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cos_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_cosh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_deg2rad_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_digamma_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_double_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erf_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erf_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_erfc_cpu_int8, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_isreal_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_jiterator_unary_cpu_int64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_mvlgamma_mvlgamma_p_5_cpu_float16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_complex32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_neg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_celu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_elu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_elu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_elu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_elu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_hardtanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_logsigmoid_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_mish_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_mish_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_mish_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_mish_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_prelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_prelu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_prelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_prelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu6_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_relu_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_rrelu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_rrelu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_rrelu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_selu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_selu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_selu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_selu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_complex_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softplus_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_softsign_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_tanhshrink_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_nn_functional_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_0_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_1_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_2_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_3_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_polygamma_polygamma_n_4_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_positive_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_positive_cpu_complex128, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_rad2deg_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_bfloat16, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_real_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_reciprocal_cpu_int32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_0_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_0_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_3_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_3_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_neg_3_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_round_decimals_neg_3_cpu_float32, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_sinh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_airy_ai_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_bool, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_non_contig_expand_special_bessel_j0_cpu_int64, 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test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_tanh_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_float16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_reference_numerics_small_trunc_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_complex_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_complex_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_silu_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_sinc_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_i0_i1_vs_scipy_cpu_bfloat16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_i0_i1_vs_scipy_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_i0_i1_vs_scipy_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_log_ndtr_vs_scipy_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_log_ndtr_vs_scipy_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_ndtr_vs_scipy_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_special_ndtr_vs_scipy_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_complex128, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_complex64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_float32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_float64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_int16, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_int32, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_int64, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_int8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_threshold_cpu_uint8, test/test_unary_ufuncs.py::TestUnaryUfuncsCPU::test_unary_out_op_mem_overlap_cpu_float64
2025-08-14T23:19:09.9372663Z 
2025-08-14T23:19:09.9372854Z Running test batch 'tests to run' cost 7749.69 seconds
2025-08-14T23:19:21.0061287Z 
2025-08-14T23:19:21.0061682Z real	129m25.836s
2025-08-14T23:19:21.0061979Z user	499m46.532s
2025-08-14T23:19:21.0062219Z sys	33m58.892s
2025-08-14T23:19:21.0078653Z + assert_git_not_dirty
2025-08-14T23:19:21.0078965Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]]
2025-08-14T23:19:21.0085482Z + [[ linux-jammy-py3.13-clang12 != *xla* ]]
2025-08-14T23:19:21.0093710Z ++ git status --porcelain
2025-08-14T23:19:21.0094273Z ++ grep -v '?? third_party'
2025-08-14T23:20:03.6537868Z ++ true
2025-08-14T23:20:03.6575573Z + git_status=
2025-08-14T23:20:03.6577405Z + [[ -n '' ]]
2025-08-14T23:20:03.6577704Z + test_aten
2025-08-14T23:20:03.6582238Z + echo 'Running ATen tests with pytorch lib'
2025-08-14T23:20:03.6582651Z Running ATen tests with pytorch lib
2025-08-14T23:20:03.6582981Z + [[ -n '' ]]
2025-08-14T23:20:03.6583262Z + echo 'Running test with the build folder'
2025-08-14T23:20:03.6583669Z Running test with the build folder
2025-08-14T23:20:03.6584012Z + TEST_BASE_DIR=build/bin
2025-08-14T23:20:03.6590874Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libc10.so build/bin
2025-08-14T23:20:03.6635487Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libcaffe2*' build/bin
2025-08-14T23:20:03.6648597Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libmkldnn*' build/bin
2025-08-14T23:20:03.6662066Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libnccl*' build/bin
2025-08-14T23:20:03.6677092Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorchbind_test.so build/bin
2025-08-14T23:20:03.6687935Z + ls build/bin
2025-08-14T23:20:03.6759472Z  BackoffTest			       c10_typeid_test
2025-08-14T23:20:03.6760089Z  CMakeFiles			       cmake_install.cmake
2025-08-14T23:20:03.6760484Z  CTestTestfile.cmake		       cpu_allocator_test
2025-08-14T23:20:03.6761133Z  CppSignature_test		       cpu_generator_test
2025-08-14T23:20:03.6761877Z  Dict_test			       cpu_profiling_allocator_test
2025-08-14T23:20:03.6762317Z  Dimname_test			       cpu_rng_test
2025-08-14T23:20:03.6762649Z  FileStoreTest			       dlconvertor_test
2025-08-14T23:20:03.6763172Z  HashStoreTest			       example_allreduce
2025-08-14T23:20:03.6763538Z  IListRef_test			       extension_backend_test
2025-08-14T23:20:03.6763885Z  KernelFunction_test		       half_test
2025-08-14T23:20:03.6764346Z  List_test			       inline_container_test
2025-08-14T23:20:03.6764694Z  MaybeOwned_test		       ivalue_test
2025-08-14T23:20:03.6765059Z  NamedTensor_test		       kernel_function_legacy_test
2025-08-14T23:20:03.6765509Z  ProcessGroupGlooTest		       kernel_function_test
2025-08-14T23:20:03.6765943Z  StorageUtils_test		       kernel_lambda_legacy_test
2025-08-14T23:20:03.6766324Z  TCPStoreTest			       kernel_lambda_test
2025-08-14T23:20:03.6766696Z  apply_utils_test		       kernel_stackbased_test
2025-08-14T23:20:03.6767059Z  atest				       lazy_tensor_test
2025-08-14T23:20:03.6767388Z  backend_fallback_test		       legacy_vmap_test
2025-08-14T23:20:03.6767743Z  basic				       libc10.so
2025-08-14T23:20:03.6768032Z  broadcast_test			      'libcaffe2*'
2025-08-14T23:20:03.6768369Z  c10_AllocatorConfig_test	      'libmkldnn*'
2025-08-14T23:20:03.6768697Z  c10_ArrayRef_test		      'libnccl*'
2025-08-14T23:20:03.6769010Z  c10_Bitset_test		       libtorch.so
2025-08-14T23:20:03.6769388Z  c10_CompileTimeFunctionPointer_test   libtorch_cpu.so
2025-08-14T23:20:03.6769828Z  c10_ConstexprCrc_test		       libtorch_global_deps.so
2025-08-14T23:20:03.6770255Z  c10_DeadlockDetection_test	       libtorch_python.so
2025-08-14T23:20:03.6770947Z  c10_DeviceGuard_test		       libtorchbind_test.so
2025-08-14T23:20:03.6771430Z  c10_Device_test		       make_boxed_from_unboxed_functor_test
2025-08-14T23:20:03.6771864Z  c10_DispatchKeySet_test	       math_kernel_test
2025-08-14T23:20:03.6772247Z  c10_Enumerate_test		       memory_format_test
2025-08-14T23:20:03.6772623Z  c10_Half_test			       memory_overlapping_test
2025-08-14T23:20:03.6773024Z  c10_InlineDeviceGuard_test	       mobile_memory_cleanup
2025-08-14T23:20:03.6773443Z  c10_InlineStreamGuard_test	       native_test
2025-08-14T23:20:03.6773830Z  c10_IntrusiveList_test		       op_allowlist_test
2025-08-14T23:20:03.6774206Z  c10_LeftRight_test		       op_registration_test
2025-08-14T23:20:03.6774606Z  c10_Metaprogramming_test	       operator_name_test
2025-08-14T23:20:03.6775004Z  c10_NetworkFlow_test		       operators_test
2025-08-14T23:20:03.6775378Z  c10_Scalar_test		       packedtensoraccessor_test
2025-08-14T23:20:03.6775774Z  c10_Semaphore_test		       parallel_benchmark
2025-08-14T23:20:03.6776142Z  c10_SizesAndStrides_test	       pow_test
2025-08-14T23:20:03.6776483Z  c10_StreamGuard_test		       protoc
2025-08-14T23:20:03.6776797Z  c10_SymInt_test		       protoc-3.13.0.0
2025-08-14T23:20:03.6777144Z  c10_Synchronized_test		       quantized_test
2025-08-14T23:20:03.6777510Z  c10_ThreadLocal_test		       reduce_ops_test
2025-08-14T23:20:03.6777904Z  c10_TypeIndex_test		       reportMemoryUsage_test
2025-08-14T23:20:03.6778278Z  c10_TypeList_test		       scalar_tensor_test
2025-08-14T23:20:03.6778630Z  c10_TypeTraits_test		       scalar_test
2025-08-14T23:20:03.6778991Z  c10_accumulate_test		       static_runtime_bench
2025-08-14T23:20:03.6779356Z  c10_bfloat16_test		       static_runtime_test
2025-08-14T23:20:03.6779732Z  c10_bit_cast_test		       stride_properties_test
2025-08-14T23:20:03.6780219Z  c10_complex_math_test		       tensor_iterator_test
2025-08-14T23:20:03.6780628Z  c10_complex_test		       test_api
2025-08-14T23:20:03.6780949Z  c10_cow_test			       test_cpp_rpc
2025-08-14T23:20:03.6781282Z  c10_error_test			       test_dist_autograd
2025-08-14T23:20:03.6781620Z  c10_exception_test		       test_jit
2025-08-14T23:20:03.6781922Z  c10_flags_test			       test_lazy
2025-08-14T23:20:03.6782242Z  c10_generic_math_test		       test_nativert
2025-08-14T23:20:03.6782614Z  c10_intrusive_ptr_benchmark	       test_parallel
2025-08-14T23:20:03.6782992Z  c10_intrusive_ptr_test		       thread_init_test
2025-08-14T23:20:03.6783353Z  c10_irange_test		       torch_shm_manager
2025-08-14T23:20:03.6783692Z  c10_lazy_test			       type_ptr_test
2025-08-14T23:20:03.6783997Z  c10_logging_test		       type_test
2025-08-14T23:20:03.6784338Z  c10_optional_test		       undefined_tensor_test
2025-08-14T23:20:03.6784779Z  c10_ordered_preserving_dict_test      vec_test_all_types_AVX2
2025-08-14T23:20:03.6785224Z  c10_registry_test		       vec_test_all_types_AVX512
2025-08-14T23:20:03.6785649Z  c10_small_vector_test		       vec_test_all_types_DEFAULT
2025-08-14T23:20:03.6786061Z  c10_ssize_test			       verify_api_visibility
2025-08-14T23:20:03.6786423Z  c10_string_util_test		       weakref_test
2025-08-14T23:20:03.6786750Z  c10_string_view_test		       wrapdim_test
2025-08-14T23:20:03.6787103Z  c10_tempfile_test		       xla_tensor_test
2025-08-14T23:20:03.6787476Z + aten/tools/run_tests.sh build/bin
2025-08-14T23:20:03.6812800Z + set -e
2025-08-14T23:20:03.6815497Z ++ dirname aten/tools/run_tests.sh
2025-08-14T23:20:03.6841426Z + VALGRIND_SUP=/var/lib/jenkins/workspace/aten/tools/valgrind.sup
2025-08-14T23:20:03.6842175Z + export CPP_TESTS_DIR=build/bin
2025-08-14T23:20:03.6842480Z + CPP_TESTS_DIR=build/bin
2025-08-14T23:20:03.6842749Z + VALGRIND=ON
2025-08-14T23:20:03.6844827Z + python test/run_test.py --cpp --verbose -i cpp/basic cpp/atest cpp/scalar_test cpp/broadcast_test cpp/wrapdim_test cpp/apply_utils_test cpp/dlconvertor_test cpp/native_test cpp/scalar_tensor_test cpp/undefined_tensor_test cpp/extension_backend_test cpp/lazy_tensor_test cpp/tensor_iterator_test cpp/Dimname_test cpp/Dict_test cpp/NamedTensor_test cpp/cpu_generator_test cpp/legacy_vmap_test cpp/operators_test
2025-08-14T23:20:06.0644733Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:06.0646265Z   import pkg_resources
2025-08-14T23:20:07.5851442Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json
2025-08-14T23:20:07.5977816Z Found test times from artifacts
2025-08-14T23:20:07.6480080Z Found test times from artifacts
2025-08-14T23:20:07.6495404Z Running all tests
2025-08-14T23:20:07.6500473Z Running parallel tests on 3 processes
2025-08-14T23:20:07.6502287Z Name: tests to run (est. time: 0.0min)
2025-08-14T23:20:07.6502664Z   Serial tests (0):
2025-08-14T23:20:07.6502974Z   Parallel tests (19):
2025-08-14T23:20:07.6503233Z     cpp/Dict_test 1/1
2025-08-14T23:20:07.6503494Z     cpp/Dimname_test 1/1
2025-08-14T23:20:07.6503767Z     cpp/NamedTensor_test 1/1
2025-08-14T23:20:07.6504064Z     cpp/apply_utils_test 1/1
2025-08-14T23:20:07.6504344Z     cpp/atest 1/1
2025-08-14T23:20:07.6504571Z     cpp/basic 1/1
2025-08-14T23:20:07.6504819Z     cpp/broadcast_test 1/1
2025-08-14T23:20:07.6505110Z     cpp/cpu_generator_test 1/1
2025-08-14T23:20:07.6505396Z     cpp/dlconvertor_test 1/1
2025-08-14T23:20:07.6505695Z     cpp/extension_backend_test 1/1
2025-08-14T23:20:07.6506007Z     cpp/lazy_tensor_test 1/1
2025-08-14T23:20:07.6506297Z     cpp/legacy_vmap_test 1/1
2025-08-14T23:20:07.6506634Z     cpp/native_test 1/1
2025-08-14T23:20:07.6507010Z     cpp/operators_test 1/1
2025-08-14T23:20:07.6507637Z     cpp/scalar_tensor_test 1/1
2025-08-14T23:20:07.6508065Z     cpp/scalar_test 1/1
2025-08-14T23:20:07.6508353Z     cpp/tensor_iterator_test 1/1
2025-08-14T23:20:07.6508663Z     cpp/undefined_tensor_test 1/1
2025-08-14T23:20:07.6508982Z     cpp/wrapdim_test 1/1
2025-08-14T23:20:07.6509503Z Name: excluded (est. time: 0.0min)
2025-08-14T23:20:07.6509799Z   Serial tests (0):
2025-08-14T23:20:07.6510052Z   Parallel tests (0):
2025-08-14T23:20:07.6510392Z Running cpp/Dict_test 1/1 ... [2025-08-14 23:20:07.650618]
2025-08-14T23:20:07.6510781Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:07.6520593Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dict_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-23eccda58a058b02.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:07.651815]
2025-08-14T23:20:09.7705748Z 
2025-08-14T23:20:09.7706643Z cpp/Dict_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dict_test_1.1_9363edbdebe6f929_.log
2025-08-14T23:20:09.7707267Z 
2025-08-14T23:20:11.3725813Z Uploading artifacts took 1.60 seconds
2025-08-14T23:20:11.3726298Z Running cpp/Dimname_test 1/1 ... [2025-08-14 23:20:11.372306]
2025-08-14T23:20:11.3726793Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:11.3729308Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dimname_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-dd52b50e79729655.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:11.372686]
2025-08-14T23:20:13.0402518Z 
2025-08-14T23:20:13.0403739Z cpp/Dimname_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dimname_test_1.1_0be034c2e0304e34_.log
2025-08-14T23:20:13.0404459Z 
2025-08-14T23:20:13.0404672Z Running cpp/NamedTensor_test 1/1 ... [2025-08-14 23:20:13.039930]
2025-08-14T23:20:13.0405141Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:13.0406543Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/NamedTensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-5cf7f988f0489396.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:13.040291]
2025-08-14T23:20:14.7074799Z 
2025-08-14T23:20:14.7076133Z cpp/NamedTensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.NamedTensor_test_1.1_0f8a37180b107557_.log
2025-08-14T23:20:14.7077132Z 
2025-08-14T23:20:14.7077344Z Running cpp/apply_utils_test 1/1 ... [2025-08-14 23:20:14.707375]
2025-08-14T23:20:14.7077846Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:14.7079620Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/apply_utils_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-d1f98c6b212187e6.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:14.707728]
2025-08-14T23:20:16.4252975Z 
2025-08-14T23:20:16.4254067Z cpp/apply_utils_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.apply_utils_test_1.1_8a4088c6c6d693c1_.log
2025-08-14T23:20:16.4254768Z 
2025-08-14T23:20:16.4254931Z Running cpp/atest 1/1 ... [2025-08-14 23:20:16.425161]
2025-08-14T23:20:16.4255325Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:16.4258129Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/atest', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-753cdd22323ad242.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:16.425569]
2025-08-14T23:20:18.1428114Z 
2025-08-14T23:20:18.1429133Z cpp/atest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.atest_1.1_2c8e4486f797c52c_.log
2025-08-14T23:20:18.1429737Z 
2025-08-14T23:20:18.1429969Z Running cpp/basic 1/1 ... [2025-08-14 23:20:18.142698]
2025-08-14T23:20:18.1430589Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:18.1433661Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/basic', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-278ffc5eca1ae617.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:18.143106]
2025-08-14T23:20:19.8604196Z 
2025-08-14T23:20:19.8605248Z cpp/basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.basic_1.1_410f01925104c328_.log
2025-08-14T23:20:19.8605822Z 
2025-08-14T23:20:19.8606028Z Running cpp/broadcast_test 1/1 ... [2025-08-14 23:20:19.860261]
2025-08-14T23:20:19.8608170Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:19.8609808Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/broadcast_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-726f3dbef2f3ecdc.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:19.860651]
2025-08-14T23:20:21.5780836Z 
2025-08-14T23:20:21.5781769Z cpp/broadcast_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.broadcast_test_1.1_7e6238ca6f71b479_.log
2025-08-14T23:20:21.5782454Z 
2025-08-14T23:20:21.5782696Z Running cpp/cpu_generator_test 1/1 ... [2025-08-14 23:20:21.577873]
2025-08-14T23:20:21.5783279Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:21.5784924Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/cpu_generator_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-af8ab8838af64424.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:21.578215]
2025-08-14T23:20:23.2955629Z 
2025-08-14T23:20:23.2957016Z cpp/cpu_generator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.cpu_generator_test_1.1_99d3b5701bf3fc31_.log
2025-08-14T23:20:23.2957912Z 
2025-08-14T23:20:23.2958193Z Running cpp/dlconvertor_test 1/1 ... [2025-08-14 23:20:23.295419]
2025-08-14T23:20:23.2958768Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:23.2960660Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/dlconvertor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-f7fe70baed4eee32.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:23.295788]
2025-08-14T23:20:25.0134169Z 
2025-08-14T23:20:25.0135257Z cpp/dlconvertor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.dlconvertor_test_1.1_0b1775f34dc2d7f6_.log
2025-08-14T23:20:25.0135954Z 
2025-08-14T23:20:25.0136201Z Running cpp/extension_backend_test 1/1 ... [2025-08-14 23:20:25.013274]
2025-08-14T23:20:25.0136653Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:25.0139004Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/extension_backend_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-3ba9b0eca48f8c20.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:25.013638]
2025-08-14T23:20:26.7310374Z 
2025-08-14T23:20:26.7311747Z cpp/extension_backend_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.extension_backend_test_1.1_6ce6cab6042fb82b_.log
2025-08-14T23:20:26.7312531Z 
2025-08-14T23:20:26.7312733Z Running cpp/lazy_tensor_test 1/1 ... [2025-08-14 23:20:26.730812]
2025-08-14T23:20:26.7313271Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:26.7315001Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/lazy_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e58e72258c323a7a.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:26.731259]
2025-08-14T23:20:28.4488735Z 
2025-08-14T23:20:28.4490000Z cpp/lazy_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.lazy_tensor_test_1.1_70dab27b315475d0_.log
2025-08-14T23:20:28.4490912Z 
2025-08-14T23:20:28.4491208Z Running cpp/legacy_vmap_test 1/1 ... [2025-08-14 23:20:28.448755]
2025-08-14T23:20:28.4491635Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:28.4493967Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/legacy_vmap_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-607c61590b30bc44.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:28.449148]
2025-08-14T23:20:30.1161200Z 
2025-08-14T23:20:30.1162093Z cpp/legacy_vmap_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.legacy_vmap_test_1.1_b58aa9fc53249aca_.log
2025-08-14T23:20:30.1162775Z 
2025-08-14T23:20:30.1162961Z Running cpp/native_test 1/1 ... [2025-08-14 23:20:30.116011]
2025-08-14T23:20:30.1163377Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:30.1166155Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/native_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-485a100019c1b917.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:30.116385]
2025-08-14T23:20:31.8336712Z 
2025-08-14T23:20:31.8338103Z cpp/native_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.native_test_1.1_9d502b9299b6745c_.log
2025-08-14T23:20:31.8338734Z 
2025-08-14T23:20:31.8338947Z Running cpp/operators_test 1/1 ... [2025-08-14 23:20:31.833530]
2025-08-14T23:20:31.8339395Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:31.8342015Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/operators_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-afb9f75b37f26f09.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:31.833913]
2025-08-14T23:20:33.5010342Z 
2025-08-14T23:20:33.5011280Z cpp/operators_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.operators_test_1.1_52f9e3ecdc49bd65_.log
2025-08-14T23:20:33.5011946Z 
2025-08-14T23:20:33.5012171Z Running cpp/scalar_tensor_test 1/1 ... [2025-08-14 23:20:33.500920]
2025-08-14T23:20:33.5012818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:33.5015317Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-17f398e9eb6606cf.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:33.501305]
2025-08-14T23:20:35.1688624Z 
2025-08-14T23:20:35.1689774Z cpp/scalar_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_tensor_test_1.1_6e86a58a6256c10e_.log
2025-08-14T23:20:35.1690493Z 
2025-08-14T23:20:35.1690681Z Running cpp/scalar_test 1/1 ... [2025-08-14 23:20:35.168729]
2025-08-14T23:20:35.1691098Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:35.1693707Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-ff884e52f9c51d07.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:35.169111]
2025-08-14T23:20:36.8363582Z 
2025-08-14T23:20:36.8364513Z cpp/scalar_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_test_1.1_f2420573c41c7d63_.log
2025-08-14T23:20:36.8365245Z 
2025-08-14T23:20:36.8365469Z Running cpp/tensor_iterator_test 1/1 ... [2025-08-14 23:20:36.836213]
2025-08-14T23:20:36.8366000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:36.8367828Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/tensor_iterator_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-4795de8927162b3f.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:36.836554]
2025-08-14T23:20:38.5537210Z 
2025-08-14T23:20:38.5538763Z cpp/tensor_iterator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.tensor_iterator_test_1.1_5469841f5ca9408c_.log
2025-08-14T23:20:38.5539564Z 
2025-08-14T23:20:38.5539829Z Running cpp/undefined_tensor_test 1/1 ... [2025-08-14 23:20:38.553587]
2025-08-14T23:20:38.5540281Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:38.5542015Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/undefined_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-b271e0f03c8affe2.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:38.553972]
2025-08-14T23:20:40.2714742Z 
2025-08-14T23:20:40.2716460Z cpp/undefined_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.undefined_tensor_test_1.1_0a2bea467df8bde4_.log
2025-08-14T23:20:40.2717704Z 
2025-08-14T23:20:40.2718014Z Running cpp/wrapdim_test 1/1 ... [2025-08-14 23:20:40.271353]
2025-08-14T23:20:40.2718720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:40.2720938Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/wrapdim_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-b4bb0dbbccdeae07.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:40.271781]
2025-08-14T23:20:41.9893727Z 
2025-08-14T23:20:41.9894607Z cpp/wrapdim_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.wrapdim_test_1.1_ee1a4a2f5fad343f_.log
2025-08-14T23:20:41.9895271Z 
2025-08-14T23:20:44.4714223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:44.4717058Z   import pkg_resources
2025-08-14T23:20:44.4727939Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:44.4731005Z   import pkg_resources
2025-08-14T23:20:44.4938400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:44.4941329Z   import pkg_resources
2025-08-14T23:20:44.5986789Z Running cpp/Dict_test 1/1 ... [2025-08-14 23:20:44.598293]
2025-08-14T23:20:44.5987447Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:44.5992011Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dict_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e0a2ebe2c3033c08.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:44.598803]
2025-08-14T23:20:44.5996683Z Running cpp/Dimname_test 1/1 ... [2025-08-14 23:20:44.599438]
2025-08-14T23:20:44.5997385Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:44.6002853Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dimname_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-c5a658e774eebdd5.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:44.599935]
2025-08-14T23:20:44.6216401Z Running cpp/NamedTensor_test 1/1 ... [2025-08-14 23:20:44.621216]
2025-08-14T23:20:44.6217218Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:44.6222002Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/NamedTensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-cb1e5eafca3c0ae6.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:44.621711]
2025-08-14T23:20:48.1758719Z 
2025-08-14T23:20:48.1760038Z cpp/Dimname_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dimname_test_1.1_b9c058e3dbbedc52_.log
2025-08-14T23:20:48.1761083Z 
2025-08-14T23:20:48.7478488Z 
2025-08-14T23:20:48.7479994Z cpp/NamedTensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.NamedTensor_test_1.1_df3cde8dd3dbeb97_.log
2025-08-14T23:20:48.7481271Z 
2025-08-14T23:20:51.9198215Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:51.9201036Z   import pkg_resources
2025-08-14T23:20:52.0483671Z Running cpp/apply_utils_test 1/1 ... [2025-08-14 23:20:52.047941]
2025-08-14T23:20:52.0484585Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:52.0488698Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/apply_utils_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-c119b96c144c6d08.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:52.048461]
2025-08-14T23:20:52.4307388Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:52.4313208Z   import pkg_resources
2025-08-14T23:20:52.5684666Z Running cpp/atest 1/1 ... [2025-08-14 23:20:52.568051]
2025-08-14T23:20:52.5685291Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:52.5690062Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/atest', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-50368241eb000fb8.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:52.568644]
2025-08-14T23:20:53.3307980Z 
2025-08-14T23:20:53.3310902Z cpp/Dict_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dict_test_1.1_d2e61637e86a45bd_.log
2025-08-14T23:20:53.3315214Z 
2025-08-14T23:20:55.4198827Z 
2025-08-14T23:20:55.4200878Z cpp/apply_utils_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.apply_utils_test_1.1_08ccfcc15376e683_.log
2025-08-14T23:20:55.4202012Z 
2025-08-14T23:20:56.8421246Z 
2025-08-14T23:20:56.8422447Z cpp/atest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.atest_1.1_f7ccfe578ecf029f_.log
2025-08-14T23:20:56.8423053Z 
2025-08-14T23:20:57.1917934Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:57.1921014Z   import pkg_resources
2025-08-14T23:20:57.3215422Z Running cpp/basic 1/1 ... [2025-08-14 23:20:57.321152]
2025-08-14T23:20:57.3216227Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:57.3220447Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/basic', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-3d43dde22ffd8d46.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:57.321647]
2025-08-14T23:20:59.3467144Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:20:59.3470104Z   import pkg_resources
2025-08-14T23:20:59.5003928Z Running cpp/broadcast_test 1/1 ... [2025-08-14 23:20:59.500055]
2025-08-14T23:20:59.5004403Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:20:59.5008055Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/broadcast_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-59e70fc292e14822.xml', '-x', '--reruns=2'] ... [2025-08-14 23:20:59.500513]
2025-08-14T23:21:00.1417013Z 
2025-08-14T23:21:00.1418314Z cpp/basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.basic_1.1_f0c02faff56230a1_.log
2025-08-14T23:21:00.1419535Z 
2025-08-14T23:21:00.8105413Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:00.8108095Z   import pkg_resources
2025-08-14T23:21:00.9420137Z Running cpp/cpu_generator_test 1/1 ... [2025-08-14 23:21:00.941624]
2025-08-14T23:21:00.9420901Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:00.9425613Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/cpu_generator_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-977e6b9a6d7c2f09.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:00.942175]
2025-08-14T23:21:02.0201287Z 
2025-08-14T23:21:02.0202752Z cpp/broadcast_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.broadcast_test_1.1_87bd7de7b9ca39f1_.log
2025-08-14T23:21:02.0203766Z 
2025-08-14T23:21:04.0849415Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:04.0852028Z   import pkg_resources
2025-08-14T23:21:04.2911375Z Running cpp/dlconvertor_test 1/1 ... [2025-08-14 23:21:04.290733]
2025-08-14T23:21:04.2911976Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:04.2917896Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/dlconvertor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-5ec16cfd88e74132.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:04.291374]
2025-08-14T23:21:04.7639174Z 
2025-08-14T23:21:04.7640405Z cpp/cpu_generator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.cpu_generator_test_1.1_4d43ef26f0889a82_.log
2025-08-14T23:21:04.7641205Z 
2025-08-14T23:21:05.7884751Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:05.7887792Z   import pkg_resources
2025-08-14T23:21:05.9299140Z Running cpp/extension_backend_test 1/1 ... [2025-08-14 23:21:05.929515]
2025-08-14T23:21:05.9299893Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:05.9303480Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/extension_backend_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e60c24d0de1f5882.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:05.930055]
2025-08-14T23:21:06.9619682Z 
2025-08-14T23:21:06.9620849Z cpp/dlconvertor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.dlconvertor_test_1.1_27994ebba2f0f439_.log
2025-08-14T23:21:06.9621597Z 
2025-08-14T23:21:08.3997510Z 
2025-08-14T23:21:08.3999042Z cpp/extension_backend_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.extension_backend_test_1.1_42b3772bae00d66e_.log
2025-08-14T23:21:08.4000207Z 
2025-08-14T23:21:08.5002284Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:08.5003823Z   import pkg_resources
2025-08-14T23:21:08.6331020Z Running cpp/lazy_tensor_test 1/1 ... [2025-08-14 23:21:08.632717]
2025-08-14T23:21:08.6331490Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:08.6334838Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/lazy_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-46fb5fc057c10e55.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:08.633189]
2025-08-14T23:21:10.5498024Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:10.5500863Z   import pkg_resources
2025-08-14T23:21:10.6790269Z Running cpp/legacy_vmap_test 1/1 ... [2025-08-14 23:21:10.678550]
2025-08-14T23:21:10.6791051Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:10.6794506Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/legacy_vmap_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-f6b5ea4a6301344a.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:10.679048]
2025-08-14T23:21:11.0528768Z 
2025-08-14T23:21:11.0530470Z cpp/lazy_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.lazy_tensor_test_1.1_ff9b09d4b52bcf19_.log
2025-08-14T23:21:11.0531799Z 
2025-08-14T23:21:11.9223359Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:11.9226085Z   import pkg_resources
2025-08-14T23:21:12.1209586Z Running cpp/native_test 1/1 ... [2025-08-14 23:21:12.120507]
2025-08-14T23:21:12.1210375Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:12.1216155Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/native_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e97d861d07ec1056.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:12.121197]
2025-08-14T23:21:14.8915549Z 
2025-08-14T23:21:14.8916890Z cpp/native_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.native_test_1.1_dba275f0cab8a6d2_.log
2025-08-14T23:21:14.8918090Z 
2025-08-14T23:21:15.0304246Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:15.0306965Z   import pkg_resources
2025-08-14T23:21:15.1617451Z Running cpp/operators_test 1/1 ... [2025-08-14 23:21:15.161356]
2025-08-14T23:21:15.1618372Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:15.1622784Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/operators_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-2112c7e4e646c4dd.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:15.161873]
2025-08-14T23:21:15.6084413Z 
2025-08-14T23:21:15.6085826Z cpp/legacy_vmap_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.legacy_vmap_test_1.1_97ffb4ec09d2368d_.log
2025-08-14T23:21:15.6086713Z 
2025-08-14T23:21:17.8321179Z 
2025-08-14T23:21:17.8322711Z cpp/operators_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.operators_test_1.1_8bf7aa7ca686c0e8_.log
2025-08-14T23:21:17.8323931Z 
2025-08-14T23:21:18.4400662Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:18.4403485Z   import pkg_resources
2025-08-14T23:21:18.5684977Z Running cpp/scalar_tensor_test 1/1 ... [2025-08-14 23:21:18.568104]
2025-08-14T23:21:18.5685845Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:18.5689320Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-fe4abbd71ae3582c.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:18.568548]
2025-08-14T23:21:19.2697732Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:19.2700695Z   import pkg_resources
2025-08-14T23:21:19.4735951Z Running cpp/scalar_test 1/1 ... [2025-08-14 23:21:19.473156]
2025-08-14T23:21:19.4736741Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:19.4741324Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-16f40da885e1aa77.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:19.473744]
2025-08-14T23:21:21.0419122Z 
2025-08-14T23:21:21.0420995Z cpp/scalar_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_tensor_test_1.1_e93d6e59b5cc01a1_.log
2025-08-14T23:21:21.0422229Z 
2025-08-14T23:21:21.5405882Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:21.5408137Z   import pkg_resources
2025-08-14T23:21:21.6684749Z Running cpp/tensor_iterator_test 1/1 ... [2025-08-14 23:21:21.668119]
2025-08-14T23:21:21.6685313Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:21.6688478Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/tensor_iterator_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-1effbf926b0cdcf5.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:21.668574]
2025-08-14T23:21:22.3440858Z 
2025-08-14T23:21:22.3441995Z cpp/scalar_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_test_1.1_c2c25956bf214c18_.log
2025-08-14T23:21:22.3443068Z 
2025-08-14T23:21:24.5759538Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:24.5762456Z   import pkg_resources
2025-08-14T23:21:24.7063477Z Running cpp/undefined_tensor_test 1/1 ... [2025-08-14 23:21:24.705885]
2025-08-14T23:21:24.7064262Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:24.7068800Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/undefined_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-74296ae15646b3a6.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:24.706402]
2025-08-14T23:21:25.9378110Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:25.9380453Z   import pkg_resources
2025-08-14T23:21:26.1092406Z Running cpp/wrapdim_test 1/1 ... [2025-08-14 23:21:26.108225]
2025-08-14T23:21:26.1093224Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:21:26.1099150Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/wrapdim_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-fcc4f3ce2e1e3033.xml', '-x', '--reruns=2'] ... [2025-08-14 23:21:26.108815]
2025-08-14T23:21:27.4773052Z 
2025-08-14T23:21:27.4774546Z cpp/undefined_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.undefined_tensor_test_1.1_2e86b5a815bfe963_.log
2025-08-14T23:21:27.4775928Z 
2025-08-14T23:21:29.1307039Z 
2025-08-14T23:21:29.1308454Z cpp/wrapdim_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.wrapdim_test_1.1_7baabb7107b6d1a5_.log
2025-08-14T23:21:29.1309941Z 
2025-08-14T23:21:31.5880355Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:31.5883395Z   import pkg_resources
2025-08-14T23:21:32.3072356Z 
2025-08-14T23:21:32.3073710Z cpp/tensor_iterator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.tensor_iterator_test_1.1_5fc500f16d07153a_.log
2025-08-14T23:21:32.3074647Z 
2025-08-14T23:21:33.0143828Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:21:33.0145401Z   import pkg_resources
2025-08-14T23:21:33.8940599Z Running test batch 'tests to run' cost 86.24 seconds
2025-08-14T23:21:34.7116680Z + run_if_exists tensor_interop_test
2025-08-14T23:21:34.7117414Z + local test_name=tensor_interop_test
2025-08-14T23:21:34.7118034Z + [[ -x build/bin/tensor_interop_test ]]
2025-08-14T23:21:34.7118740Z + echo 'Warning: tensor_interop_test does not exist.'
2025-08-14T23:21:34.7119501Z Warning: tensor_interop_test does not exist.
2025-08-14T23:21:34.7120086Z + run_if_exists cudnn_test
2025-08-14T23:21:34.7120604Z + local test_name=cudnn_test
2025-08-14T23:21:34.7121121Z + [[ -x build/bin/cudnn_test ]]
2025-08-14T23:21:34.7121683Z + echo 'Warning: cudnn_test does not exist.'
2025-08-14T23:21:34.7122335Z Warning: cudnn_test does not exist.
2025-08-14T23:21:34.7122944Z + run_if_exists cuda_generator_test
2025-08-14T23:21:34.7123540Z + local test_name=cuda_generator_test
2025-08-14T23:21:34.7124058Z + [[ -x build/bin/cuda_generator_test ]]
2025-08-14T23:21:34.7124942Z + echo 'Warning: cuda_generator_test does not exist.'
2025-08-14T23:21:34.7125419Z Warning: cuda_generator_test does not exist.
2025-08-14T23:21:34.7125756Z + run_if_exists apply_test
2025-08-14T23:21:34.7126047Z + local test_name=apply_test
2025-08-14T23:21:34.7126346Z + [[ -x build/bin/apply_test ]]
2025-08-14T23:21:34.7126654Z + echo 'Warning: apply_test does not exist.'
2025-08-14T23:21:34.7127004Z Warning: apply_test does not exist.
2025-08-14T23:21:34.7127318Z + run_if_exists stream_test
2025-08-14T23:21:34.7127590Z + local test_name=stream_test
2025-08-14T23:21:34.7127886Z + [[ -x build/bin/stream_test ]]
2025-08-14T23:21:34.7128205Z + echo 'Warning: stream_test does not exist.'
2025-08-14T23:21:34.7128551Z Warning: stream_test does not exist.
2025-08-14T23:21:34.7128854Z + run_if_exists cuda_half_test
2025-08-14T23:21:34.7129149Z + local test_name=cuda_half_test
2025-08-14T23:21:34.7129455Z + [[ -x build/bin/cuda_half_test ]]
2025-08-14T23:21:34.7129782Z + echo 'Warning: cuda_half_test does not exist.'
2025-08-14T23:21:34.7130148Z Warning: cuda_half_test does not exist.
2025-08-14T23:21:34.7130486Z + run_if_exists cuda_vectorized_test
2025-08-14T23:21:34.7130802Z + local test_name=cuda_vectorized_test
2025-08-14T23:21:34.7131156Z + [[ -x build/bin/cuda_vectorized_test ]]
2025-08-14T23:21:34.7131547Z + echo 'Warning: cuda_vectorized_test does not exist.'
2025-08-14T23:21:34.7131938Z Warning: cuda_vectorized_test does not exist.
2025-08-14T23:21:34.7132304Z + run_if_exists cuda_distributions_test
2025-08-14T23:21:34.7132649Z + local test_name=cuda_distributions_test
2025-08-14T23:21:34.7133004Z + [[ -x build/bin/cuda_distributions_test ]]
2025-08-14T23:21:34.7133391Z + echo 'Warning: cuda_distributions_test does not exist.'
2025-08-14T23:21:34.7133822Z Warning: cuda_distributions_test does not exist.
2025-08-14T23:21:34.7134191Z + run_if_exists cuda_optional_test
2025-08-14T23:21:34.7134499Z + local test_name=cuda_optional_test
2025-08-14T23:21:34.7134828Z + [[ -x build/bin/cuda_optional_test ]]
2025-08-14T23:21:34.7135202Z + echo 'Warning: cuda_optional_test does not exist.'
2025-08-14T23:21:34.7135582Z Warning: cuda_optional_test does not exist.
2025-08-14T23:21:34.7136016Z + run_if_exists cuda_tensor_interop_test
2025-08-14T23:21:34.7136416Z + local test_name=cuda_tensor_interop_test
2025-08-14T23:21:34.7136761Z + [[ -x build/bin/cuda_tensor_interop_test ]]
2025-08-14T23:21:34.7137162Z + echo 'Warning: cuda_tensor_interop_test does not exist.'
2025-08-14T23:21:34.7137590Z Warning: cuda_tensor_interop_test does not exist.
2025-08-14T23:21:34.7137961Z + run_if_exists cuda_complex_test
2025-08-14T23:21:34.7138265Z + local test_name=cuda_complex_test
2025-08-14T23:21:34.7138593Z + [[ -x build/bin/cuda_complex_test ]]
2025-08-14T23:21:34.7138954Z + echo 'Warning: cuda_complex_test does not exist.'
2025-08-14T23:21:34.7139322Z Warning: cuda_complex_test does not exist.
2025-08-14T23:21:34.7139666Z + run_if_exists cuda_complex_math_test
2025-08-14T23:21:34.7139999Z + local test_name=cuda_complex_math_test
2025-08-14T23:21:34.7140332Z + [[ -x build/bin/cuda_complex_math_test ]]
2025-08-14T23:21:34.7140726Z + echo 'Warning: cuda_complex_math_test does not exist.'
2025-08-14T23:21:34.7141142Z Warning: cuda_complex_math_test does not exist.
2025-08-14T23:21:34.7141499Z + run_if_exists cuda_cub_test
2025-08-14T23:21:34.7141780Z + local test_name=cuda_cub_test
2025-08-14T23:21:34.7142080Z + [[ -x build/bin/cuda_cub_test ]]
2025-08-14T23:21:34.7142418Z + echo 'Warning: cuda_cub_test does not exist.'
2025-08-14T23:21:34.7142764Z Warning: cuda_cub_test does not exist.
2025-08-14T23:21:34.7143096Z + run_if_exists cuda_atomic_ops_test
2025-08-14T23:21:34.7143420Z + local test_name=cuda_atomic_ops_test
2025-08-14T23:21:34.7143738Z + [[ -x build/bin/cuda_atomic_ops_test ]]
2025-08-14T23:21:34.7144116Z + echo 'Warning: cuda_atomic_ops_test does not exist.'
2025-08-14T23:21:34.7144513Z Warning: cuda_atomic_ops_test does not exist.
2025-08-14T23:21:34.7144842Z + '[' ON == ON ']'
2025-08-14T23:21:34.7145586Z + valgrind --suppressions=/var/lib/jenkins/workspace/aten/tools/valgrind.sup --error-exitcode=1 build/bin/basic '--gtest_filter=-*CUDA'
2025-08-14T23:21:34.7432673Z ==26757== Memcheck, a memory error detector
2025-08-14T23:21:34.7433182Z ==26757== Copyright (C) 2002-2022, and GNU GPL'd, by Julian Seward et al.
2025-08-14T23:21:34.7433757Z ==26757== Using Valgrind-3.20.0 and LibVEX; rerun with -h for copyright info
2025-08-14T23:21:34.7434275Z ==26757== Command: build/bin/basic --gtest_filter=-*CUDA
2025-08-14T23:21:34.7434636Z ==26757== 
2025-08-14T23:21:35.1956155Z ==26757== Warning: set address range perms: large range [0x4a4c000, 0x1a646000) (defined)
2025-08-14T23:21:35.1956923Z ==26757== Warning: set address range perms: large range [0x5c2d000, 0x1741d000) (defined)
2025-08-14T23:21:59.0725745Z Running main() from /var/lib/jenkins/workspace/third_party/googletest/googletest/src/gtest_main.cc
2025-08-14T23:21:59.1007398Z Note: Google Test filter = -*CUDA
2025-08-14T23:21:59.1057416Z [==========] Running 6 tests from 1 test suite.
2025-08-14T23:21:59.1084105Z [----------] Global test environment set-up.
2025-08-14T23:21:59.1154180Z [----------] 6 tests from BasicTest
2025-08-14T23:21:59.1177696Z [ RUN      ] BasicTest.BasicTestCPU
2025-08-14T23:21:59.6581040Z hwloc x86 backend cannot work under Valgrind, disabling.
2025-08-14T23:21:59.6581561Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid
2025-08-14T23:21:59.6582044Z and reloading them under Valgrind with HWLOC_CPUID_PATH.
2025-08-14T23:21:59.7056604Z hwloc x86 backend cannot work under Valgrind, disabling.
2025-08-14T23:21:59.7057114Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid
2025-08-14T23:21:59.7057577Z and reloading them under Valgrind with HWLOC_CPUID_PATH.
2025-08-14T23:21:59.7773284Z hwloc x86 backend cannot work under Valgrind, disabling.
2025-08-14T23:21:59.7773780Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid
2025-08-14T23:21:59.7774255Z and reloading them under Valgrind with HWLOC_CPUID_PATH.
2025-08-14T23:22:00.5599902Z    347 ms
2025-08-14T23:22:00.6469583Z    55 ms
2025-08-14T23:22:00.7202895Z    65 ms
2025-08-14T23:22:01.3263289Z [       OK ] BasicTest.BasicTestCPU (2206 ms)
2025-08-14T23:22:01.3275578Z [ RUN      ] BasicTest.BasicTestHalfCPU
2025-08-14T23:22:01.4687947Z    91 ms
2025-08-14T23:22:01.5234176Z    47 ms
2025-08-14T23:22:01.5900559Z    64 ms
2025-08-14T23:22:01.6443779Z [       OK ] BasicTest.BasicTestHalfCPU (313 ms)
2025-08-14T23:22:01.6444213Z [ RUN      ] BasicTest.FactoryMethodsTest
2025-08-14T23:22:01.6774408Z [       OK ] BasicTest.FactoryMethodsTest (32 ms)
2025-08-14T23:22:01.6774784Z [ RUN      ] BasicTest.BasicStdTestCPU
2025-08-14T23:22:01.8417996Z Simple example: called once
2025-08-14T23:22:01.8506386Z throw: call_once will retry
2025-08-14T23:22:01.8900543Z throw: call_once will retry
2025-08-14T23:22:01.8903297Z throw: call_once will retry
2025-08-14T23:22:01.8908005Z Didn't throw, call_once will not attempt again
2025-08-14T23:22:01.8927242Z [       OK ] BasicTest.BasicStdTestCPU (215 ms)
2025-08-14T23:22:01.8927662Z [ RUN      ] BasicTest.TestForBlobResizeCPU
2025-08-14T23:22:01.9102427Z [       OK ] BasicTest.TestForBlobResizeCPU (17 ms)
2025-08-14T23:22:01.9102887Z [ RUN      ] BasicTest.TestForBlobStridesResizeCPU
2025-08-14T23:22:01.9135677Z [       OK ] BasicTest.TestForBlobStridesResizeCPU (3 ms)
2025-08-14T23:22:01.9157164Z [----------] 6 tests from BasicTest (2796 ms total)
2025-08-14T23:22:01.9157477Z 
2025-08-14T23:22:01.9169263Z [----------] Global test environment tear-down
2025-08-14T23:22:01.9197598Z [==========] 6 tests from 1 test suite ran. (2822 ms total)
2025-08-14T23:22:01.9210247Z [  PASSED  ] 6 tests.
2025-08-14T23:22:03.8992147Z ==26757== 
2025-08-14T23:22:03.8996958Z ==26757== HEAP SUMMARY:
2025-08-14T23:22:03.8997524Z ==26757==     in use at exit: 430,198 bytes in 6,364 blocks
2025-08-14T23:22:03.8998387Z ==26757==   total heap usage: 649,737 allocs, 643,373 frees, 206,936,836 bytes allocated
2025-08-14T23:22:03.8999150Z ==26757== 
2025-08-14T23:22:03.9361370Z ==26757== LEAK SUMMARY:
2025-08-14T23:22:03.9362030Z ==26757==    definitely lost: 0 bytes in 0 blocks
2025-08-14T23:22:03.9362509Z ==26757==    indirectly lost: 0 bytes in 0 blocks
2025-08-14T23:22:03.9362895Z ==26757==      possibly lost: 69,920 bytes in 2 blocks
2025-08-14T23:22:03.9363330Z ==26757==    still reachable: 360,278 bytes in 6,362 blocks
2025-08-14T23:22:03.9363780Z ==26757==         suppressed: 0 bytes in 0 blocks
2025-08-14T23:22:03.9364571Z ==26757== Rerun with --leak-check=full to see details of leaked memory
2025-08-14T23:22:03.9365137Z ==26757== 
2025-08-14T23:22:03.9365473Z ==26757== For lists of detected and suppressed errors, rerun with: -s
2025-08-14T23:22:03.9365999Z ==26757== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 0 from 0)
2025-08-14T23:22:03.9804816Z + [[ -x build/bin/tensor_interop_test ]]
2025-08-14T23:22:03.9806428Z + [[ -n '' ]]
2025-08-14T23:22:03.9806774Z + assert_git_not_dirty
2025-08-14T23:22:03.9807249Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]]
2025-08-14T23:22:03.9807837Z + [[ linux-jammy-py3.13-clang12 != *xla* ]]
2025-08-14T23:22:03.9814558Z ++ git status --porcelain
2025-08-14T23:22:03.9815288Z ++ grep -v '?? third_party'
2025-08-14T23:22:04.2421785Z ++ true
2025-08-14T23:22:04.2422865Z + git_status=
2025-08-14T23:22:04.2423198Z + [[ -n '' ]]
2025-08-14T23:22:04.2423428Z + test_libtorch 1
2025-08-14T23:22:04.2443388Z + local SHARD=1
2025-08-14T23:22:04.2443828Z + [[ crossref != \s\l\o\w ]]
2025-08-14T23:22:04.2444346Z + echo 'Testing libtorch'
2025-08-14T23:22:04.2444630Z Testing libtorch
2025-08-14T23:22:04.2445433Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libbackend_with_compiler.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2456526Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libjitbackend_test.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2467545Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libcaffe2_nvrtc.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2478856Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2489625Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm_windows /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2501250Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorchbind_test.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2513771Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libnvfuser*' /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2520586Z + export CPP_TESTS_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2521223Z + CPP_TESTS_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin
2025-08-14T23:22:04.2521683Z + [[ -z 1 ]]
2025-08-14T23:22:04.2521904Z + [[ 1 == \1 ]]
2025-08-14T23:22:04.2522124Z + test_libtorch_api
2025-08-14T23:22:04.2532412Z + MNIST_DIR=/var/lib/jenkins/workspace/test/cpp/api/mnist
2025-08-14T23:22:04.2533458Z + python tools/download_mnist.py --quiet -d /var/lib/jenkins/workspace/test/cpp/api/mnist
2025-08-14T23:22:04.3023632Z Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz ...
2025-08-14T23:22:04.3183339Z Failed to download (trying next):
2025-08-14T23:22:04.3183711Z HTTP Error 404: Not Found
2025-08-14T23:22:04.3184470Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz ...
2025-08-14T23:22:04.6503263Z Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz ...
2025-08-14T23:22:04.6549235Z Failed to download (trying next):
2025-08-14T23:22:04.6549685Z HTTP Error 404: Not Found
2025-08-14T23:22:04.6550224Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz ...
2025-08-14T23:22:04.6818208Z Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz ...
2025-08-14T23:22:04.6864611Z Failed to download (trying next):
2025-08-14T23:22:04.6865109Z HTTP Error 404: Not Found
2025-08-14T23:22:04.6865622Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz ...
2025-08-14T23:22:04.7739651Z Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz ...
2025-08-14T23:22:04.7799129Z Failed to download (trying next):
2025-08-14T23:22:04.7799499Z HTTP Error 404: Not Found
2025-08-14T23:22:04.7800081Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz ...
2025-08-14T23:22:04.8163393Z + [[ linux-jammy-py3.13-clang12 == *asan* ]]
2025-08-14T23:22:04.8164144Z + [[ linux-jammy-py3.13-clang12 == *slow-gradcheck* ]]
2025-08-14T23:22:04.8164813Z + OMP_NUM_THREADS=2
2025-08-14T23:22:04.8165452Z + TORCH_CPP_TEST_MNIST_PATH=/var/lib/jenkins/workspace/test/cpp/api/mnist
2025-08-14T23:22:04.8166199Z + python test/run_test.py --cpp --verbose -i cpp/test_api -k 'not IMethodTest'
2025-08-14T23:22:07.1338406Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:22:07.1339953Z   import pkg_resources
2025-08-14T23:22:08.6488879Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json
2025-08-14T23:22:08.6612876Z Found test times from artifacts
2025-08-14T23:22:08.7118324Z Found test times from artifacts
2025-08-14T23:22:08.7135023Z Running all tests
2025-08-14T23:22:08.7138424Z Running parallel tests on 3 processes
2025-08-14T23:22:08.7139128Z Name: tests to run (est. time: 0.0min)
2025-08-14T23:22:08.7139450Z   Serial tests (0):
2025-08-14T23:22:08.7139698Z   Parallel tests (1):
2025-08-14T23:22:08.7139954Z     cpp/test_api 1/1
2025-08-14T23:22:08.7140209Z Name: excluded (est. time: 0.0min)
2025-08-14T23:22:08.7140508Z   Serial tests (0):
2025-08-14T23:22:08.7140755Z   Parallel tests (0):
2025-08-14T23:22:08.7144085Z Running cpp/test_api 1/1 ... [2025-08-14 23:22:08.714241]
2025-08-14T23:22:08.7144777Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:22:08.7149567Z Executing ['pytest', '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin/test_api', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-7c3925f33a3d4e56.xml', '-k', 'not IMethodTest', '-x', '--reruns=2'] ... [2025-08-14 23:22:08.714682]
2025-08-14T23:22:10.7827035Z 
2025-08-14T23:22:10.7827904Z cpp/test_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_api_1.1_92a0a107ca64bb4f_.log
2025-08-14T23:22:10.7828509Z 
2025-08-14T23:22:12.3168731Z Uploading artifacts took 1.53 seconds
2025-08-14T23:22:14.6794141Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:22:14.6797111Z   import pkg_resources
2025-08-14T23:22:14.7116713Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:22:14.7119796Z   import pkg_resources
2025-08-14T23:22:14.7216880Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:22:14.7219854Z   import pkg_resources
2025-08-14T23:22:14.8059854Z Running cpp/test_api 1/1 ... [2025-08-14 23:22:14.805625]
2025-08-14T23:22:14.8060644Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:22:14.8064594Z Executing ['pytest', '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin/test_api', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e4f886bb425201be.xml', '-k', 'not IMethodTest', '-x', '--reruns=2'] ... [2025-08-14 23:22:14.806057]
2025-08-14T23:24:20.5047650Z 
2025-08-14T23:24:20.5048671Z cpp/test_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_api_1.1_cae79cb91cf2d408_.log
2025-08-14T23:24:20.5060775Z 
2025-08-14T23:24:21.3212267Z Running test batch 'tests to run' cost 132.61 seconds
2025-08-14T23:24:22.1417316Z + [[ linux-jammy-py3.13-clang12 != *android* ]]
2025-08-14T23:24:22.1417874Z + [[ linux-jammy-py3.13-clang12 != *cuda* ]]
2025-08-14T23:24:22.1418236Z + [[ linux-jammy-py3.13-clang12 != *asan* ]]
2025-08-14T23:24:22.1418596Z + [[ linux-jammy-py3.13-clang12 != *s390x* ]]
2025-08-14T23:24:22.1418928Z + export CPP_TESTS_DIR=build/bin
2025-08-14T23:24:22.1419233Z + CPP_TESTS_DIR=build/bin
2025-08-14T23:24:22.1419630Z + python test/run_test.py --cpp --verbose -i cpp/static_runtime_test
2025-08-14T23:24:24.5322757Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:24:24.5324422Z   import pkg_resources
2025-08-14T23:24:26.0968795Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json
2025-08-14T23:24:26.1097998Z Found test times from artifacts
2025-08-14T23:24:26.1609218Z Found test times from artifacts
2025-08-14T23:24:26.1626616Z Running all tests
2025-08-14T23:24:26.1630126Z Running parallel tests on 3 processes
2025-08-14T23:24:26.1631115Z Name: tests to run (est. time: 0.0min)
2025-08-14T23:24:26.1631634Z   Serial tests (0):
2025-08-14T23:24:26.1631894Z   Parallel tests (1):
2025-08-14T23:24:26.1632243Z     cpp/static_runtime_test 1/1
2025-08-14T23:24:26.1632727Z Name: excluded (est. time: 0.0min)
2025-08-14T23:24:26.1633214Z   Serial tests (0):
2025-08-14T23:24:26.1633701Z   Parallel tests (0):
2025-08-14T23:24:26.1634124Z Running cpp/static_runtime_test 1/1 ... [2025-08-14 23:24:26.163105]
2025-08-14T23:24:26.1634579Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:24:26.1638388Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/static_runtime_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-3eaa47885eeeb73b.xml', '-x', '--reruns=2'] ... [2025-08-14 23:24:26.163558]
2025-08-14T23:24:27.9815695Z 
2025-08-14T23:24:27.9816982Z cpp/static_runtime_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.static_runtime_test_1.1_a684d068db774504_.log
2025-08-14T23:24:27.9817696Z 
2025-08-14T23:24:29.5783250Z Uploading artifacts took 1.60 seconds
2025-08-14T23:24:32.1770012Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:24:32.1772934Z   import pkg_resources
2025-08-14T23:24:32.1886948Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:24:32.1889843Z   import pkg_resources
2025-08-14T23:24:32.2097417Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
2025-08-14T23:24:32.2100197Z   import pkg_resources
2025-08-14T23:24:32.3088721Z Running cpp/static_runtime_test 1/1 ... [2025-08-14 23:24:32.308337]
2025-08-14T23:24:32.3089651Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set
2025-08-14T23:24:32.3092069Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/static_runtime_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-19af79994751a17c.xml', '-x', '--reruns=2'] ... [2025-08-14 23:24:32.308849]
2025-08-14T23:31:07.6306465Z 
2025-08-14T23:31:07.6307391Z cpp/static_runtime_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.static_runtime_test_1.1_9efb44ff082c679d_.log
2025-08-14T23:31:07.6310794Z 
2025-08-14T23:31:08.4906643Z Running test batch 'tests to run' cost 402.33 seconds
2025-08-14T23:31:09.4048553Z + [[ -z 1 ]]
2025-08-14T23:31:09.4048861Z + [[ 1 == \2 ]]
2025-08-14T23:31:09.4049132Z + assert_git_not_dirty
2025-08-14T23:31:09.4049430Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]]
2025-08-14T23:31:09.4049796Z + [[ linux-jammy-py3.13-clang12 != *xla* ]]
2025-08-14T23:31:09.4055782Z ++ git status --porcelain
2025-08-14T23:31:09.4056275Z ++ grep -v '?? third_party'
2025-08-14T23:31:09.6754853Z ++ true
2025-08-14T23:31:09.6755745Z + git_status=
2025-08-14T23:31:09.6756103Z + [[ -n '' ]]
2025-08-14T23:31:09.6756740Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]]
2025-08-14T23:31:09.6787477Z + sccache_epilogue
2025-08-14T23:31:09.6787866Z + echo '::group::Sccache Compilation Log'
2025-08-14T23:31:09.6788727Z ##[group]Sccache Compilation Log
2025-08-14T23:31:09.6789402Z + echo '=================== sccache compilation log ==================='
2025-08-14T23:31:09.6790147Z =================== sccache compilation log ===================
2025-08-14T23:31:09.6790785Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log
2025-08-14T23:31:09.6937580Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ==========='
2025-08-14T23:31:09.6938534Z =========== If your build fails, please take a look at the log above for possible reasons ===========
2025-08-14T23:31:09.6939047Z + sccache --show-stats
2025-08-14T23:31:09.6975726Z Compile requests                     775
2025-08-14T23:31:09.6976100Z Compile requests executed            119
2025-08-14T23:31:09.6976423Z Cache hits                            81
2025-08-14T23:31:09.6976740Z Cache hits (C/C++)                    81
2025-08-14T23:31:09.6977140Z Cache misses                          37
2025-08-14T23:31:09.6977498Z Cache misses (C/C++)                  37
2025-08-14T23:31:09.6977830Z Cache hits rate                    68.64 %
2025-08-14T23:31:09.6978161Z Cache hits rate (C/C++)            68.64 %
2025-08-14T23:31:09.6978518Z Cache timeouts                         0
2025-08-14T23:31:09.6978888Z Cache read errors                      0
2025-08-14T23:31:09.6979580Z Forced recaches                        0
2025-08-14T23:31:09.6979987Z Cache write errors                     0
2025-08-14T23:31:09.6980310Z Cache errors                           0
2025-08-14T23:31:09.6980642Z Compilations                          37
2025-08-14T23:31:09.6980975Z Compilation failures                   1
2025-08-14T23:31:09.6981306Z Non-cacheable compilations             0
2025-08-14T23:31:09.6981645Z Non-cacheable calls                    9
2025-08-14T23:31:09.6981981Z Non-compilation calls                647
2025-08-14T23:31:09.6982317Z Unsupported compiler calls             0
2025-08-14T23:31:09.6982670Z Average cache write                0.044 s
2025-08-14T23:31:09.6983007Z Average compiler                  12.441 s
2025-08-14T23:31:09.6983329Z Average cache read hit             0.041 s
2025-08-14T23:31:09.6983675Z Failed distributed compilations        0
2025-08-14T23:31:09.6983915Z 
2025-08-14T23:31:09.6984016Z Non-cacheable reasons:
2025-08-14T23:31:09.6984288Z -E                                     9
2025-08-14T23:31:09.6984513Z 
2025-08-14T23:31:09.6984751Z Cache location                  s3, name: ossci-compiler-cache-circleci-v2, prefix: /
2025-08-14T23:31:09.6985215Z Version (client)                0.10.0
2025-08-14T23:31:09.6985533Z + sccache --stop-server
2025-08-14T23:31:09.6999621Z Stopping sccache server...
2025-08-14T23:31:09.7003061Z Compile requests                     775
2025-08-14T23:31:09.7003684Z Compile requests executed            119
2025-08-14T23:31:09.7004257Z Cache hits                            81
2025-08-14T23:31:09.7004779Z Cache hits (C/C++)                    81
2025-08-14T23:31:09.7005325Z Cache misses                          37
2025-08-14T23:31:09.7005846Z Cache misses (C/C++)                  37
2025-08-14T23:31:09.7006198Z Cache hits rate                    68.64 %
2025-08-14T23:31:09.7006535Z Cache hits rate (C/C++)            68.64 %
2025-08-14T23:31:09.7006866Z Cache timeouts                         0
2025-08-14T23:31:09.7007175Z Cache read errors                      0
2025-08-14T23:31:09.7007511Z Forced recaches                        0
2025-08-14T23:31:09.7007904Z Cache write errors                     0
2025-08-14T23:31:09.7008609Z Cache errors                           0
2025-08-14T23:31:09.7009369Z Compilations                          37
2025-08-14T23:31:09.7009760Z Compilation failures                   1
2025-08-14T23:31:09.7010177Z Non-cacheable compilations             0
2025-08-14T23:31:09.7010516Z Non-cacheable calls                    9
2025-08-14T23:31:09.7010853Z Non-compilation calls                647
2025-08-14T23:31:09.7011198Z Unsupported compiler calls             0
2025-08-14T23:31:09.7011529Z Average cache write                0.044 s
2025-08-14T23:31:09.7011875Z Average compiler                  12.441 s
2025-08-14T23:31:09.7012238Z Average cache read hit             0.041 s
2025-08-14T23:31:09.7012594Z Failed distributed compilations        0
2025-08-14T23:31:09.7012834Z 
2025-08-14T23:31:09.7012938Z Non-cacheable reasons:
2025-08-14T23:31:09.7013217Z -E                                     9
2025-08-14T23:31:09.7013438Z 
2025-08-14T23:31:09.7013688Z Cache location                  s3, name: ossci-compiler-cache-circleci-v2, prefix: /
2025-08-14T23:31:09.7014149Z Version (client)                0.10.0
2025-08-14T23:31:09.7014480Z + echo ::endgroup::
2025-08-14T23:31:09.7014996Z ##[endgroup]
2025-08-14T23:31:09.7015226Z + cleanup_workspace
2025-08-14T23:31:09.7015761Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.'
2025-08-14T23:31:09.7016595Z sudo may print the following warning message that can be ignored. The chown command will still run.
2025-08-14T23:31:09.7017246Z + echo '    sudo: setrlimit(RLIMIT_STACK): Operation not permitted'
2025-08-14T23:31:09.7018015Z     sudo: setrlimit(RLIMIT_STACK): Operation not permitted
2025-08-14T23:31:09.7018680Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42'
2025-08-14T23:31:09.7019517Z For more details refer to https://github.com/sudo-project/sudo/issues/42
2025-08-14T23:31:09.7020195Z + sudo chown -R 1000 /var/lib/jenkins/workspace
2025-08-14T23:31:12.6426789Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main
2025-08-14T23:31:12.6427362Z with:
2025-08-14T23:31:12.6427782Z   benchmark-results-dir: test/test-reports
2025-08-14T23:31:12.6428212Z   dry-run: false
2025-08-14T23:31:12.6428505Z   schema-version: v3
2025-08-14T23:31:12.6429154Z   github-token: ***
2025-08-14T23:31:12.6429491Z env:
2025-08-14T23:31:12.6429796Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:12.6430377Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:12.6430987Z ##[endgroup]
2025-08-14T23:31:12.6462682Z ##[group]Run set -eux
2025-08-14T23:31:12.6463077Z set -eux
2025-08-14T23:31:12.6463538Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-08-14T23:31:12.6464087Z 
2025-08-14T23:31:12.6464406Z DEVICE_NAME=""
2025-08-14T23:31:12.6464762Z DEVICE_TYPE=""
2025-08-14T23:31:12.6465128Z 
2025-08-14T23:31:12.6465577Z if command -v nvidia-smi; then
2025-08-14T23:31:12.6466164Z   # NB: I'm using PyTorch here to get the device name, however, it needs to
2025-08-14T23:31:12.6466824Z   # install the correct version of PyTorch manually for now. Any PyTorch
2025-08-14T23:31:12.6467490Z   # version is fine, I just use 2.7.1 to satify PYPIDEP linter
2025-08-14T23:31:12.6468060Z   python3 -mpip install torch==2.7.1
2025-08-14T23:31:12.6468528Z elif command -v rocminfo; then
2025-08-14T23:31:12.6469074Z   # NB: Installing torch on ROCm runner with pip here causes CI to fail
2025-08-14T23:31:12.6469795Z   # with a memoryview is too large error only on MI300 runners. Is pip
2025-08-14T23:31:12.6470481Z   # version on ROCm runner there too old? As a workaround, let's use the
2025-08-14T23:31:12.6471042Z   # GPU device name coming from rocminfo instead
2025-08-14T23:31:12.6471658Z   DEVICE_NAME=rocm
2025-08-14T23:31:12.6472269Z   DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs)
2025-08-14T23:31:12.6472960Z fi
2025-08-14T23:31:12.6473285Z 
2025-08-14T23:31:12.6473668Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV
2025-08-14T23:31:12.6474171Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV
2025-08-14T23:31:12.6667744Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:12.6668450Z env:
2025-08-14T23:31:12.6668809Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:12.6669386Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:12.6669978Z ##[endgroup]
2025-08-14T23:31:12.6704256Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-08-14T23:31:13.4393183Z Defaulting to user installation because normal site-packages is not writeable
2025-08-14T23:31:14.5068555Z Collecting boto3==1.35.33
2025-08-14T23:31:14.5229710Z   Downloading boto3-1.35.33-py3-none-any.whl (139 kB)
2025-08-14T23:31:14.8364594Z Collecting psutil==7.0.0
2025-08-14T23:31:14.8399539Z   Downloading psutil-7.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (277 kB)
2025-08-14T23:31:14.8681954Z Collecting pynvml==12.0.0
2025-08-14T23:31:14.8719361Z   Downloading pynvml-12.0.0-py3-none-any.whl (26 kB)
2025-08-14T23:31:16.0663736Z Collecting botocore<1.36.0,>=1.35.33
2025-08-14T23:31:16.0699006Z   Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB)
2025-08-14T23:31:16.2544961Z Collecting s3transfer<0.11.0,>=0.10.0
2025-08-14T23:31:16.2587878Z   Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB)
2025-08-14T23:31:16.2643740Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.33) (0.10.0)
2025-08-14T23:31:16.3089443Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0
2025-08-14T23:31:16.3123599Z   Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB)
2025-08-14T23:31:16.3219357Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1)
2025-08-14T23:31:16.3229231Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.25.10)
2025-08-14T23:31:16.4759648Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.15.0)
2025-08-14T23:31:16.6207267Z Installing collected packages: botocore, s3transfer, nvidia-ml-py, pynvml, psutil, boto3
2025-08-14T23:31:17.1259392Z   Attempting uninstall: nvidia-ml-py
2025-08-14T23:31:17.1260408Z     Found existing installation: nvidia-ml-py 11.525.84
2025-08-14T23:31:17.1280580Z     Uninstalling nvidia-ml-py-11.525.84:
2025-08-14T23:31:17.1641270Z       Successfully uninstalled nvidia-ml-py-11.525.84
2025-08-14T23:31:17.2296528Z   Attempting uninstall: psutil
2025-08-14T23:31:17.2297365Z     Found existing installation: psutil 5.9.8
2025-08-14T23:31:17.2373695Z     Uninstalling psutil-5.9.8:
2025-08-14T23:31:17.2386803Z       Successfully uninstalled psutil-5.9.8
2025-08-14T23:31:17.4086615Z Successfully installed boto3-1.35.33 botocore-1.35.99 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4
2025-08-14T23:31:17.5249119Z + DEVICE_NAME=
2025-08-14T23:31:17.5249431Z + DEVICE_TYPE=
2025-08-14T23:31:17.5249714Z + command -v nvidia-smi
2025-08-14T23:31:17.5249994Z + command -v rocminfo
2025-08-14T23:31:17.5250250Z + echo DEVICE_NAME=
2025-08-14T23:31:17.5250988Z + echo DEVICE_TYPE=
2025-08-14T23:31:17.5282097Z ##[group]Run set -eux
2025-08-14T23:31:17.5282480Z set -eux
2025-08-14T23:31:17.5282704Z 
2025-08-14T23:31:17.5282953Z if [[ -z "${GITHUB_TOKEN}" ]]; then
2025-08-14T23:31:17.5283319Z   echo "Missing github-token input"
2025-08-14T23:31:17.5283670Z   exit 1
2025-08-14T23:31:17.5283900Z fi
2025-08-14T23:31:17.5290158Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:17.5290665Z env:
2025-08-14T23:31:17.5290894Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:17.5291355Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:17.5291871Z   DEVICE_NAME: 
2025-08-14T23:31:17.5292100Z   DEVICE_TYPE: 
2025-08-14T23:31:17.5292568Z   GITHUB_TOKEN: ***
2025-08-14T23:31:17.5292793Z ##[endgroup]
2025-08-14T23:31:17.5317323Z + [[ -z *** ]]
2025-08-14T23:31:17.5391188Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main
2025-08-14T23:31:17.5391900Z with:
2025-08-14T23:31:17.5392334Z   github-token: ***
2025-08-14T23:31:17.5392658Z env:
2025-08-14T23:31:17.5393023Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:17.5393548Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:17.5394160Z   DEVICE_NAME: 
2025-08-14T23:31:17.5394532Z   DEVICE_TYPE: 
2025-08-14T23:31:17.5394877Z ##[endgroup]
2025-08-14T23:31:17.5420589Z ##[group]Run set -eux
2025-08-14T23:31:17.5420887Z set -eux
2025-08-14T23:31:17.5421134Z 
2025-08-14T23:31:17.5421615Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-08-14T23:31:17.5427077Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:17.5427466Z env:
2025-08-14T23:31:17.5427677Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:17.5428158Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:17.5428698Z   DEVICE_NAME: 
2025-08-14T23:31:17.5428933Z   DEVICE_TYPE: 
2025-08-14T23:31:17.5429308Z   GITHUB_TOKEN: ***
2025-08-14T23:31:17.5429545Z ##[endgroup]
2025-08-14T23:31:17.5451649Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 16976255017 i-02d6cf458b1433fa4
2025-08-14T23:31:19.5990283Z setting job-id=48127032084
2025-08-14T23:31:19.5990835Z setting job-name=linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T23:31:19.6109228Z ##[group]Run set -eux
2025-08-14T23:31:19.6109521Z set -eux
2025-08-14T23:31:19.6109877Z 
2025-08-14T23:31:19.6110277Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \
2025-08-14T23:31:19.6110799Z   --schema-version "${SCHEMA_VERSION}" \
2025-08-14T23:31:19.6111160Z   --repo "${REPO}" \
2025-08-14T23:31:19.6111554Z   --head-branch "${HEAD_BRANCH}" \
2025-08-14T23:31:19.6111889Z   --head-sha "${HEAD_SHA}" \
2025-08-14T23:31:19.6112237Z   --workflow-id "${WORKFLOW_RUN_ID}" \
2025-08-14T23:31:19.6112605Z   --run-attempt "${RUN_ATTEMPT}" \
2025-08-14T23:31:19.6112943Z   --job-id "${JOB_ID}" \
2025-08-14T23:31:19.6113241Z   --job-name "${JOB_NAME}"
2025-08-14T23:31:19.6122026Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.6122421Z env:
2025-08-14T23:31:19.6122647Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.6123122Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.6123637Z   DEVICE_NAME: 
2025-08-14T23:31:19.6123868Z   DEVICE_TYPE: 
2025-08-14T23:31:19.6124102Z   SCHEMA_VERSION: v3
2025-08-14T23:31:19.6124348Z   REPO: pytorch/pytorch
2025-08-14T23:31:19.6124620Z   HEAD_BRANCH: refs/heads/main
2025-08-14T23:31:19.6124949Z   HEAD_SHA: 1fc683cf17c8c673044538d10266c00f92987be2
2025-08-14T23:31:19.6125296Z   WORKFLOW_RUN_ID: 16976255017
2025-08-14T23:31:19.6125575Z   RUN_ATTEMPT: 1
2025-08-14T23:31:19.6125805Z   JOB_ID: 48127032084
2025-08-14T23:31:19.6126201Z   JOB_NAME: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T23:31:19.6126665Z ##[endgroup]
2025-08-14T23:31:19.6154869Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 1fc683cf17c8c673044538d10266c00f92987be2 --workflow-id 16976255017 --run-attempt 1 --job-id 48127032084 --job-name 'linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)'
2025-08-14T23:31:19.6490875Z ##[group]Run set -eux
2025-08-14T23:31:19.6491155Z set -eux
2025-08-14T23:31:19.6491389Z 
2025-08-14T23:31:19.6491784Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py"
2025-08-14T23:31:19.6497472Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.6497867Z env:
2025-08-14T23:31:19.6498082Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.6498559Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.6499076Z   DEVICE_NAME: 
2025-08-14T23:31:19.6499321Z   DEVICE_TYPE: 
2025-08-14T23:31:19.6499538Z ##[endgroup]
2025-08-14T23:31:19.6524180Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py
2025-08-14T23:31:19.6932354Z INFO:root:Fail to import torch to get the device name
2025-08-14T23:31:19.7069661Z ##[group]Run set -eux
2025-08-14T23:31:19.7069954Z set -eux
2025-08-14T23:31:19.7070191Z 
2025-08-14T23:31:19.7070437Z # TODO (huydhn): Implement this part
2025-08-14T23:31:19.7070840Z echo "dependencies={}" >> "${GITHUB_OUTPUT}"
2025-08-14T23:31:19.7076656Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.7077032Z env:
2025-08-14T23:31:19.7077258Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.7077733Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.7078250Z   DEVICE_NAME: 
2025-08-14T23:31:19.7078567Z   DEVICE_TYPE: 
2025-08-14T23:31:19.7078798Z ##[endgroup]
2025-08-14T23:31:19.7101339Z + echo 'dependencies={}'
2025-08-14T23:31:19.7131781Z ##[group]Run set -eux
2025-08-14T23:31:19.7132112Z set -eux
2025-08-14T23:31:19.7132347Z 
2025-08-14T23:31:19.7132670Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then
2025-08-14T23:31:19.7133204Z   echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping"
2025-08-14T23:31:19.7133696Z   # We don't want the job to fail if the directory doesn't exist
2025-08-14T23:31:19.7134097Z   exit 0
2025-08-14T23:31:19.7134330Z fi
2025-08-14T23:31:19.7134532Z 
2025-08-14T23:31:19.7134776Z if [[ "${DRY_RUN}" == "true" ]]; then
2025-08-14T23:31:19.7135276Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-08-14T23:31:19.7135992Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-08-14T23:31:19.7136580Z     --metadata "${BENCHMARK_METADATA}" \
2025-08-14T23:31:19.7137144Z     --runners "${RUNNER_INFO}" \
2025-08-14T23:31:19.7137660Z     --dependencies "${DEPENDENCIES}" \
2025-08-14T23:31:19.7138161Z     --dry-run
2025-08-14T23:31:19.7138540Z else
2025-08-14T23:31:19.7139099Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-08-14T23:31:19.7139750Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-08-14T23:31:19.7140205Z     --metadata "${BENCHMARK_METADATA}" \
2025-08-14T23:31:19.7140691Z     --runners "${RUNNER_INFO}" \
2025-08-14T23:31:19.7141044Z     --dependencies "${DEPENDENCIES}"
2025-08-14T23:31:19.7141356Z fi
2025-08-14T23:31:19.7147042Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.7147432Z env:
2025-08-14T23:31:19.7147644Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.7148120Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.7148656Z   DEVICE_NAME: 
2025-08-14T23:31:19.7148908Z   DEVICE_TYPE: 
2025-08-14T23:31:19.7149279Z   BENCHMARK_RESULTS_DIR: test/test-reports
2025-08-14T23:31:19.7149788Z   DRY_RUN: false
2025-08-14T23:31:19.7151293Z   BENCHMARK_METADATA: {"timestamp": 1755214279, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "1fc683cf17c8c673044538d10266c00f92987be2", "workflow_id": 16976255017, "run_attempt": 1, "job_id": 48127032084}
2025-08-14T23:31:19.7153229Z   RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 8, "avail_mem_in_gb": 15, "extra_info": {"hostname": "ip-10-1-41-230.ec2.internal"}, "name": "", "type": ""}]
2025-08-14T23:31:19.7153871Z   DEPENDENCIES: {}
2025-08-14T23:31:19.7154117Z ##[endgroup]
2025-08-14T23:31:19.7176827Z + [[ ! -d test/test-reports ]]
2025-08-14T23:31:19.7177132Z + [[ false == \t\r\u\e ]]
2025-08-14T23:31:19.7180028Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1755214279, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "1fc683cf17c8c673044538d10266c00f92987be2", "workflow_id": 16976255017, "run_attempt": 1, "job_id": 48127032084}' --runners '[{"cpu_info": "x86_64", "cpu_count": 8, "avail_mem_in_gb": 15, "extra_info": {"hostname": "ip-10-1-41-230.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}'
2025-08-14T23:31:19.9321422Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'lazy/test_ts_opinfo'}], 'excluded': []} from test/test-reports/td_exclusions-688f017d78a116cea60c.json is not a benchmark record, skipping
2025-08-14T23:31:19.9323573Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-08-14T23:31:19.9402234Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'inductor/test_cudagraph_trees'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'dynamo/test_repros'}, {'test_file': 'inductor/test_extension_backend'}, {'test_file': 'inductor/test_compiled_optimizers'}, {'test_file': 'dynamo/test_higher_order_ops'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'dynamo/test_misc'}, {'test_file': 'inductor/test_triton_kernels'}, {'test_file': 'inductor/test_inplace_padding'}, {'test_file': 'inductor/test_torchbind'}, {'test_file': 'inductor/test_memory'}, {'test_file': 'inductor/test_aot_inductor_package'}, {'test_file': 'export/test_torchbind'}, {'test_file': 'inductor/test_codecache'}, {'test_file': 'dynamo/test_utils'}, {'test_file': 'dynamo/test_dicts'}, {'test_file': 'test_content_store'}, {'test_file': 'dynamo/test_error_messages'}, {'test_file': 'dynamo/test_trace_rules'}, {'test_file': 'dynamo/test_exceptions'}, {'test_file': 'dynamo/test_precompile_context'}, {'test_file': 'dynamo/test_structured_trace'}, {'test_file': 'dynamo/test_recompile_ux'}, {'test_file': 'inductor/test_cudagraph_trees_expandable_segments'}, {'test_file': 'inductor/test_distributed_patterns'}, {'test_file': 'functorch/test_eager_transforms'}, {'test_file': 'functorch/test_control_flow'}, {'test_file': 'test_ci_sanity_check_fail'}, {'test_file': 'inductor/test_aot_inductor'}, {'test_file': 'test_binary_ufuncs'}, {'test_file': 'test_numpy_interop'}, {'test_file': 'test_ops'}, {'test_file': 'test_type_hints'}, {'test_file': 'nn/test_parametrization'}, {'test_file': 'test_numba_integration'}, {'test_file': 'test_cpp_extensions_mtia_backend'}, {'test_file': 'test_tensor_creation_ops'}, {'test_file': 'test_cpp_extensions_stream_and_event'}, {'test_file': 'test_public_bindings'}, {'test_file': 'test_cuda'}, {'test_file': 'test_autograd'}, {'test_file': 'test_reductions'}, {'test_file': 'test_indexing'}, {'test_file': 'test_nn'}, {'test_file': 'test_overrides'}, {'test_file': 'test_type_promotion'}, {'test_file': 'inductor/test_torchinductor'}, {'test_file': 'doctests'}, {'test_file': 'inductor/test_max_autotune'}, {'test_file': 'inductor/test_torchinductor_dynamic_shapes'}, {'test_file': 'inductor/test_torchinductor_codegen_dynamic_shapes'}, {'test_file': 'inductor/test_torchinductor_opinfo'}, {'test_file': 'inductor/test_cpu_repro'}, {'test_file': 'inductor/test_cuda_repro'}, {'test_file': 'inductor/test_kernel_benchmark'}, {'test_file': 'dynamo/test_unspec'}, {'test_file': 'inductor/test_pattern_matcher'}, {'test_file': 'inductor/test_mkldnn_pattern_matcher'}, {'test_file': 'inductor/test_perf'}, {'test_file': 'inductor/test_foreach'}, {'test_file': 'dynamo/test_modules'}, {'test_file': 'inductor/test_triton_wrapper'}, {'test_file': 'inductor/test_coordinate_descent_tuner'}, {'test_file': 'inductor/test_smoke'}, {'test_file': 'inductor/test_select_algorithm'}, {'test_file': 'inductor/test_dependencies'}, {'test_file': 'inductor/test_compiled_autograd'}, {'test_file': 'inductor/test_fused_attention'}, {'test_file': 'inductor/test_group_batch_fusion'}, {'test_file': 'inductor/test_inductor_freezing'}, {'test_file': 'inductor/test_split_cat_fx_passes'}, {'test_file': 'inductor/test_minifier'}, {'test_file': 'inductor/test_snode_runtime'}, {'test_file': 'inductor/test_custom_lowering'}, {'test_file': 'inductor/test_config'}, {'test_file': 'dynamo/test_backends'}, {'test_file': 'dynamo/test_after_aot'}, {'test_file': 'inductor/test_layout_optim'}, {'test_file': 'inductor/test_binary_folding'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'inductor/test_mmdecomp'}, {'test_file': 'dynamo/test_cudagraphs'}, {'test_file': 'dynamo/test_aot_autograd'}, {'test_file': 'dynamo/test_ctx_manager'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 'inductor/test_flex_attention'}, {'test_file': 'inductor/test_control_flow'}, {'test_file': 'inductor/test_aot_inductor_arrayref'}, {'test_file': 'inductor/test_padding'}, {'test_file': 'inductor/test_torchinductor_strided_blocks'}, {'test_file': 'inductor/test_halide'}, {'test_file': 'inductor/test_triton_cpu_backend'}, {'test_file': 'inductor/test_aot_inductor_custom_ops'}, {'test_file': 'inductor/test_cpu_select_algorithm'}, {'test_file': 'inductor/test_flex_decoding'}, {'test_file': 'inductor/test_unbacked_symints'}, {'test_file': 'inductor/test_external_callables'}, {'test_file': 'dynamo/cpython/3_13/test_generator_stop'}, {'test_file': 'inductor/test_provenance_tracing'}, {'test_file': 'inductor/test_benchmark_fusion'}, {'test_file': 'dynamo/cpython/3_13/test_exception_variations'}, {'test_file': 'dynamo/cpython/3_13/test_int_literal'}, {'test_file': 'dynamo/cpython/3_13/test_itertools'}, {'test_file': 'dynamo/cpython/3_13/test_with'}, {'test_file': 'dynamo/cpython/3_13/test_raise'}, {'test_file': 'dynamo/cpython/3_13/test_contextlib'}, {'test_file': 'inductor/test_alignment'}, {'test_file': 'inductor/test_triton_syntax'}, {'test_file': 'dynamo/cpython/3_13/test_ordered_dict'}, {'test_file': 'dynamo/cpython/3_13/test_numeric_tower'}, {'test_file': 'dynamo/cpython/3_13/test_baseexception'}, {'test_file': 'dynamo/cpython/3_13/test_operator'}, {'test_file': 'dynamo/cpython/3_13/test_exceptions'}, {'test_file': 'dynamo/cpython/3_13/test_collections'}, {'test_file': 'dynamo/cpython/3_13/test_heapq'}, {'test_file': 'dynamo/cpython/3_13/test_int'}, {'test_file': 'dynamo/cpython/3_13/test_userlist'}, {'test_file': 'dynamo/cpython/3_13/test_generators'}, {'test_file': 'dynamo/cpython/3_13/test_set'}, {'test_file': 'dynamo/cpython/3_13/test_math'}, {'test_file': 'dynamo/cpython/3_13/test_userdict'}, {'test_file': 'dynamo/cpython/3_13/test_iter'}, {'test_file': 'dynamo/cpython/3_13/test_bool'}, {'test_file': 'dynamo/cpython/3_13/test_sort'}, {'test_file': 'dynamo/cpython/3_13/test_cmath'}, {'test_file': 'dynamo/cpython/3_13/test_sys'}, {'test_file': 'dynamo/cpython/3_13/test_list'}, {'test_file': 'dynamo/cpython/3_13/test_tuple'}, {'test_file': 'dynamo/cpython/3_13/test_dict'}, {'test_file': 'dynamo/cpython/3_13/test_complex'}, {'test_file': 'dynamo/cpython/3_13/test_float'}, {'test_file': 'inductor/test_subgraph_choice'}, {'test_file': 'inductor/test_cpp_wrapper_hipify'}, {'test_file': 'inductor/test_pad_mm'}, {'test_file': 'inductor/test_multi_kernel'}, {'test_file': 'export/test_export'}, {'test_file': 'inductor/test_cutlass_backend'}, {'test_file': 'dynamo/test_deque_reconstruct'}, {'test_file': 'export/test_retraceability'}, {'test_file': 'inductor/test_cooperative_reductions'}, {'test_file': 'inductor/test_triton_extension_backend'}, {'test_file': 'inductor/test_analysis'}, {'test_file': 'inductor/test_inductor_annotations'}, {'test_file': 'inductor/test_ck_backend'}, {'test_file': 'inductor/test_inductor_utils'}, {'test_file': 'inductor/test_remote_cache'}, {'test_file': 'export/test_functionalized_assertions'}, {'test_file': 'inductor/test_op_completeness'}, {'test_file': 'inductor/test_indexing'}, {'test_file': 'inductor/test_fp8'}, {'test_file': 'inductor/test_fx_fusion'}, {'test_file': 'inductor/test_debug_trace'}, {'test_file': 'inductor/test_online_softmax'}, {'test_file': 'export/test_export_strict'}, {'test_file': 'inductor/test_async_compile'}, {'test_file': 'export/test_export_training_ir_to_run_decomp'}, {'test_file': 'inductor/test_minifier_utils'}, {'test_file': 'export/test_unflatten_training_ir'}, {'test_file': 'export/test_tree_utils'}, {'test_file': 'inductor/test_combo_kernels'}, {'test_file': 'inductor/test_b2b_gemm'}, {'test_file': 'dynamo/test_skip_guard_eval_unsafe'}, {'test_file': 'dynamo/test_functions'}, {'test_file': 'inductor/test_memory_planning'}, {'test_file': 'dynamo/test_interop'}, {'test_file': 'inductor/test_compile_worker'}, {'test_file': 'dynamo/test_buffers_override'}, {'test_file': 'dynamo/test_frame_init'}, {'test_file': 'dynamo/cpython/3_13/test_unittest/test_assertions'}, {'test_file': 'dynamo/test_base_output'}, {'test_file': 'dynamo/test_fx_passes_pre_grad'}, {'test_file': 'export/test_serdes'}, {'test_file': 'inductor/test_utils'}, {'test_file': 'inductor/test_metrics'}, {'test_file': 'inductor/test_cpu_cpp_wrapper'}, {'test_file': 'inductor/test_move_constructors_to_cuda'}, {'test_file': 'inductor/test_autoheuristic'}, {'test_file': 'dynamo/test_inline_and_install'}, {'test_file': 'dynamo/test_nops'}, {'test_file': 'dynamo/test_skip_non_tensor'}, {'test_file': 'inductor/test_gpu_cpp_wrapper'}, {'test_file': 'inductor/test_cutlass_evt'}, {'test_file': 'dynamo/test_recompiles'}, {'test_file': 'inductor/test_kernel_optimization'}, {'test_file': 'inductor/test_codegen_triton'}, {'test_file': 'export/test_export_with_inline_and_install'}, {'test_file': 'inductor/test_cudacodecache'}, {'test_file': 'inductor/test_static_cuda_launcher'}, {'test_file': 'inductor/test_op_dtype_prop'}, {'test_file': 'dynamo/test_pre_dispatch'}, {'test_file': 'dynamo/test_resume'}, {'test_file': 'dynamo/test_sdpa'}, {'test_file': 'dynamo/test_metrics_context'}, {'test_file': 'inductor/test_inplacing_pass'}, {'test_file': 'dynamo/test_global'}, {'test_file': 'dynamo/test_graph_region_tracker'}, {'test_file': 'inductor/test_custom_post_grad_passes'}, {'test_file': 'inductor/test_fuzzer'}, {'test_file': 'export/test_tools'}, {'test_file': 'inductor/test_best_config'}, {'test_file': 'dynamo/test_subgraphs'}, {'test_file': 'inductor/test_triton_heuristics'}, {'test_file': 'test_custom_ops'}, {'test_file': 'inductor/test_quantization'}, {'test_file': 'inductor/test_block_analysis'}, {'test_file': 'inductor/test_profiler'}, {'test_file': 'inductor/test_compile_subprocess'}, {'test_file': 'inductor/test_xpu_basic'}, {'test_file': 'dynamo/test_view'}, {'test_file': 'inductor/test_helion_kernels'}, {'test_file': 'dynamo/test_list'}, {'test_file': 'inductor/test_aot_inductor_utils'}, {'test_file': 'inductor/test_loop_ordering'}, {'test_file': 'inductor/test_ordered_set'}, {'test_file': 'inductor/test_fxir_backend'}, {'test_file': 'inductor/test_decompose_mem_bound_mm'}, {'test_file': 'dynamo/test_install_free_tensors'}, {'test_file': 'dynamo/test_fx_graph_runnable'}, {'test_file': 'dynamo/test_autograd_function'}, {'test_file': 'export/test_cpp_serdes'}, {'test_file': 'dynamo/test_config'}, {'test_file': 'export/test_package'}, {'test_file': 'inductor/test_benchmarking'}, {'test_file': 'inductor/test_needs_exact_strides'}, {'test_file': 'dynamo/test_reconstruct'}, {'test_file': 'inductor/test_inductor_scheduler'}, {'test_file': 'dynamo/test_compile'}, {'test_file': 'inductor/test_compile'}, {'test_file': 'export/test_db'}, {'test_file': 'inductor/test_graph_transform_observer'}, {'test_file': 'dynamo/test_export_mutations'}, {'test_file': 'dynamo/test_unittest'}, {'test_file': 'dynamo/test_pgo'}, {'test_file': 'dynamo/test_sources'}, {'test_file': 'dynamo/test_graph_deduplication'}, {'test_file': 'inductor/test_torchinductor_codegen_config_overrides'}, {'test_file': 'dynamo/test_flat_apply'}, {'test_file': 'dynamo/test_guard_serialization'}, {'test_file': 'dynamo/test_modes'}, {'test_file': 'inductor/test_scatter_optimization'}, {'test_file': 'inductor/test_split_cat_fx_aten_passes'}, {'test_file': 'export/test_passes'}, {'test_file': 'export/test_unflatten'}, {'test_file': 'export/test_upgrader'}, {'test_file': 'export/test_swap'}, {'test_file': 'export/test_schema'}, {'test_file': 'dynamo/test_decorators'}, {'test_file': 'dynamo/test_einops'}, {'test_file': 'dynamo/test_backward_higher_order_ops'}, {'test_file': 'export/test_nativert'}, {'test_file': 'inductor/test_minifier_isolate'}, {'test_file': 'inductor/test_auto_functionalize'}, {'test_file': 'dynamo/test_verify_correctness'}, {'test_file': 'dynamo/test_export'}, {'test_file': 'dynamo/test_model_output'}, {'test_file': 'dynamo/test_sets'}, {'test_file': 'dynamo/test_base_hop'}, {'test_file': 'dynamo/test_profiler'}, {'test_file': 'dynamo/test_deviceguard'}, {'test_file': 'dynamo/test_optimizers'}, {'test_file': 'dynamo/test_debug_utils'}, {'test_file': 'dynamo/test_python_dispatcher'}, {'test_file': 'export/test_lift_unlift'}, {'test_file': 'dynamo/test_compiler_bisector'}, {'test_file': 'test_model_exports_to_core_aten'}, {'test_file': 'dynamo/test_package'}, {'test_file': 'export/test_experimental'}, {'test_file': 'dynamo/test_input_attr_tracking'}, {'test_file': 'dynamo/test_bytecode_utils'}, {'test_file': 'export/test_hop'}, {'test_file': 'export/test_converter'}, {'test_file': 'dynamo/test_callback'}, {'test_file': 'export/test_pass_infra'}, {'test_file': 'inductor/test_mps_basic'}, {'test_file': 'dynamo/test_aot_autograd_cache'}, {'test_file': 'inductor/test_efficient_conv_bn_eval'}, {'test_file': 'dynamo/test_cudagraphs_expandable_segments'}, {'test_file': 'dynamo/test_guard_manager'}, {'test_file': 'test_sparse_semi_structured'}, {'test_file': 'export/test_serialize'}, {'test_file': 'dynamo/test_torchrec'}, {'test_file': 'export/test_verifier'}, {'test_file': 'dynamo/test_minifier'}, {'test_file': 'test_functionalization_of_rng_ops'}, {'test_file': 'dynamo/test_fake_distributed'}, {'test_file': 'dynamo/test_hooks'}, {'test_file': 'dynamo/test_generator'}, {'test_file': 'dynamo/test_reorder_logs'}, {'test_file': 'dynamo/test_subclasses'}, {'test_file': 'export/test_sparse'}, {'test_file': 'export/test_draft_export'}, {'test_file': 'dynamo/test_comptime'}, {'test_file': 'test_testing'}, {'test_file': 'dynamo/test_python_autograd'}, {'test_file': 'test_quantization'}, {'test_file': 'test_dynamic_shapes'}, {'test_file': 'higher_order_ops/test_invoke_subgraph'}, {'test_file': 'dynamo/cpython/3_13/test_defaultdict'}, {'test_file': 'test_package'}, {'test_file': 'test_hop_infra'}, {'test_file': 'test_comparison_utils'}, {'test_file': 'functorch/test_ac_logging'}, {'test_file': 'test_mkl_verbose'}, {'test_file': 'test_appending_byte_serializer'}, {'test_file': 'test_cpp_api_parity'}, {'test_file': 'test_autoload'}, {'test_file': 'test_proxy_tensor'}, {'test_file': 'test_mkldnn_verbose'}, {'test_file': 'test_utils_config_module'}, {'test_file': 'test_functionalization'}, {'test_file': 'test_rename_privateuse1_to_existing_device'}, {'test_file': 'test_transformers_privateuse1'}, {'test_file': 'test_transformers'}, {'test_file': 'test_extension_utils'}, {'test_file': 'test_ao_sparsity'}, {'test_file': 'test_license'}, {'test_file': 'torch_np/test_binary_ufuncs'}, {'test_file': 'xpu/test_fusion'}, {'test_file': 'torch_np/test_unary_ufuncs'}, {'test_file': 'test_foreach'}, {'test_file': 'test_expanded_weights'}, {'test_file': 'typing/test_python_operators'}, {'test_file': 'test_fx_experimental'}, {'test_file': 'test_file_check'}, {'test_file': 'torch_np/test_dtype'}, {'test_file': 'higher_order_ops/test_with_effects'}, {'test_file': 'test_native_functions'}, {'test_file': 'functorch/test_minifier'}, {'test_file': 'test_flop_counter'}, {'test_file': 'torch_np/test_nep50_examples'}, {'test_file': 'higher_order_ops/test_invoke_quant'}, {'test_file': 'test_per_overload_api'}, {'test_file': 'test_tensorexpr_pybind'}, {'test_file': 'test_pytree'}, {'test_file': 'test_fx_passes'}, {'test_file': 'test_fx'}, {'test_file': 'test_fake_tensor'}, {'test_file': 'test_module_tracker'}, {'test_file': 'test_typing'}, {'test_file': 'test_openmp'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarinherit'}, {'test_file': 'functorch/test_ac_knapsack'}, {'test_file': 'backends/xeon/test_launch'}, {'test_file': 'test_nestedtensor'}, {'test_file': 'test_namedtensor'}, {'test_file': 'test_openreg'}, {'test_file': 'xpu/test_gemm'}, {'test_file': 'torch_np/test_ufuncs_basic'}, {'test_file': 'test_meta'}, {'test_file': 'test_show_pickle'}, {'test_file': 'test_utils_filelock'}, {'test_file': 'torch_np/test_random'}, {'test_file': 'profiler/test_kineto'}, {'test_file': 'test_tensorexpr'}, {'test_file': 'test_compile_benchmark_util'}, {'test_file': 'test_jiterator'}, {'test_file': 'test_optim'}, {'test_file': 'test_decomp'}, {'test_file': 'torch_np/test_basic'}, {'test_file': 'lazy/test_bindings'}, {'test_file': 'test_legacy_vmap'}, {'test_file': 'test_modules'}, {'test_file': 'test_torch'}, {'test_file': 'test_matmul_cuda'}, {'test_file': 'test_weak'}, {'test_file': 'functorch/test_logging'}, {'test_file': 'test_logging'}, {'test_file': 'test_out_dtype_op'}, {'test_file': 'test_complex'}, {'test_file': 'xpu/test_conv'}, {'test_file': 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic'}, {'test_file': 'torch_np/numpy_tests/core/test_einsum'}, {'test_file': 'test_ops_jit'}, {'test_file': 'lazy/test_step_closures'}, {'test_file': 'test_ops_gradients'}, {'test_file': 'test_fx_reinplace_pass'}, {'test_file': 'nn/test_multihead_attention'}, {'test_file': 'functorch/test_aot_joint_with_descriptors'}, {'test_file': 'test_pruning_op'}, {'test_file': 'lazy/test_functionalization'}, {'test_file': 'test_utils'}, {'test_file': 'functorch/test_ac'}, {'test_file': 'test_python_dispatch'}, {'test_file': 'test_ops_fwd_gradients'}, {'test_file': 'test_hub'}, {'test_file': 'test_set_default_mobile_cpu_allocator'}, {'test_file': 'test_cuda_expandable_segments'}, {'test_file': 'test_stateless'}, {'test_file': 'test_dispatch'}, {'test_file': 'distributions/test_constraints'}, {'test_file': 'test_namedtuple_return_api'}, {'test_file': 'profiler/test_record_function'}, {'test_file': 'test_multiprocessing'}, {'test_file': 'test_autograd_fallback'}, {'test_file': 'nn/test_lazy_modules'}, {'test_file': 'test_jit_fuser_te'}, {'test_file': 'test_segment_reductions'}, {'test_file': 'test_import_stats'}, {'test_file': 'test_masked'}, {'test_file': 'test_cuda_sanitizer'}, {'test_file': 'test_monitor'}, {'test_file': 'profiler/test_cpp_thread'}, {'test_file': 'test_subclass'}, {'test_file': 'profiler/test_profiler'}, {'test_file': 'functorch/test_vmap_registrations'}, {'test_file': 'nn/test_pruning'}, {'test_file': 'test_itt'}, {'test_file': 'optim/test_lrscheduler'}, {'test_file': 'test_jit_disabled'}, {'test_file': 'torch_np/numpy_tests/core/test_numeric'}, {'test_file': 'test_sympy_utils'}, {'test_file': 'torch_np/test_indexing'}, {'test_file': 'torch_np/numpy_tests/lib/test_function_base'}, {'test_file': 'test_jit'}, {'test_file': 'nn/test_packed_sequence'}, {'test_file': 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic'}, {'test_file': 'functorch/test_ops'}, {'test_file': 'functorch/test_aotdispatch'}, {'test_file': 'test_schema_check'}, {'test_file': 'test_datapipe'}, {'test_file': 'test_autocast'}, {'test_file': 'test_bundled_inputs'}, {'test_file': 'profiler/test_execution_trace'}, {'test_file': 'lazy/test_generator'}, {'test_file': 'torch_np/numpy_tests/core/test_indexing'}, {'test_file': 'test_maskedtensor'}, {'test_file': 'test_tensorboard'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'lazy/test_ts_opinfo'}, {'test_file': 'test_mkldnn_fusion'}, {'test_file': 'benchmark_utils/test_benchmark_utils'}, {'test_file': 'test_linalg'}, {'test_file': 'optim/test_swa_utils'}, {'test_file': 'test_futures'}, {'test_file': 'torch_np/numpy_tests/lib/test_histograms'}, {'test_file': 'optim/test_optim'}, {'test_file': 'nn/test_embedding'}, {'test_file': 'nn/test_dropout'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarmath'}, {'test_file': 'test_functional_optim'}, {'test_file': 'test_vulkan'}, {'test_file': 'functorch/test_vmap'}, {'test_file': 'test_cuda_trace'}, {'test_file': 'nn/test_load_state_dict'}, {'test_file': 'test_shape_ops'}, {'test_file': 'torch_np/numpy_tests/core/test_dtype'}, {'test_file': 'torch_np/numpy_tests/core/test_shape_base'}, {'test_file': 'test_type_info'}, {'test_file': 'test_dataloader'}, {'test_file': 'test_jit_llga_fuser'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'test_native_mha'}, {'test_file': 'test_sort_and_select'}, {'test_file': 'torch_np/numpy_tests/lib/test_twodim_base'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'nn/test_module_hooks'}, {'test_file': 'test_numa_binding'}, {'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'lazy/test_debug_util'}, {'test_file': 'test_cuda_nvml_based_avail'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'torch_np/numpy_tests/linalg/test_linalg'}, {'test_file': 'test_sparse_csr'}, {'test_file': 'test_view_ops'}, {'test_file': 'test_accelerator'}, {'test_file': 'profiler/test_memory_profiler'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'test_function_schema'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'test_cpp_extensions_jit'}, {'test_file': 'test_scatter_gather_ops'}, {'test_file': 'test_serialization'}, {'test_file': 'torch_np/numpy_tests/core/test_dlpack'}, {'test_file': 'test_xnnpack_integration'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'test_mkldnn'}, {'test_file': 'test_unary_ufuncs'}, {'test_file': 'nn/test_pooling'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_methods'}, {'test_file': 'nn/test_init'}, {'test_file': 'test_cuda_primary_ctx'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'test_mobile_optimizer'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'test_cuda_multigpu'}, {'test_file': 'test_multiprocessing_spawn'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'nn/test_convolution'}, {'test_file': 'test_sparse'}, {'test_file': 'test_jit_autocast'}, {'test_file': 'test_dlpack'}, {'test_file': 'profiler/test_profiler_tree'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'profiler/test_torch_tidy'}, {'test_file': 'torch_np/test_reductions'}, {'test_file': 'lazy/test_reuse_ir'}, {'test_file': 'test_functional_autograd_benchmark'}, {'test_file': 'test_prims'}, {'test_file': 'test_spectral_ops'}, {'test_file': 'profiler/test_python_tracer'}, {'test_file': 'distributions/test_distributions'}, {'test_file': 'test_autoload_enable'}, {'test_file': 'test_cpp_extensions_aot_no_ninja'}, {'test_file': 'test_autoload_disable'}, {'test_file': 'test_cpp_extensions_aot_ninja'}], 'excluded': []} from test/test-reports/td_exclusions-acfdf47b9976ade40bde.json is not a benchmark record, skipping
2025-08-14T23:31:19.9479235Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-08-14T23:31:19.9483152Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/Dict_test'}, {'test_file': 'cpp/Dimname_test'}, {'test_file': 'cpp/NamedTensor_test'}, {'test_file': 'cpp/apply_utils_test'}, {'test_file': 'cpp/atest'}, {'test_file': 'cpp/basic'}, {'test_file': 'cpp/broadcast_test'}, {'test_file': 'cpp/cpu_generator_test'}, {'test_file': 'cpp/dlconvertor_test'}, {'test_file': 'cpp/extension_backend_test'}, {'test_file': 'cpp/lazy_tensor_test'}, {'test_file': 'cpp/legacy_vmap_test'}, {'test_file': 'cpp/native_test'}, {'test_file': 'cpp/operators_test'}, {'test_file': 'cpp/scalar_tensor_test'}, {'test_file': 'cpp/scalar_test'}, {'test_file': 'cpp/tensor_iterator_test'}, {'test_file': 'cpp/undefined_tensor_test'}, {'test_file': 'cpp/wrapdim_test'}], 'excluded': []} from test/test-reports/td_exclusions-b554103d75feac6d17f9.json is not a benchmark record, skipping
2025-08-14T23:31:19.9487165Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-08-14T23:31:19.9488805Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/test_api'}], 'excluded': []} from test/test-reports/td_exclusions-4519eb4efecf3b12f69d.json is not a benchmark record, skipping
2025-08-14T23:31:19.9490429Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-08-14T23:31:19.9492206Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/static_runtime_test'}], 'excluded': []} from test/test-reports/td_exclusions-7237d004664f507ee8d2.json is not a benchmark record, skipping
2025-08-14T23:31:19.9493915Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-08-14T23:31:19.9599758Z ##[group]Run cat test/**/*_toprint.log || true
2025-08-14T23:31:19.9600168Z cat test/**/*_toprint.log || true
2025-08-14T23:31:19.9605745Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.9606137Z env:
2025-08-14T23:31:19.9606362Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.9606826Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.9607346Z   DEVICE_NAME: 
2025-08-14T23:31:19.9607580Z   DEVICE_TYPE: 
2025-08-14T23:31:19.9607812Z ##[endgroup]
2025-08-14T23:31:19.9691291Z cat: 'test/**/*_toprint.log': No such file or directory
2025-08-14T23:31:19.9724393Z ##[group]Run kill "$MONITOR_SCRIPT_PID"
2025-08-14T23:31:19.9724763Z kill "$MONITOR_SCRIPT_PID"
2025-08-14T23:31:19.9729951Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:19.9730357Z env:
2025-08-14T23:31:19.9730581Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:19.9731043Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:19.9731567Z   DEVICE_NAME: 
2025-08-14T23:31:19.9731800Z   DEVICE_TYPE: 
2025-08-14T23:31:19.9732044Z   MONITOR_SCRIPT_PID: 41601
2025-08-14T23:31:19.9732305Z ##[endgroup]
2025-08-14T23:31:19.9873188Z Prepare all required actions
2025-08-14T23:31:19.9873637Z Getting action download info
2025-08-14T23:31:20.1143539Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a)
2025-08-14T23:31:20.3288797Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02)
2025-08-14T23:31:20.7484442Z ##[group]Run ./.github/actions/upload-test-artifacts
2025-08-14T23:31:20.7484824Z with:
2025-08-14T23:31:20.7485144Z   file-suffix: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T23:31:20.7485591Z   s3-bucket: gha-artifacts
2025-08-14T23:31:20.7485846Z env:
2025-08-14T23:31:20.7486071Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:20.7486550Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:20.7487170Z   DEVICE_NAME: 
2025-08-14T23:31:20.7487406Z   DEVICE_TYPE: 
2025-08-14T23:31:20.7487635Z ##[endgroup]
2025-08-14T23:31:20.7516217Z ##[group]Run # Remove any previous test jsons if they exist
2025-08-14T23:31:20.7516707Z # Remove any previous test jsons if they exist
2025-08-14T23:31:20.7517087Z rm -f test-jsons-*.zip
2025-08-14T23:31:20.7517528Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json'
2025-08-14T23:31:20.7523299Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:20.7523671Z env:
2025-08-14T23:31:20.7523895Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:20.7524372Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:20.7524884Z   DEVICE_NAME: 
2025-08-14T23:31:20.7525117Z   DEVICE_TYPE: 
2025-08-14T23:31:20.7525442Z   FILE_SUFFIX: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T23:31:20.7525847Z ##[endgroup]
2025-08-14T23:31:20.7690922Z   adding: test/test-reports/td_exclusions-688f017d78a116cea60c.json (deflated 16%)
2025-08-14T23:31:20.7695197Z   adding: test/test-reports/td_exclusions-acfdf47b9976ade40bde.json (deflated 82%)
2025-08-14T23:31:20.7695861Z   adding: test/test-reports/td_exclusions-b554103d75feac6d17f9.json (deflated 73%)
2025-08-14T23:31:20.7696535Z   adding: test/test-reports/td_exclusions-4519eb4efecf3b12f69d.json (deflated 18%)
2025-08-14T23:31:20.7697202Z   adding: test/test-reports/td_exclusions-7237d004664f507ee8d2.json (deflated 14%)
2025-08-14T23:31:20.7724569Z ##[group]Run # Remove any previous test reports if they exist
2025-08-14T23:31:20.7725068Z # Remove any previous test reports if they exist
2025-08-14T23:31:20.7725557Z rm -f test-reports-*.zip
2025-08-14T23:31:20.7726056Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv'
2025-08-14T23:31:20.7731690Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:20.7732087Z env:
2025-08-14T23:31:20.7732313Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:20.7732833Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:20.7733353Z   DEVICE_NAME: 
2025-08-14T23:31:20.7733584Z   DEVICE_TYPE: 
2025-08-14T23:31:20.7733898Z   FILE_SUFFIX: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T23:31:20.7734298Z ##[endgroup]
2025-08-14T23:31:20.7855850Z   adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-e8fddc04c6b28b01.xml (deflated 28%)
2025-08-14T23:31:20.7858798Z   adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-bf9890eb277a5f1b.xml (deflated 94%)
2025-08-14T23:31:20.7859903Z   adding: test/test-reports/python-pytest/test_cpp_extensions_mtia_backend/test_cpp_extensions_mtia_backend-92cac652a0da6e43.xml (deflated 72%)
2025-08-14T23:31:20.7868392Z   adding: test/test-reports/python-pytest/test_tensor_creation_ops/test_tensor_creation_ops-afc8fad07a5d7d87.xml (deflated 94%)
2025-08-14T23:31:20.7869846Z   adding: test/test-reports/python-pytest/test_cpp_extensions_stream_and_event/test_cpp_extensions_stream_and_event-c5c7e20e0b42ab82.xml (deflated 54%)
2025-08-14T23:31:20.7916826Z   adding: test/test-reports/python-pytest/test_reductions/test_reductions-14fd00367a79a5af.xml (deflated 96%)
2025-08-14T23:31:20.7955471Z   adding: test/test-reports/python-pytest/test_nn/test_nn-6051f41f4ec1d5a5.xml (deflated 96%)
2025-08-14T23:31:20.7969633Z   adding: test/test-reports/python-pytest/test_overrides/test_overrides-502f9e8ae6506bb6.xml (deflated 95%)
2025-08-14T23:31:20.7977914Z   adding: test/test-reports/python-pytest/test_cpp_api_parity/test_cpp_api_parity-d66c051d07831989.xml (deflated 96%)
2025-08-14T23:31:20.7979007Z   adding: test/test-reports/python-pytest/test_transformers_privateuse1/test_transformers_privateuse1-e7339da1b249f42e.xml (deflated 53%)
2025-08-14T23:31:20.7980116Z   adding: test/test-reports/python-pytest/test_extension_utils/test_extension_utils-94eccc6ab1dadf6a.xml (deflated 53%)
2025-08-14T23:31:20.8004403Z   adding: test/test-reports/python-pytest/test_fx/test_fx-e68b2b9f2aad8a6c.xml (deflated 94%)
2025-08-14T23:31:20.8010513Z   adding: test/test-reports/python-pytest/test_fake_tensor/test_fake_tensor-df115a0a747f7c1d.xml (deflated 92%)
2025-08-14T23:31:20.8011764Z   adding: test/test-reports/python-pytest/test_openreg/test_openreg-6d957b518846664a.xml (deflated 79%)
2025-08-14T23:31:20.8012661Z   adding: test/test-reports/python-pytest/test_show_pickle/test_show_pickle-801a16a546f2f111.xml (deflated 37%)
2025-08-14T23:31:20.8013587Z   adding: test/test-reports/python-pytest/test_tensorexpr/test_tensorexpr-a1058c1034c5eafe.xml (deflated 88%)
2025-08-14T23:31:20.8029064Z   adding: test/test-reports/python-pytest/test_torch/test_torch-12713f3a98a10b2a.xml (deflated 92%)
2025-08-14T23:31:20.8093483Z   adding: test/test-reports/python-pytest/test_utils/test_utils-3264747cdd913576.xml (deflated 96%)
2025-08-14T23:31:20.8095842Z   adding: test/test-reports/python-pytest/test_python_dispatch/test_python_dispatch-282f7879e3b8fc4d.xml (deflated 86%)
2025-08-14T23:31:20.8096806Z   adding: test/test-reports/python-pytest/test_dispatch/test_dispatch-8280ecaed010f995.xml (deflated 85%)
2025-08-14T23:31:20.8097807Z   adding: test/test-reports/python-pytest/test_namedtuple_return_api/test_namedtuple_return_api-626e9911506d20c7.xml (deflated 73%)
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2025-08-14T23:31:21.0518961Z ##[group]Run # Remove any previous usage logs if they exist
2025-08-14T23:31:21.0519447Z # Remove any previous usage logs if they exist
2025-08-14T23:31:21.0519853Z rm -f logs-*.zip
2025-08-14T23:31:21.0520203Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true
2025-08-14T23:31:21.0520730Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true
2025-08-14T23:31:21.0526458Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:21.0526854Z env:
2025-08-14T23:31:21.0527082Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:21.0527561Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:21.0528178Z   DEVICE_NAME: 
2025-08-14T23:31:21.0528410Z   DEVICE_TYPE: 
2025-08-14T23:31:21.0528746Z   FILE_SUFFIX: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T23:31:21.0529142Z ##[endgroup]
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2025-08-14T23:31:21.4155878Z   adding: test/test-reports/cpp.static_runtime_test_1.1_a684d068db774504_.log (deflated 73%)
2025-08-14T23:31:21.4166232Z   adding: test/test-reports/cpp.static_runtime_test_1.1_9efb44ff082c679d_.log (deflated 89%)
2025-08-14T23:31:21.4197771Z ##[group]Run # Remove any previous debugging artifacts if they exist
2025-08-14T23:31:21.4198324Z # Remove any previous debugging artifacts if they exist
2025-08-14T23:31:21.4198745Z rm -f debug-*.zip
2025-08-14T23:31:21.4199038Z if [ -d 'test/debug' ]; then
2025-08-14T23:31:21.4199392Z   zip -r "debug-${FILE_SUFFIX}.zip" test/debug
2025-08-14T23:31:21.4199812Z fi
2025-08-14T23:31:21.4205309Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:21.4205689Z env:
2025-08-14T23:31:21.4205928Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:21.4206406Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:21.4206909Z   DEVICE_NAME: 
2025-08-14T23:31:21.4207146Z   DEVICE_TYPE: 
2025-08-14T23:31:21.4207486Z   FILE_SUFFIX: test-crossref-1-2-lf.linux.2xlarge_48127032084
2025-08-14T23:31:21.4207885Z ##[endgroup]
2025-08-14T23:31:21.4297105Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-08-14T23:31:21.4297434Z with:
2025-08-14T23:31:21.4297637Z   s3-bucket: gha-artifacts
2025-08-14T23:31:21.4297955Z   s3-prefix: pytorch/pytorch/16976255017/1/artifact

2025-08-14T23:31:21.4298302Z   retention-days: 14
2025-08-14T23:31:21.4298539Z   if-no-files-found: warn
2025-08-14T23:31:21.4298803Z   path: test-jsons-*.zip
2025-08-14T23:31:21.4299048Z   name: artifact
2025-08-14T23:31:21.4299270Z   region: us-east-1
2025-08-14T23:31:21.4299476Z env:
2025-08-14T23:31:21.4299682Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:21.4300150Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:21.4300655Z   DEVICE_NAME: 
2025-08-14T23:31:21.4300888Z   DEVICE_TYPE: 
2025-08-14T23:31:21.4301117Z ##[endgroup]
2025-08-14T23:31:21.9347109Z NOTE: s3-prefix specified, ignoring name parameter
2025-08-14T23:31:21.9347610Z With the provided path, there will be 1 file uploaded
2025-08-14T23:31:21.9348076Z Uploading to s3 prefix: pytorch/pytorch/16976255017/1/artifact
2025-08-14T23:31:22.0651622Z Starting upload of test-jsons-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:22.2218230Z Finished upload of test-jsons-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:22.2424461Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-08-14T23:31:22.2424802Z with:
2025-08-14T23:31:22.2425033Z   s3-bucket: gha-artifacts
2025-08-14T23:31:22.2425383Z   s3-prefix: pytorch/pytorch/16976255017/1/artifact

2025-08-14T23:31:22.2425745Z   retention-days: 14
2025-08-14T23:31:22.2425997Z   if-no-files-found: error
2025-08-14T23:31:22.2426386Z   path: test-reports-*.zip
2025-08-14T23:31:22.2426660Z   name: artifact
2025-08-14T23:31:22.2426884Z   region: us-east-1
2025-08-14T23:31:22.2427117Z env:
2025-08-14T23:31:22.2427336Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:22.2427814Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:22.2428330Z   DEVICE_NAME: 
2025-08-14T23:31:22.2428562Z   DEVICE_TYPE: 
2025-08-14T23:31:22.2428781Z ##[endgroup]
2025-08-14T23:31:22.5684561Z NOTE: s3-prefix specified, ignoring name parameter
2025-08-14T23:31:22.5685357Z With the provided path, there will be 1 file uploaded
2025-08-14T23:31:22.5686168Z Uploading to s3 prefix: pytorch/pytorch/16976255017/1/artifact
2025-08-14T23:31:22.5727275Z Starting upload of test-reports-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:22.7938235Z Finished upload of test-reports-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:22.8127348Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-08-14T23:31:22.8127710Z with:
2025-08-14T23:31:22.8127945Z   s3-bucket: gha-artifacts
2025-08-14T23:31:22.8128277Z   s3-prefix: pytorch/pytorch/16976255017/1/artifact

2025-08-14T23:31:22.8128640Z   retention-days: 14
2025-08-14T23:31:22.8128905Z   if-no-files-found: ignore
2025-08-14T23:31:22.8129183Z   path: logs-*.zip
2025-08-14T23:31:22.8129421Z   name: artifact
2025-08-14T23:31:22.8129644Z   region: us-east-1
2025-08-14T23:31:22.8129875Z env:
2025-08-14T23:31:22.8130093Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:22.8130554Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:22.8131066Z   DEVICE_NAME: 
2025-08-14T23:31:22.8131294Z   DEVICE_TYPE: 
2025-08-14T23:31:22.8131508Z ##[endgroup]
2025-08-14T23:31:23.1397533Z NOTE: s3-prefix specified, ignoring name parameter
2025-08-14T23:31:23.1398227Z With the provided path, there will be 1 file uploaded
2025-08-14T23:31:23.1398703Z Uploading to s3 prefix: pytorch/pytorch/16976255017/1/artifact
2025-08-14T23:31:23.1438168Z Starting upload of logs-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:23.3065532Z Finished upload of logs-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:23.3250547Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-08-14T23:31:23.3250891Z with:
2025-08-14T23:31:23.3251122Z   s3-bucket: gha-artifacts
2025-08-14T23:31:23.3251452Z   s3-prefix: pytorch/pytorch/16976255017/1/artifact

2025-08-14T23:31:23.3251813Z   retention-days: 14
2025-08-14T23:31:23.3252062Z   if-no-files-found: ignore
2025-08-14T23:31:23.3252340Z   path: debug-*.zip
2025-08-14T23:31:23.3252579Z   name: artifact
2025-08-14T23:31:23.3252804Z   region: us-east-1
2025-08-14T23:31:23.3253037Z env:
2025-08-14T23:31:23.3253254Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:23.3253723Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:23.3254232Z   DEVICE_NAME: 
2025-08-14T23:31:23.3254462Z   DEVICE_TYPE: 
2025-08-14T23:31:23.3254684Z ##[endgroup]
2025-08-14T23:31:23.6453835Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded.
2025-08-14T23:31:23.6641676Z ##[group]Run # shellcheck disable=SC2156
2025-08-14T23:31:23.6642073Z # shellcheck disable=SC2156
2025-08-14T23:31:23.6642659Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
2025-08-14T23:31:23.6649388Z shell: /usr/bin/bash -e {0}
2025-08-14T23:31:23.6649680Z env:
2025-08-14T23:31:23.6649907Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:23.6650372Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:23.6650888Z   DEVICE_NAME: 
2025-08-14T23:31:23.6651124Z   DEVICE_TYPE: 
2025-08-14T23:31:23.6651345Z ##[endgroup]
2025-08-14T23:31:23.9562613Z Prepare all required actions
2025-08-14T23:31:23.9563030Z Getting action download info
2025-08-14T23:31:24.0568328Z ##[group]Run ./.github/actions/upload-utilization-stats
2025-08-14T23:31:24.0568795Z with:
2025-08-14T23:31:24.0569018Z   job_id: 48127032084
2025-08-14T23:31:24.0569429Z   job_name: linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T23:31:24.0569896Z   workflow_name: pull
2025-08-14T23:31:24.0570160Z   workflow_run_id: 16976255017
2025-08-14T23:31:24.0570446Z   workflow_attempt: 1
2025-08-14T23:31:24.0570687Z env:
2025-08-14T23:31:24.0570894Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:24.0571367Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:24.0571878Z   DEVICE_NAME: 
2025-08-14T23:31:24.0572099Z   DEVICE_TYPE: 
2025-08-14T23:31:24.0572329Z ##[endgroup]
2025-08-14T23:31:24.0590956Z ##[group]Run echo "workflow_id: 16976255017"
2025-08-14T23:31:24.0591366Z echo "workflow_id: 16976255017"
2025-08-14T23:31:24.0591813Z echo "workflow_attempt: 1"
2025-08-14T23:31:24.0592139Z echo "workflow_Name: pull"
2025-08-14T23:31:24.0592453Z echo "job_id: 48127032084"
2025-08-14T23:31:24.0592969Z echo "job_name:  linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)"
2025-08-14T23:31:24.0593492Z echo "artifact_prefix: "
2025-08-14T23:31:24.0593804Z python3 --version
2025-08-14T23:31:24.0599321Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:24.0599694Z env:
2025-08-14T23:31:24.0599919Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:24.0600391Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:24.0600890Z   DEVICE_NAME: 
2025-08-14T23:31:24.0601120Z   DEVICE_TYPE: 
2025-08-14T23:31:24.0601350Z ##[endgroup]
2025-08-14T23:31:24.0624791Z workflow_id: 16976255017
2025-08-14T23:31:24.0625124Z workflow_attempt: 1
2025-08-14T23:31:24.0625524Z workflow_Name: pull
2025-08-14T23:31:24.0625779Z job_id: 48127032084
2025-08-14T23:31:24.0626197Z job_name:  linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)
2025-08-14T23:31:24.0626675Z artifact_prefix: 
2025-08-14T23:31:24.0637028Z Python 3.9.23
2025-08-14T23:31:24.0687431Z ##[group]Run nick-fields/retry@v3.0.0
2025-08-14T23:31:24.0687742Z with:
2025-08-14T23:31:24.0687955Z   shell: bash
2025-08-14T23:31:24.0688185Z   timeout_minutes: 5
2025-08-14T23:31:24.0688424Z   max_attempts: 5
2025-08-14T23:31:24.0688666Z   retry_wait_seconds: 30
2025-08-14T23:31:24.0689224Z   command: set -eu
python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3 dataclasses_json==0.6.7

2025-08-14T23:31:24.0689825Z   polling_interval_seconds: 1
2025-08-14T23:31:24.0690115Z   warning_on_retry: true
2025-08-14T23:31:24.0690382Z   continue_on_error: false
2025-08-14T23:31:24.0690631Z env:
2025-08-14T23:31:24.0690849Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:24.0691339Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:24.0691858Z   DEVICE_NAME: 
2025-08-14T23:31:24.0692079Z   DEVICE_TYPE: 
2025-08-14T23:31:24.0692311Z ##[endgroup]
2025-08-14T23:31:24.4239382Z Defaulting to user installation because normal site-packages is not writeable
2025-08-14T23:31:24.4992352Z Collecting python-dateutil==2.8.2
2025-08-14T23:31:24.5138870Z   Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB)
2025-08-14T23:31:25.4949557Z Collecting boto3==1.35.42
2025-08-14T23:31:25.4986327Z   Downloading boto3-1.35.42-py3-none-any.whl (139 kB)
2025-08-14T23:31:26.0101122Z Collecting pandas==2.1.3
2025-08-14T23:31:26.0139771Z   Downloading pandas-2.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB)
2025-08-14T23:31:26.1507196Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/ec2-user/.local/lib/python3.9/site-packages (0.6.7)
2025-08-14T23:31:26.1526053Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil==2.8.2) (1.15.0)
2025-08-14T23:31:26.1571695Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.4)
2025-08-14T23:31:26.1577464Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.0)
2025-08-14T23:31:26.1581508Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (1.35.99)
2025-08-14T23:31:26.2214742Z Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3.9/site-packages (from pandas==2.1.3) (2022.7.1)
2025-08-14T23:31:26.2548918Z Collecting tzdata>=2022.1
2025-08-14T23:31:26.2584205Z   Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB)
2025-08-14T23:31:27.0976525Z Collecting numpy<2,>=1.22.4
2025-08-14T23:31:27.1016196Z   Downloading numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)
2025-08-14T23:31:27.2979398Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (0.9.0)
2025-08-14T23:31:27.2983613Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (3.26.1)
2025-08-14T23:31:27.3044056Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.25.10)
2025-08-14T23:31:27.3161575Z Requirement already satisfied: packaging>=17.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0)
2025-08-14T23:31:27.3267113Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0)
2025-08-14T23:31:27.3273212Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.14.1)
2025-08-14T23:31:27.4917102Z Installing collected packages: python-dateutil, tzdata, numpy, pandas, boto3
2025-08-14T23:31:32.5391981Z   Attempting uninstall: boto3
2025-08-14T23:31:32.5392990Z     Found existing installation: boto3 1.35.33
2025-08-14T23:31:32.5491980Z     Uninstalling boto3-1.35.33:
2025-08-14T23:31:32.5505659Z       Successfully uninstalled boto3-1.35.33
2025-08-14T23:31:32.6078625Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 tzdata-2025.2
2025-08-14T23:31:33.1636123Z Command completed after 1 attempt(s).
2025-08-14T23:31:33.1698679Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-08-14T23:31:33.1699403Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-08-14T23:31:33.1699916Z   --workflow-run-id "16976255017" \
2025-08-14T23:31:33.1700295Z   --workflow-name "pull" \
2025-08-14T23:31:33.1700639Z   --workflow-run-attempt "1" \
2025-08-14T23:31:33.1700976Z   --job-id "48127032084" \
2025-08-14T23:31:33.1701467Z   --job-name "linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)" \
2025-08-14T23:31:33.1702011Z   --local-path "" \
2025-08-14T23:31:33.1702312Z   --artifact-prefix ""
2025-08-14T23:31:33.1707814Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:33.1708189Z env:
2025-08-14T23:31:33.1708416Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:33.1708897Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:33.1709636Z   DEVICE_NAME: 
2025-08-14T23:31:33.1709873Z   DEVICE_TYPE: 
2025-08-14T23:31:33.1710110Z ##[endgroup]
2025-08-14T23:31:35.6945299Z repo: pytorch/pytorch
2025-08-14T23:31:35.6945715Z Search for test log in s3 bucket: ossci-utilization
2025-08-14T23:31:35.6946621Z Downloading logs-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:35.6947313Z extracting usage_log.txt from zip file logs-test-crossref-1-2-lf.linux.2xlarge_48127032084.zip
2025-08-14T23:31:35.6947872Z Converted Log Model: UtilizationMetadata:
2025-08-14T23:31:35.6949320Z  UtilizationMetadata(level='metadata', workflow_id='16976255017', job_id='48127032084', workflow_name='pull', job_name='linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)', usage_collect_interval=1.0, data_model_version=1.5, start_at=1755205614, gpu_count=0, cpu_count=8, gpu_type=None, error=None)
2025-08-14T23:31:35.6950771Z [Db Segments] detected pytest cmd: 25, generated segments: 25
2025-08-14T23:31:35.6951194Z [db model] Peek db timeseries 
2025-08-14T23:31:35.6951462Z :{
2025-08-14T23:31:35.6951782Z     "created_at": 1755214295,
2025-08-14T23:31:35.6952079Z     "type": "utilization",
2025-08-14T23:31:35.6952335Z     "tags": [
2025-08-14T23:31:35.6952562Z         "record"
2025-08-14T23:31:35.6952790Z     ],
2025-08-14T23:31:35.6953020Z     "time_stamp": 1755205614,
2025-08-14T23:31:35.6953299Z     "repo": "pytorch/pytorch",
2025-08-14T23:31:35.6953587Z     "workflow_id": 16976255017,
2025-08-14T23:31:35.6953871Z     "run_attempt": 1,
2025-08-14T23:31:35.6954114Z     "job_id": 48127032084,
2025-08-14T23:31:35.6954392Z     "workflow_name": "pull",
2025-08-14T23:31:35.6954837Z     "job_name": "linux-jammy-py3.13-clang12 / test (crossref, 1, 2, lf.linux.2xlarge)",
2025-08-14T23:31:35.6955305Z     "json_data": "{}"
2025-08-14T23:31:35.6955547Z }
2025-08-14T23:31:35.6956058Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/16976255017/1/48127032084/metadata
2025-08-14T23:31:35.6956996Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/16976255017/1/48127032084/metadata 
2025-08-14T23:31:35.6957983Z Writing 1729 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/16976255017/1/48127032084/time_series
2025-08-14T23:31:35.6958997Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/16976255017/1/48127032084/time_series 
2025-08-14T23:31:35.8342827Z ##[group]Run pytorch/test-infra/.github/actions/teardown-linux@main
2025-08-14T23:31:35.8343302Z with:
2025-08-14T23:31:35.8343518Z env:
2025-08-14T23:31:35.8343725Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:35.8344202Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:35.8344715Z   DEVICE_NAME: 
2025-08-14T23:31:35.8344944Z   DEVICE_TYPE: 
2025-08-14T23:31:35.8345162Z ##[endgroup]
2025-08-14T23:31:35.8371465Z ##[group]Run set -eou pipefail
2025-08-14T23:31:35.8371809Z set -eou pipefail
2025-08-14T23:31:35.8372088Z 
2025-08-14T23:31:35.8372470Z echo "Holding runner for 2 hours until all ssh sessions have logged out"
2025-08-14T23:31:35.8372942Z for _ in $(seq 1440); do
2025-08-14T23:31:35.8373290Z     # Break if no ssh session exists anymore
2025-08-14T23:31:35.8373668Z     if [ "$(who)" = "" ]; then
2025-08-14T23:31:35.8373969Z       break
2025-08-14T23:31:35.8374254Z     fi
2025-08-14T23:31:35.8374483Z     echo "."
2025-08-14T23:31:35.8374740Z     sleep 5
2025-08-14T23:31:35.8374983Z done
2025-08-14T23:31:35.8380570Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:35.8380971Z env:
2025-08-14T23:31:35.8381202Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:35.8381676Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:35.8382180Z   DEVICE_NAME: 
2025-08-14T23:31:35.8382412Z   DEVICE_TYPE: 
2025-08-14T23:31:35.8382641Z ##[endgroup]
2025-08-14T23:31:35.8405532Z Holding runner for 2 hours until all ssh sessions have logged out
2025-08-14T23:31:35.8498593Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty
2025-08-14T23:31:35.8499367Z # ignore expansion of "docker ps -q" since it could be empty
2025-08-14T23:31:35.8499824Z # shellcheck disable=SC2046
2025-08-14T23:31:35.8500198Z docker stop $(docker ps -q) || true
2025-08-14T23:31:35.8500546Z # Prune all of the docker images
2025-08-14T23:31:35.8500976Z docker system prune -af
2025-08-14T23:31:35.8506596Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:35.8506971Z env:
2025-08-14T23:31:35.8507202Z   GIT_DEFAULT_BRANCH: main
2025-08-14T23:31:35.8507680Z   DOCKER_CONTAINER_ID: 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:35.8508184Z   DEVICE_NAME: 
2025-08-14T23:31:35.8508421Z   DEVICE_TYPE: 
2025-08-14T23:31:35.8508651Z ##[endgroup]
2025-08-14T23:31:47.0274393Z 363edb3ac314
2025-08-14T23:31:47.7476441Z Deleted Containers:
2025-08-14T23:31:47.7476906Z 363edb3ac314befa9c3d4e20f7345404b892c8fe537024d56974bba42f94746a
2025-08-14T23:31:47.7477258Z 
2025-08-14T23:31:54.9145782Z Deleted Images:
2025-08-14T23:31:54.9147119Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-bfa89110622ba7202628e9faac705f183070defe
2025-08-14T23:31:54.9148384Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image@sha256:e5a191418e9f11a59a218b040bad54b9c3113ac41271ba5a6874e1c6d47db7c7
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2025-08-14T23:31:54.9201012Z 
2025-08-14T23:31:54.9345503Z Total reclaimed space: 11.43GB
2025-08-14T23:31:54.9476360Z Post job cleanup.
2025-08-14T23:31:54.9549628Z Post job cleanup.
2025-08-14T23:31:55.0606155Z [command]/usr/bin/git version
2025-08-14T23:31:55.0835670Z git version 2.47.1
2025-08-14T23:31:55.0873817Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/b19ab3f4-46bf-4faa-bb25-c66225e3e84e/.gitconfig'
2025-08-14T23:31:55.0883151Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/b19ab3f4-46bf-4faa-bb25-c66225e3e84e' before making global git config changes
2025-08-14T23:31:55.0884558Z Adding repository directory to the temporary git global config as a safe directory
2025-08-14T23:31:55.0889080Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-08-14T23:31:55.0940700Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-08-14T23:31:55.0981893Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :"
2025-08-14T23:31:55.1409285Z Entering 'android/libs/fbjni'
2025-08-14T23:31:55.1475959Z Entering 'third_party/FP16'
2025-08-14T23:31:55.1538280Z Entering 'third_party/FXdiv'
2025-08-14T23:31:55.1599883Z Entering 'third_party/NNPACK'
2025-08-14T23:31:55.1664249Z Entering 'third_party/NVTX'
2025-08-14T23:31:55.1720775Z Entering 'third_party/VulkanMemoryAllocator'
2025-08-14T23:31:55.1775348Z Entering 'third_party/XNNPACK'
2025-08-14T23:31:55.1914394Z Entering 'third_party/aiter'
2025-08-14T23:31:55.1977991Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-08-14T23:31:55.2045867Z Entering 'third_party/benchmark'
2025-08-14T23:31:55.2110124Z Entering 'third_party/composable_kernel'
2025-08-14T23:31:55.2173517Z Entering 'third_party/cpp-httplib'
2025-08-14T23:31:55.2227698Z Entering 'third_party/cpuinfo'
2025-08-14T23:31:55.2293398Z Entering 'third_party/cudnn_frontend'
2025-08-14T23:31:55.2350733Z Entering 'third_party/cutlass'
2025-08-14T23:31:55.2417626Z Entering 'third_party/fbgemm'
2025-08-14T23:31:55.2516610Z Entering 'third_party/fbgemm/external/asmjit'
2025-08-14T23:31:55.2597044Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-08-14T23:31:55.2719865Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-08-14T23:31:55.2800349Z Entering 'third_party/fbgemm/external/cutlass'
2025-08-14T23:31:55.2922608Z Entering 'third_party/fbgemm/external/googletest'
2025-08-14T23:31:55.3001628Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-08-14T23:31:55.3077805Z Entering 'third_party/fbgemm/external/json'
2025-08-14T23:31:55.3150424Z Entering 'third_party/flash-attention'
2025-08-14T23:31:55.3205120Z Entering 'third_party/flash-attention/csrc/composable_kernel'
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2025-08-14T23:31:55.6176534Z Entering 'third_party/tensorpipe'
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2025-08-14T23:31:55.6650198Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-08-14T23:31:55.6670122Z http.https://github.com/.extraheader
2025-08-14T23:31:55.6680045Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader
2025-08-14T23:31:55.6710848Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :"
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2025-08-14T23:31:55.9937155Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
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2025-08-14T23:31:56.0008726Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
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2025-08-14T23:31:56.0146824Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
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2025-08-14T23:31:56.1010782Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
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2025-08-14T23:31:56.1079284Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
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2025-08-14T23:31:56.1150148Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-08-14T23:31:56.1186501Z http.https://github.com/.extraheader
2025-08-14T23:31:56.1221688Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-08-14T23:31:56.1259658Z http.https://github.com/.extraheader
2025-08-14T23:31:56.1294906Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
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2025-08-14T23:31:56.1366670Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
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2025-08-14T23:31:56.1438909Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
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2025-08-14T23:31:56.1511803Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
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2025-08-14T23:31:56.2508377Z http.https://github.com/.extraheader
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2025-08-14T23:31:56.2576790Z http.https://github.com/.extraheader
2025-08-14T23:31:56.2608610Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-08-14T23:31:56.2643997Z http.https://github.com/.extraheader
2025-08-14T23:31:56.2769051Z A job completed hook has been configured by the self-hosted runner administrator
2025-08-14T23:31:56.2801695Z ##[group]Run '/home/ec2-user/runner-scripts/after_job.sh'
2025-08-14T23:31:56.2806783Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-08-14T23:31:56.2807195Z ##[endgroup]
2025-08-14T23:32:06.4724553Z Cleaning up orphan processes